This paper presents a versatile robotic system for sewing 3D structured object. Leveraging on using a customized robotic sewing device and closed-loop visual servoing control, an all-in-one solution for sewing personalized stent graft is demonstrated. Stitch size planning and automatic knot tying are proposed as the two key functions of the system. By using effective stitch size planning, sub-millimetre sewing accuracy is achieved for stitch sizes ranging from 2mm to 5mm. In addition, a thread manipulator for thread management and tension control is also proposed to perform successive knot tying to secure each stitch. Detailed laboratory experiments have been performed to access the proposed instruments and allied algorithms. The proposed framework can be generalised to a wide range of applications including 3D industrial sewing, as well as transferred to other clinical areas such as surgical suturing.
Extensive research on automated sewing has been performed in the apparel industry focusing on incorporating sensors and robots to augment the ability of conventional sewing machines. Relevant topics include fabric tension control for robot-assisted fabric feeding @cite_3 , sewing seam tracking using an optical sensor @cite_6 or a camera system @cite_12 , multi-arm robotic sewing @cite_22 , and automatic sewing worklines @cite_9 . These systems, however, constrained by the incorporation of conventional sewing machines, work only on a flat sewing table. Recently, innovation in 3D structured object sewing is an important topic for industrial manufacturing. KSL Keilmann (Lorsch, Germany) has developed different single-sided sewing heads, such as KSL double needle RS 530, for sewing 3D fabric-reinforced structures for aircraft parts. Different to a conventional sewing machine, which applies stitches by using synchronized parts working on both side of the fabric, the single-sided sewing head features two needles, which are able to apply interwoven chain stitches from the outer surface of a 3D object. These single-sided sewing heads, however, are designed to sew large and heavy objects.
@cite_22 @cite_9 @cite_6 @cite_3 @cite_12
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In this paper a concept for automated multi-robot-aided sewing is presented. The objective of the work is to demonstrate automatic sewing of 3D-shaped covers for recliners, by assembling two different hide parts with different shapes, using two robots to align the parts during sewing. The system consists of an industrial sewing machine and two real-time controlled Universal Robots 6-axis industrial manipulators. A force feedback system combined with optical edge sensors is evaluated for the control of the sewing process. The force sensors are used to synchronize the velocity and feed rate between the robots and the sewing machine. A test cell was built to determine the feasibility of the force feedback control and velocity synchronization. Experiments are presented which investigate the ability of the robot to feed a hide part into the sewing machine using a force sensor and different strategies for velocity synchronization. A new automated sewing system is described, consisting of two robots handling the fabric on the table in a similar manner as does a human operator during sewing. To enable user-friendly operation of the system operation, particularly in the phase of preparing new tasks, the original Multi-arm Robot Control (MRC) system has been developed. It incorporates a task-oriented robot language and graphical user interface to enable easy programming of complex motion such as hands coordination during task execution, fabric tension control, and synchronization with the sewing machine speed. To avoid possible collisions, simulation of the already programmed task can be easily performed. The control of hand coordination and the fabric tension has also been developed and implemented. To control seam path and its deviation from the desired trajectory, visual feedback was adopted. Complete system functioning was verified experimentally by sewing. The work addresses the problem of clothing perception and manipulation by a two armed industrial robot aiming at a real-time automated folding of a piece of garment spread out on a flat surface. A complete solution combining vision sensing, garment segmentation and understanding, planning of the manipulation and its real execution on a robot is proposed. A new polygonal model of a garment is introduced. Fitting the model into a segmented garment contour is used to detect garment landmark points. It is shown how folded variants of the unfolded model can be derived automatically. Universality and usefulness of the model is demonstrated by its favorable performance within the whole folding procedure which is applicable to a variety of garments categories (towel, pants, shirt, etc.) and evaluated experimentally using the two armed robot. The principal novelty with respect to the state of the art is in the new garment polygonal model and its manipulation planning algorithm which leads to the speed up by two orders of magnitude. The sewing process is a manufacturing technology which presents severe challenges for automation. Due to variations in the material properties and unpredictable mechanical compliance, real-time sensor-based control strategies are necessary to achieve satisfying results. This paper presents a sewing cell consisting of two lightweight industrial robots and a sewing machine. Sensors are included both for force and edge positioning control. Experiments are presented showing the performance of the proposed real-time control framework. The experiments focus on the real-time control loop for force and edge control during the sewing process.