US20130274923A1 - Active Alignment Using Continuous Motion Sweeps and Temporal Interpolation - Google Patents
Active Alignment Using Continuous Motion Sweeps and Temporal Interpolation Download PDF
optical element
Andre By
AUTOMATION ENGR Inc
2013-04-12 Application filed by AUTOMATION ENGR Inc filed Critical AUTOMATION ENGR Inc
2013-04-16 Assigned to AUTOMATION ENGINEERING, INC. reassignment AUTOMATION ENGINEERING, INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: BY, Andre
2013-08-22 Assigned to MASSACHUSETTS GROWTH CAPITAL CORPORATION reassignment MASSACHUSETTS GROWTH CAPITAL CORPORATION SECURITY AGREEMENT Assignors: AUTOMATION ENGINEERING, INC.
2013-10-21 Assigned to MASSACHUSETTS GROWTH CAPITAL CORPORATION reassignment MASSACHUSETTS GROWTH CAPITAL CORPORATION CORRECTIVE ASSIGNMENT TO CORRECT THE 13861884 PREVIOUSLY RECORDED ON REEL 031422 FRAME 0131. ASSIGNOR(S) HEREBY CONFIRMS THE SECURITY AGREEMENT. Assignors: AUTOMATION ENGINEERING, INC.
2013-12-16 Assigned to MASSACHUSETTS GROWTH CAPITAL CORPORATION reassignment MASSACHUSETTS GROWTH CAPITAL CORPORATION RELEASE BY SECURED PARTY (SEE DOCUMENT FOR DETAILS). Assignors: AUTOMATION ENGINEERING, INC.
B—PERFORMING OPERATIONS; TRANSPORTING
B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
B25J9/00—Programme-controlled manipulators
B25J9/16—Programme controls
B25J9/1694—Programme controls characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
B25J9/1697—Vision controlled systems
G02—OPTICS
G02B—OPTICAL ELEMENTS, SYSTEMS, OR APPARATUS
G02B13/00—Optical objectives specially designed for the purposes specified below
G02B13/001—Miniaturised objectives for electronic devices, e.g. portable telephones, webcams, PDAs, small digital cameras
G02B27/00—Other optical systems; Other optical apparatus
G02B27/62—Optical apparatus specially adapted for adjusting optical elements during the assembly of optical systems
G02B7/00—Mountings, adjusting means, or light-tight connections, for optical elements
G02B7/003—Alignment of optical elements
G02B7/005—Motorised alignment
Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
Y10S901/00—Robots
Y10S901/46—Sensing device
Y10S901/47—Optical
Methods and apparatus for actively aligning a first optical element, such as a lens, to a second optical element, such as an image sensor, use continuous scans, even absent a synchronization signal from one of the optical elements. During a scan, timed position information about the scanned optical element is collected, and then a relationship between position of the scanned optical element and time is estimated, such as by fitting a curve to a set of position-time pairs. This relationship can then be used to estimate locations of the scanned optical element at times when image data or other alignment quality-indicating data samples are acquired. From this alignment quality versus location data, an optimum alignment position can be determined, and the scanned optical element can then be positioned at the determined alignment position.
This application claims the benefit of U.S. Provisional Patent Application No. 61/623,932, filed Apr. 13, 2012, titled "Active Alignment Using Continuous Motion Sweeps and Temporal Interpolation," the entire contents of which are hereby incorporated by reference herein, for all purposes.
The present invention relates to automatic robotic alignment of optical components during manufacture or testing and, more particularly, to apparatus and methods that involve continuous motion sweeps of the optical components through potential alignment positions to optimize placement of the optical components.
Robots are used in many precision manufacturing processes. For example, robots are used to precisely align lenses before digital camera sensors, such as in the manufacture of cell phones and backup cameras for automobiles. In other examples, robots align ends of optical fibers before lasers or light sensors in the manufacture of telecommunication and computer network equipment. Many of the lenses are quite small, on the order of several millimeters in diameter, and must, therefore, be positioned with high precision, often on the order of about ±5 μm or less, relative to the sensors or lasers.
To keep costs down, less-than-precise methods are often used to manufacture optical elements for the lenses and to mount the optical elements in lens housings. Consequently, the optical elements and lenses are often not uniform, from piece to piece. That is, dimensions and symmetries of the components often vary from lens to lens or other optical components, resulting in variations in focal length and orientation of the optical axes of the components.
To compensate for such variations, several known methods are used to custom align each lens to its corresponding image sensor. One method involves mounting a finely threaded bracket to the sensor and mounting a group of optical elements in a complementarily threaded barrel. The distance between the optical elements and the sensor can then be adjusted as the lens barrel is threaded into the bracket. Once the optical elements are disposed a desired distance from the sensor, the barrel may be fixed, relative to the bracket, to prevent further rotation. Unfortunately, this method allows adjustment of only the distance between the optical elements and the sensor along the z axis (the optical axis). Thus, this method is referred to as aligning with only one degree of freedom. Such an alignment methodology cannot compensate for all potential asymmetries in the optical elements or imperfect alignment of the optical elements within the barrel.
A more sophisticated method, developed by Automation Engineering, Inc. ("AEi"), Wilmington, Mass., involves attaching the lens barrel (which in this case does not require threads) to the image sensor or its substrate or a camera housing that includes the image sensor by an adhesive with camera module or other opto-electronic product component geometries such that more than one degree of freedom alignment is possible. The position of the lens barrel, relative to the image sensor, is adjusted in free space by a robot, which then holds the lens barrel in position until the adhesive cures sufficiently to prevent objectionable creep once the robot releases the lens barrel. Using this method, the position of the lens may be adjusted along all three linear axes (x, y and z), and pitch (rotation about the x axis) and roll (rotation about the y axis) of the lens may be adjusted, to achieve a lens position and orientation, relative to the sensor, that compensates for imperfections in the optical elements and in the way the optical elements are mounted within the barrel with respect to the position of the image sensor. This method is referred to as aligning about five degrees of freedom.
A refinement of this method, also develop by Automation Engineering, Inc., involves the robot rotating the lens about the optical axis of the lens or about the z axis to optimize image quality, to compensate for angular lens asymmetries in this axis. Note that alignment about the optical or z axis is generally not possible with the threaded barrel alignment method, because it is highly unlikely to simultaneously achieve both a desired lens-to-sensor spacing (by threading the barrel in or out) and a desired lens rotation angle (by rotating the barrel). Adding this refinement to the 5-degree of freedom alignment method provides a 6-degree of freedom alignment.
"Passive alignment" involves aligning components to each other based on design specifications of the components, using precision mechanical fixtures, tooling, physical characteristics (fiducials) on surfaces of components and the like. For example, a target design focal length of a lens may be used to position the lens, relative to a sensor. However, passive alignment assumes components perfectly conform to their theoretical design specifications. This, of course, does not typically occur with real-world products. Thus, passive alignment methods are typically unable to compensate adequately for piece-to-piece variations in components, such as lenses, unless each piece is individually tested to ascertain its actual specifications.
In contrast, "active alignment" involves measuring one or more key performance attributes of a combination of components during manufacture and using the measured attributes in a feedback loop to control the manufacture. For example, a visual target, such as a test pattern, may be disposed within a viewing angle of a lens-and-image-sensor combination while a robot steps the lens through a series of discrete positions (ex., along the x, y and z axes) and orientations (ex., tips, tilts and rotations about the z axis). A computer analyzes image data from the sensor at each step and, based on this analysis, the computer controls the robot to position and orient the lens for optimum image quality. The lens is then fixed in position, relative to the sensor, such as by an adhesive. Active alignment is, therefore, able to compensate for piece to piece variations in components.
While active alignment requires hardware and software not necessary for passive alignment, active alignment may not necessarily be more expensive than passive alignment. For example, active alignment can often be performed using less accurate and, therefore, less expensive fixturing and motion stages in a given manufacturing station. Active alignment can also provide higher manufacturing yield, which results in reduced manufacturing costs. However, stepping through all the test positions and orientations takes time. Manufacturers constantly seek to shorten cycle times and, thus, speed up manufacturing processes.
SUMMARY OF EMBODIMENTS
An embodiment of the present invention provides a computer-implemented method for actively aligning a first optical element to a second optical element. The method involves performing operations by a processor. A robot continuously scans the first optical element along a trajectory from a starting location to an ending location. While the robot continuously scans the first optical element from the starting location to the ending location, a plurality of time spaced-apart positions of the first optical element are stored. In addition, a plurality of time spaced-apart alignment data items is acquired. Each alignment data item of the plurality of time spaced-apart alignment data items results from an optical signal that passed through the first optical element and was received by the second optical element. Each alignment data item contains data indicative of a degree of optical alignment between the first optical element and the second optical element. A desired alignment position is estimated. The estimate is based at least in part on the plurality of time spaced-apart alignment data items and the plurality of time spaced-apart positions of the first optical element. The robot moves the first optical element to the desired alignment position.
For each alignment data item, a corresponding position of the first optical element may be stored in timed relation with acquiring image data for the alignment data item.
Optionally, for each alignment data item, a synchronization signal may be generated in timed relation with acquisition of the alignment data item.
For each position of the plurality of time spaced-apart positions, a position of the first optical element may be stored in response to the synchronization signal.
Optionally, a relationship may be estimated between: (a) degree of optical alignment between the first optical element and the second optical element and (b) position of the first optical element. The relationship may be estimated based on the plurality of time spaced-apart alignment data items and the plurality of time spaced-apart positions of the first optical element. Estimating the desired alignment position may be based on the relationship.
The second optical element may include a digital image sensor. For each alignment data item of the plurality of time spaced-apart alignment data items, image data may be acquired for a respective image from the digital image sensor, and the synchronization signal may be generated in timed relation with acquiring the image data.
The digital image sensor may generate the synchronization signal.
For each position of the plurality of time spaced-apart positions of the first optical element, a corresponding acquisition time at which the position was acquired may be stored. A first relationship between: (a) position of the first optical element and (b) time may be estimated, based on the plurality of time spaced-apart positions of the first optical element and the respective acquisition time of each position. A plurality of positions of the first optical element may be estimated, corresponding to times when respective ones of the time-spaced apart alignment data items were acquired. The estimate may be made using times at which the time spaced-apart alignment data items were acquired and the first relationship. A second relationship between: (a) degree of optical alignment between the first optical element and the second optical element and (b) position of the first optical element may be estimated. The estimate may be based on the plurality of time spaced-apart alignment data items and the plurality of positions of the first optical element. Estimating the desired alignment position may involve estimating the desired alignment position based on the second relationship.
Storing a corresponding acquisition time may involve accessing a first clock. Acquiring the plurality of time spaced-apart alignment data items may involve, for each alignment data item of the plurality of time spaced-apart alignment data items, accessing a second clock. The second clock is distinct from the first clock. The first clock may be synchronized with the second clock. Optionally or alternatively, an offset between the first clock and the second clock may be calculated, and the offset may be stored.
The first optical element may include a lens, and the second optical element may include an image sensor. A target may be positioned, such that the lens projects an image of the target on the image sensor. The data indicative of the degree of optical alignment between the first optical element and the second optical element may include image data acquired from the image sensor.
Estimating the second relationship may involve analyzing the image data to calculate a plurality of focus scores. The degree of optical alignment between the first optical element and the second optical element may be based on the plurality of focus scores.
Another embodiment of the present invention provides a system for actively aligning a first optical element to a second optical element. The system includes a robot, a motion controller, a measurement controller and an alignment processor. The robot is configured to grasp the first optical element. The motion controller is configured to cause the robot to continuously scan the first optical element along a trajectory from a starting location to an ending location. While the robot continuously scans the first optical element from the starting location to the ending location, a plurality of time spaced-apart positions of the first optical element are stored. The measurement controller is configured, while the robot continuously scans the first optical element from the starting location to the ending location, to acquire a plurality of time spaced-apart alignment data items. Each alignment data item results from an optical signal that passed through the first optical element and was received by the second optical element. Each alignment data item contains data indicative of a degree of optical alignment between the first optical element and the second optical element. The alignment processor is configured to estimate a desired alignment position, based at least in part on the plurality of time spaced-apart alignment data items and the plurality of time spaced-apart positions of the first optical element. The alignment processor causes the robot to move the first optical element to the desired alignment position.
The motion controller may be configured, for each alignment data item of the plurality of time spaced-apart alignment data items, to store a corresponding position of the first optical element in timed relation with acquiring image data for the alignment data item.
The measurement controller may be configured, for each alignment data item of the plurality of time spaced-apart alignment data items, to generate a synchronization signal in timed relation with acquisition of the alignment data item. The motion controller may be configured to store a position of the first optical element in response to the synchronization signal.
The alignment processor may be configured to estimate a relationship between: (a) degree of optical alignment between the first optical element and the second optical element and (b) position of the first optical element, based on the plurality of time spaced-apart alignment data items and the plurality of time spaced-apart positions of the first optical element. The alignment processor may be configured to estimate the desired alignment position based on the relationship.
The second optical element may include a digital image sensor. The measurement controller may be configured, for each alignment data item of the plurality of time spaced-apart alignment data items, to acquire image data for a respective image from the digital image sensor and generate the synchronization signal in timed relation with acquiring the image data.
The second optical element may include a digital image sensor configured to generate the synchronization signal.
The motion controller may be configured, for each position of the plurality of time spaced-apart positions of the first optical element, to store a corresponding first acquisition time at which the position was acquired. The system may also include a curve fitter configured to estimate a first relationship between: (a) position of the first optical element and (b) time, based on the plurality of time spaced-apart positions of the first optical element and the respective acquisition time of each position. The alignment processor may be configured to estimate a plurality of positions of the first optical element corresponding to times when respective ones of the time-spaced apart alignment data items were acquired, using times at which the time spaced-apart alignment data items were acquired and the first relationship. The alignment processor may also be configured to estimate a second relationship between: (a) degree of optical alignment between the first optical element and the second optical element and (b) position of the first optical element, based on the plurality of time spaced-apart alignment data items and the plurality of positions of the first optical element. The alignment processor may also be configured to estimate the desired alignment position based on the second relationship.
The system may also include a first clock coupled to the motion controller and a second clock, distinct from the first clock, coupled to the measurement controller. The motion controller may be configured to obtain each first acquisition time from the first clock. The measurement controller may be configured to store a second acquisition time, obtained from the second clock, corresponding to acquisition time of each alignment data item of the plurality of time spaced-apart data items. The system may also include a clock synchronizer coupled to the first clock and to the second clock. The clock synchronizer may be configured to synchronize the first clock with the second clock. Optionally or alternatively, the clock synchronizer may be configured to calculate an offset between the first clock and the second clock and to store the offset.
The first optical element may include a lens, and the second optical element may include an image sensor. A target may be positioned such that the lens projects an image of the target on the image sensor. The data indicative of the degree of optical alignment between the first optical element and the second optical element may include image data acquired from the image sensor.
The alignment processor may be configured, in estimating the second relationship, to analyze the image data to calculate a plurality of focus scores. The degree of optical alignment between the first optical element and the second optical element may be based on the plurality of focus scores.
Yet another embodiment of the present invention provides a computer program product for actively aligning a first optical element to a second optical element. The computer program product includes a non-transitory computer-readable medium. Computer readable program code is stored on the medium. The computer readable program code is configured to cause a robot to continuously scan the first optical element along a trajectory from a starting location to an ending location. While the robot continuously scans the first optical element from the starting location to the ending location, a plurality of time spaced-apart positions of the first optical element are stored. A plurality of time spaced-apart alignment data items is acquired. Each alignment data item of the plurality of time spaced-apart alignment data items results from an optical signal that passed through the first optical element and was received by the second optical element. Each alignment data item contains data indicative of a degree of optical alignment between the first optical element and the second optical element. A desired alignment position is estimated, based at least in part on the plurality of time spaced-apart alignment data items and the plurality of time spaced-apart positions of the first optical element. The robot moves the first optical element to the desired alignment position.
The invention will be more fully understood by referring to the following Detailed Description of Specific Embodiments in conjunction with the Drawings, of which:
FIG. 1 is a perspective schematic illustration of a robotic active alignment system, according to the prior art.
FIG. 2 is an illustration of an alignment target of FIG. 1, according to the prior art.
FIG. 3 is a cross-sectional view of a portion of the system of FIG. 1.
FIG. 4 is a hypothetical graph of center focus score, versus z-axis position of an optical element.
FIG. 5 is a hypothetical graph of center and four corner focus scores, versus z-axis position of an unaligned optical element.
FIG. 6 is a perspective schematic illustration of a target, lens and image sensor, as well as possible rotations of the lens about two axes.
FIG. 7 is a hypothetical graph of center and four corner focus scores, versus z-axis position, similar to the graph of FIG. 6, except for an aligned optical element.
FIG. 8 is a hypothetical graph illustrating positions of an optical element as it is transitioned between adjacent positions in a stepped scan, according to the prior art.
FIG. 9 is a schematic block diagram of an embodiment of the present invention.
FIG. 10 is a hypothetical graph illustrating curve fitting to calculate a relationship between position of a scanned optical element and time, according to an embodiment of the present invention.
FIGS. 11A and 11B contain a schematic flowchart illustrating operations performed by an embodiment of the present invention.
DETAILED DESCRIPTION OF SPECIFIC EMBODIMENTS
In accordance with embodiments of the present invention, methods and apparatus are disclosed for actively aligning a first optical element, such as a lens, to a second optical element, such as an image sensor, using a continuous scan. During a scan, embodiments of the present invention collect timed position information about the scanned optical element, and then estimate a relationship between position of the scanned optical element and time, such as by fitting a curve to a set of position-time pairs. This relationship can then be used to estimate locations of the scanned optical element at times when image data or other alignment quality-indicating data samples are acquired. From this alignment quality versus location data, an optimum alignment position can be determined, and the scanned optical element can then be positioned at the determined alignment position.
Some embodiments utilize a synchronization signal from an image sensor circuit to trigger recording position information about the scanned optical element. In some embodiments, in which the image sensor circuit does not generate a synchronization signal, a synchronization signal is synthesized by an image capture component.
As alluded to above, an established approach to align objects during assembly or test operations involves use of active feedback or measurements that correlate directly to a degree (quality) of alignment between the objects. For example, a lens or other optical object can be optimally aligned to a light emitting diode to produce a highest focus beam by using a beam profiling sensor to detect when beam power density from the diode through the lens is highest. In another example, schematically illustrated in FIG. 1, an automated robot (represented by a gripper 100) is used to optimally align a lens 102 before a digital camera sensor 104 during assembly of the two objects 102 and 104 by evaluating focus sharpness of images taken by the sensor 104 while it is powered up and pointed towards an alignment target 106, while positioning the lens 102 at successive locations along the x, y and z axes and successive orientations about the x, y and z axes, with respect to the sensor 104. Pitch (about the x axis), roll (about the y axis) and yaw rotation about the z axis (the optical axis) are indicated by angles θx, θy and θz, respectively.
FIG. 2 illustrates an exemplary alignment target 200. The target 200 has high-contrast features at its center 202 and corners 204, 206, 208 and 210, as seen by the sensor 104. In the exemplary target shown in FIG. 2, each high-contrast feature includes a slightly rotated black square on a white background and other high contrast elements, such as a checkerboard pattern or line pairs. Thus, the position and orientation of the lens 102, with respect to the sensor 104, that have best image focus quality, as imaged by the sensor 104, will be where the images have highest observed image intensity gradient or contrast across the high contrast variations distributed spatially across the target 200. In other words, as the lens 102 is stepped through its various positions and orientations, when the highest contrast or intensity gradient is detected in the image, the lens 102 is positioned to provide best focus.
A bed of nails, spring-loaded test probes ("pogo pins") or another well-known in-circuit test fixture (not shown) is used to temporarily provide electrical power to the sensor 104 and to electrically connect the image sensor 104 to a computer 108 that controls the robot 100. Through the test fixture, the computer 108 receives image data from the image sensor 104 and evaluates image focus quality or another image attribute or set of attributes of the image. In some cases, separate (but interconnected) computers (not shown) control the robot 100 and receive and evaluate the image data. The computer, or the portion of the computer 108, that receives and evaluates the image data is referred to herein as a "measurement system." The computer, or the portion of the computer 108, that controls the robot 100, optionally including encoders or other devices used by the computer to measure the location of the robot 100, are collectively referred to herein as a "motion control system."
Adhesive (here represented by adhesive dots 110, but alternatively an annular or other deposition of adhesive) is used to bond the lens 102 to the image sensor 104 or its substrate 112, as more clearly shown in FIG. 3, which is a cross-sectional view of the components of FIG. 1. In a typical example, such as a camera module for a mobile device such as a cell phone, the lens-to-sensor distance 114 is nominally about 150 μm, plus or minus about 50 μm. The adhesive is typically applied before the alignment process begins, although additional adhesive can be applied afterward. For adhesive applied before the alignment process begins, sufficient adhesive is applied to accommodate extremes at which the lens 102 may be positioned and oriented, while still providing sufficient mechanical bonding between the lens 102 and the sensor 104 or substrate 112.
Once a position and an orientation that provide the best image focus quality are found, the robot 100 maintains the lens 102 in place while the adhesive at least partially cures. Most adhesives shrink while they cure. Thus, after determining the lens position and orientation that provide the best focus, some embodiments further adjust the lens position and orientation to compensate for expected adhesive shrinkage. Optionally, an ultraviolet beam and/or heat (not shown) may be applied to the adhesive to accelerate the curing.
In these and other alignment examples, finding the best alignment can be made methodical, repeatable and automatable by stepping the lens 102 through a series of discrete positions and orientations, possibly along multiple trajectories. The stepping typically begins with a lens-to-image sensor separation greater than expected to yield a well-focused image and continues to a lens-to-image sensor separation less than expected to yield a well-focused image. For example, for a lens 102 that is expected to produce a well-focused image at about 150 μm, the stepping may begin at a lens-to-image sensor separation of about 200 μm, and each step may involve moving the lens about 10 μm, until the lens 102 is within about 50 μm from the image sensor 104, or perhaps closer. At each step, the lens 102 is briefly held in position and a measurement is taken of optical power, beam density, acquired image sensor focus quality or another attribute directly related to the quality of the alignment. Using conventional equipment, one such sweep takes about 4 seconds to complete. Typically, the lens 102 is made to approach the image sensor 104. However, movement of the lens 102 may be in either direction, i.e., toward or away from the image sensor 104.
Assume the lens 102 is moved progressively along the z axis to each of several positions A, B, C, D, E, F, G and H represented by tick marks 400 in a graph in FIG. 4, and the computer 108 captures an image and calculates a focus score of the center 202 and four corners 204, 206, 208, and 210 of the of the target 106 at each of these positions A-H. The focus scores may be calculated based on a spatial rate of change or gradient across edge transitions from light to dark or dark to light in a region of interest captured by the camera under test.
Hypothetical center focus scores are indicated by points 402. The computer 108 then calculates a polynomial equation that best fits the points 402. Curve 404 represents a plot of a hypothetical best fit polynomial equation for the points 402. Thus, the curve 404 and the equation describe a relationship between beam or image focus quality and lens position. From the polynomial equation, the computer 108 calculates a z-axis location 406 for the lens 102 that should produce the best center focus score 408, i.e., at a peak in the curve 404. The peak 408 may represent a local maximum of the fitted equation. The computer 108 may then cause the robot to position the lens 102 at the determined best location 406 along the z axis and allow the adhesive to cure.
More sophisticated systems may repeat the tests to improve accuracy. For example, each test may determine a location and/or an orientation that provides an improved focus score over the previous test, and each subsequent test may begin with the lens located and/or oriented according to results of the previous test, so as to iteratively find a position and orientation that provide a good focus score.
As noted, optical elements may not be perfectly mounted within the lens 102. For example, the optical elements may be tilted, with respect to their ideal orientations. Furthermore, the sensor 104 may not be perfectly perpendicular to, or centered on, the z axis. Consequently, the position 406 (FIG. 4) of the lens 102 along the z axis that produces the best center focus score 408 many not necessarily produce best focused corners 204, 206, 208 and 210. Thus, as the lens 102 is stepped along the z axis toward the image sensor 104, one of the corners 204, 206, 208 or 210 of the target 200 may come into best focus before (i.e., at a greater z-axis distance from the sensor 104 than) the center 202 of the target 200. Similarly, the other corners 204, 206, 208 and/or 210 may come into best focus at other locations of the lens 102 along the z axis.
As the robot 100 steps the lens 102 through the positions A-H (400, FIG. 4) along the z axis, the computer 108 also analyzes portions of the sensor image data representing the corners 204, 206, 208 and 210 of the target 200 and fits polynomial curves for each of the four corners. FIG. 5 depicts a hypothetical set of curves 500, 502, 504 and 506 representing polynomial equation fits of focus scores for the four corners 204, 206, 208 and 210. In this hypothetical example, the lower-right corner 206, represented by focus score curve 506, is best focused at a smaller z-axis (lens-to-sensor) distance than the center 202 of the target 200 or any of the other three corners 204, 208 or 210. Similarly, the lower-left corner 208, represented by focus score curve 500, is best focused at a larger z-axis lens-to-sensor distance than the center 208 or any of the other three corners 204, 206 or 210. Note that the shapes and heights of the center and of the four corner focus score curves 408, 500, 502, 504 and 506 may not necessarily be identical, due to imperfections, such as asymmetries, in the lens 102.
From the polynomial equations corresponding to the curves 500, 502, 504 and 506, the computer 108 determines pitch and roll angles (θx and θy) for the lens 102 that optimize focus of the corners 204, 206, 208 and 210. A respective distance 508, 510, 512 and 514 between each peak in the corner focus score curves 500, 502, 504 and 506 and the peak of the center focus score curve 404 is proportional to an amount by which the respective portion of the lens 102 is pitched or rolled, relative to ideal, and, therefore, the amount of pitch or roll motion required to compensate for the lens imperfection. The amount of pitch or roll required also depends on the distance 212 between the center 202 of the target 200 and the high-contrast feature 204, 206, 208 or 210 used to calculate the focus score. The further the high-contrast feature 204, 206, 208 or 210 is from the center 202 of the target 200, the more pitch or roll is required to correct for a given displacement 508, 510, 512 or 514 of the peak in the focus score from the peak 408 in the center focus score.
Corner focus score curves (exemplified in this hypothetical case by curves 504 and 506) whose peaks are to the left of the center focus score curve 404 correspond to corners 204 and 206 (in this case upper-right and lower-right corners) that are in best focus when the lens 102 is closer to the image sensor 104 than when the center 202 of the target 200 is in best focus. Therefore, the lens 102 should be pitched an/d or rolled, so as to increase the distances between the lens 102 and the portions of the image sensor 104 that image these corners 204 and 206.
Similarly, corner focus score curves (exemplified by curves 500 and 502) whose peaks are to the right of the center focus score curve 404 correspond to corners 208 and 210 (in this case upper-left and lower-left corners) that are in best focus when the lens 102 is further from the image sensor 104 than when the center 202 of the target 200 is in best focus. Therefore, the lens 102 should be pitched and/or rolled, so as to decrease the distances between the lens 102 and the portions of the image sensor 104 that image these corners 208 and 210.
As shown schematically in FIG. 6 (using a different target 600 for clarity, but maintaining assumptions about lens imperfections made above), rolling the lens 102 about the y axis would simultaneously bring the lens 102 closer to, or further from, the portion of the image sensor 104 that images the upper-right corner P and the lower-right corner Q of the target 600, depending on which way (clockwise or counterclockwise) the lens 102 is rolled about the y axis. Such rolling would also bring the lens 102 further from, or close to, the portion of the image sensor 104 that images the lower-left corner R and the upper-left corner S, but in an opposite sense to that of corners P and Q. Thus, rolling the lens 102 in a negative direction (i.e., opposite the arrow 602) about the y axis moves the focus score curves 504 and 506 to the right, and it moves the focus score curves 500 and 502 to the left.
