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Simulation Based On-Line Evaluation of Singulation Plans to Handle Perception Uncertainty in Robotic Bin Picking

[+] Author Affiliations
Nithyananda B. Kumbla

University of Maryland, College Park, MD

Shantanu Thakar, Satyandra K. Gupta

University of Southern California, Los Angeles, CA

Krishnanand N. Kaipa

Old Dominion University, Norfolk, VA

Jeremy Marvel

National Institute of Standards and Technology, Gaithersburg, MD

Paper No. MSEC2017-2955, pp. V003T04A002; 12 pages
doi:10.1115/MSEC2017-2955
From:
  • ASME 2017 12th International Manufacturing Science and Engineering Conference collocated with the JSME/ASME 2017 6th International Conference on Materials and Processing
  • