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Optimal Object Placement for Minimum Discontinuity Non-revisiting Coverage Task | IEEE Conference Publication | IEEE Xplore

Optimal Object Placement for Minimum Discontinuity Non-revisiting Coverage Task

Publisher: IEEE

Abstract:

This work considers the optimal non-revisiting coverage tasks with a single non-redundant manipulator for the case when the object can be positioned at a predefined set o...View more

Abstract:

This work considers the optimal non-revisiting coverage tasks with a single non-redundant manipulator for the case when the object can be positioned at a predefined set of locations within the workcell. The scenario is often encountered in typical industrial settings, for instance when the object presents itself along a conveyor belt and its surface can not be serviced at a single location - the object being large or complex for that endeavour. Given the non-bijective nature of manipulator kinematics between task and joint space, without explicit consideration of joint-space continuity during its construction, a continuous coverage path designed in task-space may easily be truncated into intermittent segments where the manipulator needs to adopt a different configuration to continue the task, resulting in manipulator motions where the end-effector will need to lift off the surface, an altogether undesirable characteristic affecting the quality of the final product for smooth operations on objects such as polishing, painting or deburring. In this work, a novel algorithm to optimally partition the task-space whilst considering the various finite locations where the object may be stationed is proposed that ensures joint-space coverage continuity with minimal lift-offs. Results from the algorithm being challenged to achieve coverage of a number of objects, both in simulation and in real tests with an industrial manipulator, prove the effectiveness of the proposed planner when compared with classical coverage strategies faced with the same problem.
Date of Conference: 30 May 2021 - 05 June 2021
Date Added to IEEE Xplore: 18 October 2021
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Publisher: IEEE
Conference Location: Xi'an, China

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