Similarly, pitching the lens 102 about the x axis would simultaneously bring the lens 102 closer to, or further from, the portion of the image sensor 104 that images the lower-left corner R and the lower-right corner Q and, in an opposite sense, bring the lens 102 further from, or closer to, the portion of the image sensor 104 that images the upper-left corner S and the upper-right corner P, depending on which way (clockwise or counterclockwise) the lens 102 is pitched about the x axis.
Collectively, pitching and rolling the lens 102 as just described brings all the focus score curves 500, 502, 504 and 506 closer together.
As noted, the distances 508, 510, 512 and 514 (FIG. 5) indicate the relative amounts by which the lens 102 should be pitched or rolled to compensate for the mis-focused corners. The greater the distance 212 (FIG. 2) between the center 202 and any corner (ex., 206) of the target 200, the less the lens 102 needs to be tipped or tilted, for a given distance 508-514 between the peak 408 of the center focus score curve and a peak in the corner focus score curve 500-506.
Thus, the pitch and roll of the lens 102 may be adjusted (i.e., two degrees of freedom are available), by which the computer 108 can adjust the lens 102 so that all four corner focus scores peak at the same, or nearly the same, z-axis location, as represented in a hypothetical plot shown in FIG. 7. Plane geometry may be used to calculate the amount by which the lens 102 should be pitched and/or rolled, based on the distances 508-514. Depending on imperfections in the lens, it may not be possible to find a single orientation (i.e., a θx and a θy) that simultaneously maximizes all four corner focus scores. Furthermore, it may not be possible to simultaneously maximize the four corner focus scores and the center focus score. As shown in FIG. 7, the center focus score 404 may peak at z-axis distance 700 from the peak corner focus scores, after the lens 102 orientation has been adjusted.
The computer 108 may, therefore, weight the four corner focus scores and the center focus score to determine a best compromise of positions along, and orientations about, the axes of motion. The weightings (center to corners) may be selected based on needs for a particular camera assembly. In some embodiments, the center focus score to corner focus score weighting ratio may be 50/50, 60/40, 75/25, 100/0 or any other suitable weighting ratio. Using a weighting ratio of 100/0 optimizes for the center focus score, and it makes the four corner focus score curve peaks coincident (or nearly so), although, as shown in FIG. 7, the corner focus curves may peak at a different z-axis location than the center focus score peaks.
The computer 108 (FIG. 1) may iteratively perform the above-described procedure. For example, in a first pass, the computer 108 may determine a pitch and roll of the lens 102 that provides an acceptable balance among the four corner focus scores and between the center focus score and the corner focus scores collectively, as described above. Then, in a second pass, the motion control system may cause the robot 100 to tip and tilt the lens 102 according to results of the first pass and perform the above-described procedure again. Optionally, additional iterative passes may be performed.
Thus far, the movement path (trajectory) of the lens 102 under test has been described as being linear or angular (ex., pitch or roll about an axis). However, other 1-, 2- or more dimensional trajectories may be used. Exemplary trajectories include linear, helical, spiral and box.
Although the above-described procedure can yield an acceptable position and orientation for a lens, the procedure is relatively slow, because the robot must stop at each test position and orientation while an image or other measurement is captured. FIG. 8 is a hypothetical graph of displacement along the z axis plotted against time for a transition between two adjacent test positions Z1 and Z2. After an image has been captured by the computer 108 while the lens 102 in at location Z1, the computer 108 causes the robot 100 to move the lens 102 to location Z2. Being a mechanical system with mass and inertia, the movement involves a period 800 of acceleration to a slew rate, followed by a period 802 of deceleration and settling. If the system is less than critically damped, the lens position may ring (not shown) until it settles sufficiently.
For most effective and efficient active alignment of objects during manufacturing and test applications, it is important to be able to implement alignment as quickly as possible. This allows the number of units that can be assembled and tested in a given time period to be higher. Thus, implementing the most efficient and fastest scans of positions and orientations to find best focus alignment is ideal. Various methods are used to decrease the amount of time required to align objects. These methods include scanning along various trajectories, such as line scans, box scans and spiral scans. By definition, a "scan" is a sequence of positions and/or orientations along a trajectory, where focus quality or another alignment quality metric is measured for each position and/or orientation. The measurements may be performed while the robot is stopped at each position and/or orientation, or image data collected during a scan may be stored in a memory and then analyzed later, such as during the remainder of the scan or after the scan has been completed. Regardless of when the image data is analyzed (i.e., while the robot is in a position where the image data is captured or after the robot has moved beyond that position), we refer to measurements of alignment quality for the positions and/or orientations where the image data was captured. In a "stepped scan," the lens or other object to be aligned is sequentially moved to each position and/or orientation of a set of positions and/or orientations. At each position and/or orientation at which a measurement is to be taken, the motion is stopped, and then the image data is captured.
One method for reducing time required for a scan is to not stop at each measurement position and/or orientation along its trajectory. Instead, the lens or other object is moved continuously (i.e., without stopping) along the trajectory, and image data are captured at each measurement position and/or orientation, while the robot is in motion. This is called a "continuous scan." As long as measurement accuracy is not significantly diminished by taking measurements while moving the lens or other object, a continuous scan can significantly reduce the time taken to execute the alignment scan. For example, much of the acceleration time 800 and the deceleration and settling time 802 may be saved. In some embodiments, a continuous scan can save about 35-50% of the cycle time 804 required to step between successive positions and/or orientations of a stepped scan.
A challenge in implementing a continuous scan is to record the position and/or orientation of the object being aligned at the same time as measurement data is acquired. This is particularly difficult if the instrument or system that performs the data collection or the alignment quality measurements is implemented with a different set of hardware or a different software control system than is used to control the continuous scan motion and record the locus of positions and orientations corresponding of the object.
Some embodiments of the present invention synchronize the measurements taken or information collection with the positions and orientations for each measurement point during a continuous scan using an electrical signal input to the motion control system that correlates to each measurement point. In one such system, which aligns a lens to an image sensor, the image sensor circuit generates a video synchronization signal each time an image is generated. The synchronization signal is fed to the motion control system and, in response to the synchronization signal, the motion control system records the position and/or orientation of the lens when each image is captured.
Video synchronization pulses are typically generated by video image sensors, such as sensors used in backup cameras. However, sensors and related circuitry used in other contexts, such as still digital cameras, typically do not generate video synchronization signals, which makes the above-described alignment process unsuitable for these sensors. Some embodiments of the present invention solve this problem by synthesizing a synchronization signal when an image is captured, as described in more detail below. Other embodiments of the present invention do not require a synchronization signal.
One embodiment of the present invention is shown schematically in FIG. 9. During a continuous scan, at each of several times (preferably, but not necessarily, at regular time intervals), a motion control system 900 records the time and the position and/or orientation of the lens 102 (or the position and/or orientation of the robot 100, from which the position and/or orientation of the lens 102 can be determined). These time-stamped positions and/or orientations are stored in a memory 902. In parallel, a measurement system 904 records image data and the time at which each image data sample is acquired. These time-stamped image data are stored in a memory 906.
The motion control system 900 and the measurement system 904 may use a single (common) clock (not shown). However, if the motion control system 900 and the measurement system 904 utilize separate clocks 908 and 910, prior to these two parallel operations (motion and measurement), the time clocks 908 and 910 are synchronized, or before, during or after the two parallel operations are performed, an offset between the two clocks is determined and stored, by a clock synchronizer 912. Note that the rate or times at which the position and/or orientation data are recorded may be different than the rate or times at which the image data are acquired. Furthermore, the number of position and/or orientation data items recorded may be different than the number of images recorded. These differences may be a result of using separate clocks 908 and 910 and/or they may be a result of a difference in programming of the motion control system 900 and the measurement system 904.
If each image is acquired at the same time as a position and/or orientation is recorded, an alignment processor 916 can perform the calculations and command the motion control system 900, as described above, to align the lens 102. However, in most cases, recording a position and/or an orientation at the same time as each image is acquired in not possible, impractical, inconvenient or undesired. In these cases, after the scan is performed, a curve fitter 914 fits a linear or other equation to the time-stamped position and/or orientation values 902.
FIG. 10 is a graph showing a hypothetical set of time-stamped points 1000, representing positions along the z axis, as recorded by the motion control system 900 at several times, represented by tick marks 1002. FIG. 10 also shows a hypothetical curve 1004 (corresponding to the fitted equation) fitted to the points 1000.
Note that if the motion control system 900 begins recording the position and/or orientation data after the robot reaches a slew rate, and it ceases recording the data before the robot begins decelerating (as represented in FIG. 10), the acceleration 1006 and deceleration 1008 of the robot 100 is not likely to be represented by the curve 1004, and a linear curve is more likely to be fitted to the points 1000 than if the acceleration 1006 and deceleration 1008 data were recorded and used for the curve fitting. To avoid having to fit non-linear equations, it is recommended that the position and/or orientation data and the image data be collected only while the robot 100 is traveling at its slew rate. However, operation outside the slew rate portion of FIG. 10 is possible, with appropriate adjustments to the equation fitting. In particular, a higher-order, non-linear equation should be used.
The start position or orientation of a scan should be selected such that the robot 100 has a chance to accelerate and reach its slew rate before it reaches the first position and/or orientation of interest in any given test. Similarly, the end position or orientation of the scan should be selected such that the robot 100 reaches the last position and/or orientation of interest in the test, before the robot 100 begins to decelerate.
