The ultimate goal of a robotics system is of course to perform some useful function in place of its human counterpart. Benefits typically associated with the installation of fixed-location industrial robots are improved effectiveness, higher quality, reductions in manpower, greater efficiency, reliability and cost savings. Additional benefits include the ability to perform tasks for which humans are incapable and the removal of humans from dangerous or life-threatening scenarios. The concept of mobility has always suggested an additional range of applications beyond that of the typical factory floor, wherein free-roaming robots moved about with an added versatility that brought even greater returns. In practice, however, the realization of this dream has been slow in coming.
One of the most significant technological hurdles impeding the widespread introduction of mobile robotics systems arises from the need for a mobile platform to successfully interact with the physical objects and entities in its environment. The robot must be able to navigate from a known position to a desired new location and orientation, at the same time avoiding any contact with fixed or moving objects while enroute. A robust navigational scheme that preserves the validity of a world model for free-roaming platforms has remained an elusive research goal, and for this reason many proposed applications of autonomous mobile robots are yet to be implemented.
The simplest form of autonomous control is sometimes termed guidepath control and involves a navigational control loop which reacts (in a reflexive manner) to the sensed position of some external guiding reference. The intent is to free a human operator from the requirement of steering the moving platform. For example, encoded reflective stripes might be applied to the floor of the robot's environment. The robot would then be equipped with stripe detecting/decoding for determining the robot's position in its environment as provided on the encoded stripes. Such automated guided vehicles (AGVs) have found extensive use in factories and warehouses for material transfer, in modern office scenarios for material and mail pickup and delivery, and in hospitals for delivery of meals and supplies to nursing stations, to name but a few.
Advantages of guidepath control are seen primarily in the improved efficiency and reduction of manpower since an operator is no longer required to guide the vehicle. Large numbers of AGVs can operate simultaneously in a plant or warehouse without getting lost or disoriented. The AGVs are typically scheduled and controlled by a central computer which monitors overall system operation and vehicle flow. Communication with individual vehicles can be via RF links or directional near-infrared modulated light beams, or other means. However, the fundamental disadvantage of guidepath control is the lack of flexibility in the system. A vehicle cannot be commanded to go to a new location unless the guidepath is first modified. This is a significant drawback in the event of changes to product flow lines in assembly plants, or in the case of a security robot which must investigate a potential break-in at a designated remote location.
Thus, truly autonomous control implies the ability of a mobile platform to travel anywhere so desired, subject to nominal considerations of terrain. Many potential applications await an indoor robot that could move in a purposeful fashion from room to room without following a set guidepath, with the intelligence to avoid objects and, if necessary, choose alternative routes of its own planning. To do this, specialized sensors must be coupled with some type of "world modeling" capability that represents the relative/absolute locations of objects detected by these sensors. In this way, a mobile platform can be provided with sufficient awareness of its surroundings to allow it to move about in a realistic fashion, i.e., a path not forever dictated by a guidepath stripe.
The accuracy of this model, which is constructed and refined in a continuous fashion as the robot moves about its workspace, is directly dependent throughout this process upon the validity of the robot's perceived location and orientation. Accumulated dead-reckoning errors can quickly render the information entered into the model invalid in that the associated geographical reference point for data acquired relative to the robot's position is incorrect. As the accuracy of the model degrades, the ability of the robot to successfully navigate and avoid collisions diminishes rapidly, until it fails altogether. One solution to this problem is to provide navigation landmarks within the robot's environment for use by the robot in periodic (absolute) positional updates. The concept of using existing interior doorways as navigation landmarks for a mobile robotics system has always been appealing, in that no modifications to the surrounding environment are required. The robot by necessity must travel through a doorway to enter an adjoining space. If in so doing the system could obtain an accurate positional update, then such would indeed represent an elegant solution to the problem of cumulative dead-reckoning errors.
Thus, the need exists for a navigational referencing system for a mobile robot that can derive its own updated positional information as it moves through its environment. Accordingly, an object of the present invention is to provide a navigational referencing method and system for a mobile robot that derives x-y position and angular orientation of the robot within a world model of the robot's environment as the robot traverses doorway openings. Another object of the present invention is to provide a navigational referencing method and system for a mobile robot that derives a relative x-y position and angular orientation of the robot without any modifications to the robot's environment. Yet another object of the present invention is to provide a method and system of navigational referencing for a mobile robot that provides for sufficient updates to the x-y position and angular orientation of the robot within a world model of the robot's environment thereby avoiding the accumulated effect of navigational dead-reckoning errors.