We present an approach to automatically learn a bimanual robotic cleaning task on compliant objects. One robot grasps the object, while the other robot cleans it. Given a part with unknown deformation characteristics, the system visually detects the regions to be cleaned, and generates plans for both the grasping and cleaning arms. As the system performs cleaning attempts and gains experience with multiple new parts, it learns models of the part deformation depending on the cleaning force and grasping parameters. A planner iteratively generates tool paths for both robots using the available knowledge to optimize the cleaning time, including (1) delays from regrasping a part to minimize deflection and (2) time taken for repeated cleaning attempts over regions that remained dirty. A nonparametric deflection model is learned separately for each part, with minimal assumptions of the material behavior. We demonstrate the approach on a system of two KUKA LWR iiwa robots and a set of thin planar parts. Results indicate that the system is effective at rapidly learning part deformation models to enable effective iterative cleaning performance.
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ASME 2016 11th International Manufacturing Science and Engineering Conference
June 27–July 1, 2016
Blacksburg, Virginia, USA
Conference Sponsors:
- Manufacturing Engineering Division
ISBN:
978-0-7918-4990-3
PROCEEDINGS PAPER
Online Learning of Part Deformation Models in Robotic Cleaning of Compliant Objects Available to Purchase
Joshua D. Langsfeld,
Joshua D. Langsfeld
University of Maryland, College Park, MD
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Ariyan M. Kabir,
Ariyan M. Kabir
University of Maryland, College Park, MD
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Krishnanand N. Kaipa,
Krishnanand N. Kaipa
University of Maryland, College Park, MD
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Satyandra K. Gupta
Satyandra K. Gupta
University of Southern California, Los Angeles, CA
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Joshua D. Langsfeld
University of Maryland, College Park, MD
Ariyan M. Kabir
University of Maryland, College Park, MD
Krishnanand N. Kaipa
University of Maryland, College Park, MD
Satyandra K. Gupta
University of Southern California, Los Angeles, CA
Paper No:
MSEC2016-8663, V002T04A003; 11 pages
Published Online:
September 27, 2016
Citation
Langsfeld, JD, Kabir, AM, Kaipa, KN, & Gupta, SK. "Online Learning of Part Deformation Models in Robotic Cleaning of Compliant Objects." Proceedings of the ASME 2016 11th International Manufacturing Science and Engineering Conference. Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing. Blacksburg, Virginia, USA. June 27–July 1, 2016. V002T04A003. ASME. https://doi.org/10.1115/MSEC2016-8663
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