The equation fitted to the points 1000 can then be used to estimate positions and/or orientations that correspond to any time during the scan and, in particular, to the time stamps recorded for the image data 906. For example, assume eight images were recorded during the scan represented in FIG. 10, each image having been recorded at a time A, B, C, D, E, F, G and H (1012) corresponding to a dashed vertical line 1010. The alignment processor 916 uses these times A-H (1012) and the fitted equation to estimate positions and/or orientations 1014 of the lens 102 at the times the images were acquired. The term "estimate" is used here, because the fitted equation and curve 1004 represent an estimate of a relationship (a "motion profile") between time and the position and/or orientation of the lens 102 during a scan. The estimate may be perfect; nevertheless, it is referred to herein as an estimate.
Errors in the estimate may be caused by several factors, including: clock imprecision or rounding, inaccuracies in encoders 918 used to measure the position and/or orientations of the robot 100 and variations in the speed with which the robot 100 moves during the slew portion of the scan. Even if the time stamps assigned to the recorded positions and/or orientations 902 or the time stamps assigned to the recorded image data 906 include inaccuracies, using multiple data points 1000 for the positions and/or orientations, and using multiple data points 402 (FIG. 4) for the image data, acts to average out the effects of these inaccuracies.
As used herein, the term "estimate" includes calculate. One or more calculations may be performed to arrive at an estimate. As used herein, the terms "fitting an equation" and "fitting a curve" may include estimating. Curve fitting is a well-known process of constructing a curve or a mathematical function that has a best fit to a series of data points, possibly subject to constraints. Curve fitting can involve interpolation, where an exact fit to the data is required, or smoothing, in which a "smoothing" function is constructed that approximately fits the data. Curve or equation fitting may involve polynomial equations, possibly including logarithmic or exponential functions.
The alignment processor 916 (FIG. 9) implements the alignment process described above, using the estimated positions and/or orientations of the lens and focus scores it calculates from the image data. For example, the eight times A-H (1012) in FIG. 10 may correspond to the eight tick marks A-H (400) in FIG. 4, which represent the locations along the z axis at which images are captured and focus scores are calculated. The alignment processor 916 sends commands (via connection 920) to the motion control system 900 to drive the test procedure scans (to position and orient the robot 100) and to finally position the lens while the adhesive cures.
In embodiments where the image sensor 104 generates a synchronization signal whenever it captures an image, the synchronization signal may be provided to the motion control system 900, as shown by dashed line 920, and the motion control system 900 may store the position and/or orientation of the lens 102 (or the position and/or orientation of the robot 100, from which the position and/or orientation of the lens 102 can be determined) in response to the synchronization signal.
In some embodiments where the image sensor 104 does not generate synchronization signals, the measurement system 904 may synthesize a synchronization signal whenever the measurement system 904 acquires an image data sample, and this synthesized synchronization signal may be provided to the motion control system 900, as shown by dashed line 922. As described above, the motion control system 900 may store the position and/or orientation of the lens 102 (or the position and/or orientation of the robot 100, from which the position and/or orientation of the lens 102 can be determined) in response to the synthesized synchronization signal.
FIGS. 11A and 11B contain a flowchart illustrating operation of an embodiment of the present invention. At 1100, the target 106 is positioned, so the lens 102 projects an image of the target 106 on the image sensor 104. At 1102, if the motion control system 900 (FIG. 9) and the measurement system 904 utilize separate clocks 908 and 910, the two clocks 908 and 910 are synchronized or an offset between the two clocks is recorded, so times recorded by the motion control system 900 can be correlated to times recorded by the measurement system 904.
At 1104, a continuous scan begins. The robot 100 scans the lens 102 along the z axis or along another axis or along a complex path that involves several axes. While the robot 100 scans the lens 102, at 1106 the motion control system 900 (FIG. 9) acquires data from the encoders 918. The data indicates where the lens (or the robot) is positioned or oriented, along the trajectory. Several measurements ofposition or orientation of the lens 102 are taken as the robot 100 moves the lens 102, thereby yielding a plurality of time spaced-apart positions of the lens 102. (For simplicity of explanation, the term "position" is sometimes used to mean position and/or orientation.)
The time at which each of the positions or orientations is measured is also recorded from a clock, such as the clock 908 (FIG. 9). At 1108, a position measurement is associated with the time at which the measurement was taken. At 1110, the curve fitter 914 automatically fits a first equation to the measured positions of the lens 102, versus the times at which the measurements were taken. The equation represents an estimated relationship between position of the lens and time during the scan.
While the robot 100 (FIG. 1) scans the lens 102 and the motion control system 900 (FIG. 9) acquires the data indicating where the lens (or the robot) is positioned or oriented along the trajectory, at 1112, the measurement system 904 acquires a series of time spaced-apart images (alignment data items) from the image sensor 104. Each image can be analyzed for focus quality or another metric indicating how well the lens 102 is aligned with the image sensor 104. Thus, each image contains data indicative of a degree of optical alignment between the lens 102 and the image sensor 104. The alignment data items should be acquired during a portion of the scan that at least partially overlaps with a portion of the scan during which the lens positions are acquired 1106. However, non-overlapping portions of the scan may be used for acquiring the alignment data items 1112 and the lens positions 1106.
At 1114, the measurement system 904 begins a loop that executes once for each image acquired. Within the loop, at 1116, the measurement system 904 calculates a focus score or other value that indicates a degree of optical alignment of between the lens 102 and the image sensor 104. As noted, this value may be an image intensity gradient, a contrast value across portions of the target 200, a simple intensity or any other suitable value. At 1118, the measurement system 904 uses the times at which the images were acquired and the first equation, which represents the relationship between lens position and time, to calculate the positions of the lens 102 at the times the images were acquired. At 1120, the focus score is associated with its respective lens position. If there are more images, at 1122, the loop returns to 1116, otherwise control passes to 1124.
At 1124, a second equation is fitted to the focus scores, versus the associated lens positions (at times when the images were acquired). This second equation represents an estimated relationship between: (a) a degree of optical alignment of the lens to the sensor (such as the focus score), and (b) position of the lens. The alignment processor 916 then calculates a local maximum of the second equation. This local maximum provides an estimate of a good alignment position for the lens 102. As noted, this alignment position may be modified, such as to compensate for expected shrinkage of adhesive. Nevertheless, the result is referred to herein as the estimated alignment position. The robot then moves the lens 102 to the estimated alignment position.
As noted, at 1130, the operations described above may be iterated to improve accuracy of the estimated alignment position within one degree of freedom, such as along the z axis or rotation about the y axis. At 1132, these operations may be performed for each of the degrees of freedom, if needed. Although the flow chart indicates all operations for a single degree of freedom may be completed at 1130 before any operations are performed at 1132 for another degree of freedom, this need not necessarily be the case. In other words, iterations for a single degree of freedom may be intermixed with alignment procedures for other degrees of freedom.
The times at which the positions and/or orientations of the lens 102 are recorded, or alternatively the time intervals between successive recordations, may be preprogrammed, automatically determined or user-configurable. For example, the motion control system 900 (FIG. 9) may automatically determine an appropriate time interval, based on a desired number of points to fit the equation and the total range of distance or orientation (angle) to be tested and the rate at which the robot 100 moves or rotates. In other words, the time interval may be automatically selected such that the desired number of points are recorded in the time it takes the robot to travel or rotate the total range of distance or orientation, taking into account acceleration and deceleration times. As noted, the time intervals between which the motion control system 900 (FIG. 9) records successive positions and/or orientations of the lens 102 may, but need not, be regular. Similarly, the time intervals between which the measurement system 904 acquires successive images from the image sensor 104 may, but need not, be regular. Thus, as used herein, the term "time spaced-apart" does not necessarily mean at regular time intervals.
Using a continuous scan allows a system to take more image and/or position and/or orientation sample points per unit of time than a stepped scan would permit. These additional points may be used to improve accuracy of the curve fitting described above, without negatively impacting the time taken to perform an individual scan. Optionally or alternatively, the time saving (over a stepped scan) can be used to shorten the overall alignment procedure or to perform one or more additional iterations.
The image sensor 104 may be fabricated according to various technologies, such as charge-coupled device (CCD) or complementary metal-oxide-semiconductor (CMOS). In addition, the image sensor 104 output may conform to various standards, such as VGA, NTSC, PAL, SMIA, MIPI or HiSPI.
As used herein, the term "lens" means an object with one or more conventional optical elements. Although the descriptions above are generally presented in the context of aligning a lens to an image sensor, the methods and apparatus described herein are equally applicable to aligning other optical elements (such as optical fibers) to other passive optical elements (such as other optical fibers) or to other optical sensors (such as photodiodes) or to optical sources (such as light emitting diodes (LEDs) and lasers). Collectively, all such lenses, image sensors, optical fibers, photodiodes, LEDs, lasers and the like are referred to in the claims as "optical elements." Although alignment of one optical element, such as a lens, to another optical element, such as an image sensor, has been described, the methods and apparatus described herein may be used as described, with appropriate modifications, to align more than one optical element, such as several optical fibers, with a single optical element, such as an optical sensor or an optical source. Furthermore, the aligned optical elements may, but need not, all be mounted on a common substrate, such as a printed circuit board, integrated circuit board or integrated circuit substrate.
As used herein and in the claims, a "processor" may be: a single processor; a multi-processor, such as a multi-core processor or multiple processors interconnected with each other on a single or multiple integrated circuit substrate or on a single or multiple circuit boards; a single computer or multiple interconnected computers. Although some claims recite performing one or more operations "by a processor," it should be understood that: each operation may be performed by a distinct processor; all the operations may be performed by a single processor; any combination of the operations may be performed by any combination of plural processors; performance of a single operation may be distributed over a plurality of the processors; and these and other combinations are within the scope of the claims.
As used in the claims, the term "position of an optical element" means at least one of: a position of the optical element and an orientation of the optical element. That is, the term "position" means position and/or orientation. As used herein, the term "automatic" or "automatically" means performed without human intervention, although a human may initiate the performance. For example, automatically fitting an equation to a set of data requires a processor to determine parameters of the equation, without assistance from a human.
While the invention is described through the above-described exemplary embodiments, modifications to, and variations of, the illustrated embodiments may be made without departing from the inventive concepts disclosed herein. Furthermore, disclosed aspects, or portions of these aspects, may be combined in ways not listed above and/or not explicitly claimed. Accordingly, the invention should not be viewed as being limited to the disclosed embodiments.
The motion control system 900, data store 902, measurement system 904, data store 906, curve fitter 914, alignment processor 916, clocks 908 and 910, clock synchronizer 912 and other components and processes described herein can be implemented with software, hardware or a combination thereof These functions can be performed by a processor executing instructions stored in a memory.
Although aspects of embodiments may have been described with reference to flowcharts and/or block diagrams, functions, operations, decisions, etc. of all or a portion of each block, or a combination of blocks, may be combined, separated into separate operations or performed in other orders. All or a portion of each block, or a combination of blocks, may be implemented as computer program instructions (such as software), hardware (such as combinatorial logic, Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs) or other hardware), firmware or combinations thereof Embodiments may be implemented by a processor executing, or controlled by, instructions stored in a memory. The memory may be random access memory (RAM), read-only memory (ROM), flash memory or any other memory, or combination thereof, suitable for storing control software or other instructions and data. Instructions defining the functions of the present invention may be delivered to a processor in many forms, including, but not limited to, information permanently stored on non-transitory tangible non-writable storage media (e.g., read-only memory devices within a computer, such as ROM, or devices readable by a computer I/O attachment, such as CD-ROM or DVD disks), information alterably stored on non-transitory tangible writable storage media (e.g., floppy disks, removable flash memory and hard drives) or information conveyed to a computer through a communication medium, including wired or wireless computer networks. Moreover, while embodiments may be described in connection with various illustrative data structures, the system may be embodied using a variety of data structures.
1. A computer-implemented method for actively aligning a first optical element to a second optical element, the method comprising performing, by a processor, operations of
causing a robot to continuously scan the first optical element along a trajectory from a starting location to an ending location;
while the robot continuously scans the first optical element from the starting location to the ending location:
storing a plurality of time spaced-apart positions of the first optical element; and
acquiring a plurality of time spaced-apart alignment data items, wherein each alignment data item of the plurality of time spaced-apart alignment data items:
results from an optical signal that passed through the first optical element and was received by the second optical element; and
contains data indicative of a degree of optical alignment between the first optical element and the second optical element;
estimating a desired alignment position, based at least in part on the plurality of time spaced-apart alignment data items and the plurality of time spaced-apart positions of the first optical element; and
causing the robot to move the first optical element to the desired alignment position.
2. A method according to claim 1, wherein storing the plurality of time spaced-apart positions of the first optical element comprises, for each alignment data item of the plurality of time spaced-apart alignment data items, storing a corresponding position of the first optical element in timed relation with acquiring image data for the alignment data item.
3. A method according to claim 1, further comprising:
for each alignment data item of the plurality of time spaced-apart alignment data items, generating a synchronization signal in timed relation with acquisition of the alignment data item;
wherein storing the plurality of time spaced-apart positions of the first optical element comprises, for each position of the plurality of time spaced-apart positions, storing a position of the first optical element in response to the synchronization signal.
estimating a relationship between (a) degree of optical alignment between the first optical element and the second optical element and (b) position of the first optical element, based on the plurality of time spaced-apart alignment data items and the plurality of time spaced-apart positions of the first optical element; wherein:
estimating the desired alignment position comprises estimating the desired alignment position based on the relationship.
5. A method according to claim 3, wherein:
the second optical element comprises a digital image sensor; and
acquiring the plurality of time spaced-apart alignment data items comprises, for each alignment data item of the plurality of time spaced-apart alignment data items, acquiring image data for a respective image from the digital image sensor and generating the synchronization signal in timed relation with acquiring the image data.
6. A method according to claim 5, wherein generating the synchronization signal comprises generating the synchronization signal by the digital image sensor.
for each position of the plurality of time spaced-apart positions of the first optical element, storing a corresponding acquisition time at which the position was acquired;
estimating a first relationship between (a) position of the first optical element and (b) time, based on the plurality of time spaced-apart positions of the first optical element and the respective acquisition time of each position;
estimating a plurality of positions of the first optical element corresponding to times when respective ones of the time-spaced apart alignment data items were acquired, using times at which the time spaced-apart alignment data items were acquired and the first relationship;
estimating a second relationship between (a) degree of optical alignment between the first optical element and the second optical element and (b) position of the first optical element, based on the plurality of time spaced-apart alignment data items and the plurality of positions of the first optical element;
wherein estimating the desired alignment position comprises estimating the desired alignment position based on the second relationship.
storing a corresponding acquisition time comprises accessing a first clock; and
acquiring the plurality of time spaced-apart alignment data items comprises, for each alignment data item of the plurality of time spaced-apart alignment data items, accessing a second clock, distinct from the first clock; and further comprising:
synchronizing the first clock with the second clock.
calculating an offset between the first clock and the second clock; and
storing the offset.
10. A method according to claim 7, wherein the first optical element comprises a lens and the second optical element comprises an image sensor, the method further comprising:
positioning a target, such that the lens projects an image of the target on the image sensor;
wherein the data indicative of the degree of optical alignment between the first optical element and the second optical element comprises image data acquired from the image sensor.
11. A method according to claim 10, wherein estimating the second relationship comprises:
analyzing the image data to calculate a plurality of focus scores; and
basing the degree of optical alignment between the first optical element and the second optical element on the plurality of focus scores.
12. A system for actively aligning a first optical element to a second optical element, the system comprising:
a robot configured to grasp the first optical element;
a motion controller configured to:
cause the robot to continuously scan the first optical element along a trajectory from a starting location to an ending location; and
while the robot continuously scans the first optical element from the starting location to the ending location, store a plurality of time spaced-apart positions of the first optical element;
a measurement controller configured, while the robot continuously scans the first optical element from the starting location to the ending location, to:
acquire a plurality of time spaced-apart alignment data items, wherein each alignment data item of the plurality of time spaced-apart alignment data items:
contains data indicative of a degree of optical alignment between the first optical element and the second optical element; and
an alignment processor configured to:
estimate a desired alignment position, based at least in part on the plurality of time spaced-apart alignment data items and the plurality of time spaced-apart positions of the first optical element; and
cause the robot to move the first optical element to the desired alignment position.
13. A system according to claim 12, wherein the motion controller is configured, for each alignment data item of the plurality of time spaced-apart alignment data items, to store a corresponding position of the first optical element in timed relation with acquiring image data for the alignment data item.
14. A system according to claim 12, wherein:
the measurement controller is configured, for each alignment data item of the plurality of time spaced-apart alignment data items, to generate a synchronization signal in timed relation with acquisition of the alignment data item; and
the motion controller is configured to store a position of the first optical element in response to the synchronization signal.
15. A system according to claim 14, wherein the alignment processor is configured to:
estimate a relationship between (a) degree of optical alignment between the first optical element and the second optical element and (b) position of the first optical element, based on the plurality of time spaced-apart alignment data items and the plurality of time spaced-apart positions of the first optical element; and
estimate the desired alignment position based on the relationship.
the measurement controller is configured, for each alignment data item of the plurality of time spaced-apart alignment data items, to acquire image data for a respective image from the digital image sensor and generate the synchronization signal in timed relation with acquiring the image data.
17. A system according to claim 14, wherein the second optical element comprises a digital image sensor configured to generate the synchronization signal.
the motion controller is configured, for each position of the plurality of time spaced-apart positions of the first optical element, to store a corresponding first acquisition time at which the position was acquired;
a curve fitter configured to estimate a first relationship between (a) position of the first optical element and (b) time, based on the plurality of time spaced-apart positions of the first optical element and the respective acquisition time of each position;
the alignment processor is configured to:
estimate a plurality of positions of the first optical element corresponding to times when respective ones of the time-spaced apart alignment data items were acquired, using times at which the time spaced-apart alignment data items were acquired and the first relationship;
estimate a second relationship between (a) degree of optical alignment between the first optical element and the second optical element and (b) position of the first optical element, based on the plurality of time spaced-apart alignment data items and the plurality of positions of the first optical element; and
estimate the desired alignment position based on the second relationship.
19. A system according to claim 18, further comprising:
a first clock coupled to the motion controller; and
a second clock, distinct from the first clock, coupled to the measurement controller;
wherein:
the motion controller is configured to obtain each first acquisition time from the first clock; and
the measurement controller is configured to store a second acquisition time, obtained from the second clock, corresponding to acquisition time of each alignment data item of the plurality of time spaced-apart data items; and further comprising:
a clock synchronizer coupled to the first clock and to the second clock and configured to synchronize the first clock with the second clock.
a clock synchronizer coupled to the first clock and to the second clock and configured to calculate an offset between the first clock and the second clock and to store the offset.
the first optical element comprises a lens;
the second optical element comprises an image sensor; and further comprising:
a target positioned such that the lens projects an image of the target on the image sensor; and
the data indicative of the degree of optical alignment between the first optical element and the second optical element comprises image data acquired from the image sensor.
22. A system according to claim 21, wherein the alignment processor is configured, in estimating the second relationship, to:
analyze the image data to calculate a plurality of focus scores; and
base the degree of optical alignment between the first optical element and the second optical element on the plurality of focus scores.
23. A computer program product for actively aligning a first optical element to a second optical element, the computer program product comprising a non-transitory computer-readable medium having computer readable program code stored thereon, the computer readable program code configured to:
cause a robot to continuously scan the first optical element along a trajectory from a starting location to an ending location;
store a plurality of time spaced-apart positions of the first optical element; and
US13/861,844 2012-04-13 2013-04-12 Active alignment using continuous motion sweeps and temporal interpolation Active 2033-10-20 US9156168B2 (en)
US13/861,844 US9156168B2 (en) 2012-04-13 2013-04-12 Active alignment using continuous motion sweeps and temporal interpolation
US13/861,844 Active 2033-10-20 US9156168B2 (en) 2012-04-13 2013-04-12 Active alignment using continuous motion sweeps and temporal interpolation
EP (1) EP2836869A1 (en)
CN (1) CN104350408B (en)
US20150062422A1 (en) * 2013-08-27 2015-03-05 Semiconductor Components Industries, Llc Lens alignment in camera modules using phase detection pixels
WO2015070105A1 (en) * 2013-11-07 2015-05-14 Pelican Imaging Corporation Methods of manufacturing array camera modules incorporating independently aligned lens stacks
US9124815B2 (en) 2008-05-20 2015-09-01 Pelican Imaging Corporation Capturing and processing of images including occlusions captured by arrays of luma and chroma cameras
US9123118B2 (en) 2012-08-21 2015-09-01 Pelican Imaging Corporation System and methods for measuring depth using an array camera employing a bayer filter
US9143711B2 (en) 2012-11-13 2015-09-22 Pelican Imaging Corporation Systems and methods for array camera focal plane control
US9210392B2 (en) 2012-05-01 2015-12-08 Pelican Imaging Coporation Camera modules patterned with pi filter groups
US9214013B2 (en) 2012-09-14 2015-12-15 Pelican Imaging Corporation Systems and methods for correcting user identified artifacts in light field images
US9253380B2 (en) 2013-02-24 2016-02-02 Pelican Imaging Corporation Thin form factor computational array cameras and modular array cameras
US9412206B2 (en) 2012-02-21 2016-08-09 Pelican Imaging Corporation Systems and methods for the manipulation of captured light field image data
US9426361B2 (en) 2013-11-26 2016-08-23 Pelican Imaging Corporation Array camera configurations incorporating multiple constituent array cameras
US9485496B2 (en) 2008-05-20 2016-11-01 Pelican Imaging Corporation Systems and methods for measuring depth using images captured by a camera array including cameras surrounding a central camera
US9497370B2 (en) 2013-03-15 2016-11-15 Pelican Imaging Corporation Array camera architecture implementing quantum dot color filters
US9497429B2 (en) 2013-03-15 2016-11-15 Pelican Imaging Corporation Extended color processing on pelican array cameras
US9516222B2 (en) 2011-06-28 2016-12-06 Kip Peli P1 Lp Array cameras incorporating monolithic array camera modules with high MTF lens stacks for capture of images used in super-resolution processing
US9521319B2 (en) 2014-06-18 2016-12-13 Pelican Imaging Corporation Array cameras and array camera modules including spectral filters disposed outside of a constituent image sensor
US9536166B2 (en) 2011-09-28 2017-01-03 Kip Peli P1 Lp Systems and methods for decoding image files containing depth maps stored as metadata
US9578259B2 (en) 2013-03-14 2017-02-21 Fotonation Cayman Limited Systems and methods for reducing motion blur in images or video in ultra low light with array cameras
US9638883B1 (en) 2013-03-04 2017-05-02 Fotonation Cayman Limited Passive alignment of array camera modules constructed from lens stack arrays and sensors based upon alignment information obtained during manufacture of array camera modules using an active alignment process
US9733486B2 (en) 2013-03-13 2017-08-15 Fotonation Cayman Limited Systems and methods for controlling aliasing in images captured by an array camera for use in super-resolution processing
US9741118B2 (en) 2013-03-13 2017-08-22 Fotonation Cayman Limited System and methods for calibration of an array camera
US9766473B1 (en) * 2014-02-03 2017-09-19 Automation Engineering, Inc. Automated UV calibration, motorized optical target and automatic surface finder for optical alignment and assembly robot
US9766380B2 (en) 2012-06-30 2017-09-19 Fotonation Cayman Limited Systems and methods for manufacturing camera modules using active alignment of lens stack arrays and sensors
US9774789B2 (en) 2013-03-08 2017-09-26 Fotonation Cayman Limited Systems and methods for high dynamic range imaging using array cameras
US9794476B2 (en) 2011-09-19 2017-10-17 Fotonation Cayman Limited Systems and methods for controlling aliasing in images captured by an array camera for use in super resolution processing using pixel apertures
US9800859B2 (en) 2013-03-15 2017-10-24 Fotonation Cayman Limited Systems and methods for estimating depth using stereo array cameras
US9800856B2 (en) 2013-03-13 2017-10-24 Fotonation Cayman Limited Systems and methods for synthesizing images from image data captured by an array camera using restricted depth of field depth maps in which depth estimation precision varies
US9807382B2 (en) 2012-06-28 2017-10-31 Fotonation Cayman Limited Systems and methods for detecting defective camera arrays and optic arrays
US9813616B2 (en) 2012-08-23 2017-11-07 Fotonation Cayman Limited Feature based high resolution motion estimation from low resolution images captured using an array source
US9866739B2 (en) 2011-05-11 2018-01-09 Fotonation Cayman Limited Systems and methods for transmitting and receiving array camera image data
US9888194B2 (en) 2013-03-13 2018-02-06 Fotonation Cayman Limited Array camera architecture implementing quantum film image sensors
US9898856B2 (en) 2013-09-27 2018-02-20 Fotonation Cayman Limited Systems and methods for depth-assisted perspective distortion correction
US9936148B2 (en) 2010-05-12 2018-04-03 Fotonation Cayman Limited Imager array interfaces
US9933177B2 (en) 2014-11-04 2018-04-03 Google Llc Enhanced automated environmental control system scheduling using a preference function
US9942474B2 (en) 2015-04-17 2018-04-10 Fotonation Cayman Limited Systems and methods for performing high speed video capture and depth estimation using array cameras
US9955070B2 (en) 2013-03-15 2018-04-24 Fotonation Cayman Limited Systems and methods for synthesizing high resolution images using image deconvolution based on motion and depth information
US10009538B2 (en) 2013-02-21 2018-06-26 Fotonation Cayman Limited Systems and methods for generating compressed light field representation data using captured light fields, array geometry, and parallax information
US10089740B2 (en) 2014-03-07 2018-10-02 Fotonation Limited System and methods for depth regularization and semiautomatic interactive matting using RGB-D images
US10119808B2 (en) 2013-11-18 2018-11-06 Fotonation Limited Systems and methods for estimating depth from projected texture using camera arrays
US10122993B2 (en) 2013-03-15 2018-11-06 Fotonation Limited Autofocus system for a conventional camera that uses depth information from an array camera
EP3445050A1 (en) * 2017-08-14 2019-02-20 Aptiv Technologies Limited Camera assembly method with adhesive shrink offset based on individual lens characteristic
US10250871B2 (en) 2014-09-29 2019-04-02 Fotonation Limited Systems and methods for dynamic calibration of array cameras
US10306120B2 (en) 2009-11-20 2019-05-28 Fotonation Limited Capturing and processing of images captured by camera arrays incorporating cameras with telephoto and conventional lenses to generate depth maps
US9442293B2 (en) 2014-05-06 2016-09-13 Microsoft Technology Licensing, Llc Composite variable light attenuator
EP3068125A1 (en) 2015-03-09 2016-09-14 Delphi Technologies, Inc. A method of manufacturing a multiple view camera system and multiple view camera system
CN106717506B (en) * 2016-12-18 2018-12-21 山东金瓢食品机械股份有限公司 One main laminaria automatic harvester device people
US5926594A (en) 1994-08-31 1999-07-20 Litton Systems, Inc. System and method for aligning and attaching optical fibers to optical waveguides, and products obtained thereby
US6621521B1 (en) * 1996-07-26 2003-09-16 Fuji Photo Film Co., Ltd. Automatic focusing device for film scanner
US6828542B2 (en) * 2002-06-07 2004-12-07 Brion Technologies, Inc. System and method for lithography process monitoring and control
US7330211B2 (en) 2003-07-08 2008-02-12 Micron Technology, Inc. Camera module with focus adjustment structure and systems and methods of making the same
JP2005157268A (en) * 2003-11-06 2005-06-16 Canon Inc Image pickup device, control method therefor, program, and storage medium
US7598996B2 (en) * 2004-11-16 2009-10-06 Aptina Imaging Corporation System and method for focusing a digital camera
JP2007086596A (en) * 2005-09-26 2007-04-05 Pentax Corp camera
JP2008009342A (en) * 2006-06-30 2008-01-17 Sony Corp Autofocus device and method, and imaging apparatus
US8063975B2 (en) 2008-10-29 2011-11-22 Jabil Circuit, Inc. Positioning wafer lenses on electronic imagers
CN102449524B (en) 2009-03-25 2015-03-11 马格纳电子系统公司 Vehicular camera and lens assembly
US9009952B2 (en) 2011-08-29 2015-04-21 Asm Technology Singapore Pte. Ltd. Apparatus for assembling a lens module and an image sensor to form a camera module, and a method of assembling the same
2013-04-12 EP EP13719662.2A patent/EP2836869A1/en active Pending
2013-04-12 CN CN201380026472.8A patent/CN104350408B/en active IP Right Grant
US9576369B2 (en) 2008-05-20 2017-02-21 Fotonation Cayman Limited Systems and methods for generating depth maps using images captured by camera arrays incorporating cameras having different fields of view
US9188765B2 (en) 2008-05-20 2015-11-17 Pelican Imaging Corporation Capturing and processing of images including occlusions focused on an image sensor by a lens stack array
US10142560B2 (en) 2008-05-20 2018-11-27 Fotonation Limited Capturing and processing of images including occlusions focused on an image sensor by a lens stack array
US10027901B2 (en) 2008-05-20 2018-07-17 Fotonation Cayman Limited Systems and methods for generating depth maps using a camera arrays incorporating monochrome and color cameras
US9749547B2 (en) 2008-05-20 2017-08-29 Fotonation Cayman Limited Capturing and processing of images using camera array incorperating Bayer cameras having different fields of view
US9191580B2 (en) 2008-05-20 2015-11-17 Pelican Imaging Corporation Capturing and processing of images including occlusions captured by camera arrays
US9712759B2 (en) 2008-05-20 2017-07-18 Fotonation Cayman Limited Systems and methods for generating depth maps using a camera arrays incorporating monochrome and color cameras
US10218889B2 (en) 2011-05-11 2019-02-26 Fotonation Limited Systems and methods for transmitting and receiving array camera image data
US9578237B2 (en) 2011-06-28 2017-02-21 Fotonation Cayman Limited Array cameras incorporating optics with modulation transfer functions greater than sensor Nyquist frequency for capture of images used in super-resolution processing
US9864921B2 (en) 2011-09-28 2018-01-09 Fotonation Cayman Limited Systems and methods for encoding image files containing depth maps stored as metadata
US10019816B2 (en) 2011-09-28 2018-07-10 Fotonation Cayman Limited Systems and methods for decoding image files containing depth maps stored as metadata
US10275676B2 (en) 2011-09-28 2019-04-30 Fotonation Limited Systems and methods for encoding image files containing depth maps stored as metadata
US20180197035A1 (en) 2011-09-28 2018-07-12 Fotonation Cayman Limited Systems and Methods for Encoding Image Files Containing Depth Maps Stored as Metadata
US9811753B2 (en) 2011-09-28 2017-11-07 Fotonation Cayman Limited Systems and methods for encoding light field image files
US10311649B2 (en) 2012-02-21 2019-06-04 Fotonation Limited Systems and method for performing depth based image editing
US9754422B2 (en) 2012-02-21 2017-09-05 Fotonation Cayman Limited Systems and method for performing depth based image editing
US9706132B2 (en) 2012-05-01 2017-07-11 Fotonation Cayman Limited Camera modules patterned with pi filter groups
US10334241B2 (en) 2012-06-28 2019-06-25 Fotonation Limited Systems and methods for detecting defective camera arrays and optic arrays
US10261219B2 (en) 2012-06-30 2019-04-16 Fotonation Limited Systems and methods for manufacturing camera modules using active alignment of lens stack arrays and sensors
US9240049B2 (en) 2012-08-21 2016-01-19 Pelican Imaging Corporation Systems and methods for measuring depth using an array of independently controllable cameras
US9858673B2 (en) 2012-08-21 2018-01-02 Fotonation Cayman Limited Systems and methods for estimating depth and visibility from a reference viewpoint for pixels in a set of images captured from different viewpoints
US9123117B2 (en) 2012-08-21 2015-09-01 Pelican Imaging Corporation Systems and methods for generating depth maps and corresponding confidence maps indicating depth estimation reliability
US9147254B2 (en) 2012-08-21 2015-09-29 Pelican Imaging Corporation Systems and methods for measuring depth in the presence of occlusions using a subset of images
US9235900B2 (en) 2012-08-21 2016-01-12 Pelican Imaging Corporation Systems and methods for estimating depth and visibility from a reference viewpoint for pixels in a set of images captured from different viewpoints
US9129377B2 (en) 2012-08-21 2015-09-08 Pelican Imaging Corporation Systems and methods for measuring depth based upon occlusion patterns in images
US9749568B2 (en) 2012-11-13 2017-08-29 Fotonation Cayman Limited Systems and methods for array camera focal plane control
US9743051B2 (en) 2013-02-24 2017-08-22 Fotonation Cayman Limited Thin form factor computational array cameras and modular array cameras
US9917998B2 (en) 2013-03-08 2018-03-13 Fotonation Cayman Limited Systems and methods for measuring scene information while capturing images using array cameras
US10225543B2 (en) 2013-03-10 2019-03-05 Fotonation Limited System and methods for calibration of an array camera
US10091405B2 (en) 2013-03-14 2018-10-02 Fotonation Cayman Limited Systems and methods for reducing motion blur in images or video in ultra low light with array cameras
US10182216B2 (en) 2013-03-15 2019-01-15 Fotonation Limited Extended color processing on pelican array cameras
US9185276B2 (en) 2013-11-07 2015-11-10 Pelican Imaging Corporation Methods of manufacturing array camera modules incorporating independently aligned lens stacks
US9264592B2 (en) 2013-11-07 2016-02-16 Pelican Imaging Corporation Array camera modules incorporating independently aligned lens stacks
US9924092B2 (en) 2013-11-07 2018-03-20 Fotonation Cayman Limited Array cameras incorporating independently aligned lens stacks
US9813617B2 (en) 2013-11-26 2017-11-07 Fotonation Cayman Limited Array camera configurations incorporating constituent array cameras and constituent cameras
US10095046B2 (en) 2014-02-03 2018-10-09 Automation Engineering, Inc. Automated UV calibration, motorized optical target and automatic surface finder for optical alignment and assembly robot
Prescott et al. 1997 Line-based correction of radial lens distortion
US8346392B2 (en) 2013-01-01 Method and system for the high-precision positioning of at least one object in a final location in space
JP5377758B2 (en) 2013-12-25 Method and system for positioning at high accuracy at least one object in the final position in the space
US20130176432A1 (en) 2013-07-11 Automatic calibration of ptz camera system
EP2081391A2 (en) 2009-07-22 Method for adjusting position of image sensor, method and apparatus for manufacturing a camera module, and camera module
US8405820B2 (en) 2013-03-26 Ranging device and ranging module and image-capturing device using the ranging device or the ranging module
US9009952B2 (en) 2015-04-21 Apparatus for assembling a lens module and an image sensor to form a camera module, and a method of assembling the same
US8929642B2 (en) 2015-01-06 Three-dimensional scanner and robot system
WO2014160142A1 (en) 2014-10-02 Systems and methods for using alignment to increase sampling diversity of cameras in an array camera module
JP2008012604A (en) 2008-01-24 Measuring apparatus and method of its calibration
CN103018015B (en) 2016-01-20 The method and apparatus of the optical axis of the lens displacement detection apparatus
JP2016001181A (en) 2016-01-07 System and method for runtime determination of camera mis-calibration
JP2008188705A (en) 2008-08-21 Calibration device and method for robot mechanism
CN104236463B (en) 2018-12-07 Machine vision inspection system and high-speed focusing operation method of measuring the height
US7656425B2 (en) 2010-02-02 Robust field of view distortion calibration
US9279661B2 (en) 2016-03-08 Information processing apparatus and information processing method
US8339463B2 (en) 2012-12-25 Camera lens calibration system
US8619144B1 (en) 2013-12-31 Automatic camera calibration
US10112301B2 (en) 2018-10-30 Automatic calibration method for robot systems using a vision sensor
US8204298B2 (en) 2012-06-19 Focusing method and apparatus
US20120098961A1 (en) 2012-04-26 Shape measuring apparatus, robot system, and shape measuring method
US20140121836A1 (en) 2014-05-01 Object pickup device and method for picking up object
US6304680B1 (en) 2001-10-16 High resolution, high accuracy process monitoring system
US20120143370A1 (en) 2012-06-07 Robot positioning method and calibration method
US8711275B2 (en) 2014-04-29 Estimating optical characteristics of a camera component using sharpness sweep data
Owner name: AUTOMATION ENGINEERING, INC., MASSACHUSETTS
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:BY, ANDRE;REEL/FRAME:030222/0292
Owner name: MASSACHUSETTS GROWTH CAPITAL CORPORATION, MASSACHU
Free format text: SECURITY AGREEMENT;ASSIGNOR:AUTOMATION ENGINEERING, INC.;REEL/FRAME:031422/0131
Free format text: CORRECTIVE ASSIGNMENT TO CORRECT THE 13861884 PREVIOUSLY RECORDED ON REEL 031422 FRAME 0131. ASSIGNOR(S) HEREBY CONFIRMS THE SECURITY AGREEMENT;ASSIGNOR:AUTOMATION ENGINEERING, INC.;REEL/FRAME:031447/0803
Free format text: RELEASE BY SECURED PARTY;ASSIGNOR:AUTOMATION ENGINEERING, INC.;REEL/FRAME:031791/0180
Free format text: ENTITY STATUS SET TO UNDISCOUNTED (ORIGINAL EVENT CODE: BIG.)
Free format text: PAYMENT OF MAINTENANCE FEE, 4TH YEAR, LARGE ENTITY (ORIGINAL EVENT CODE: M1551); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY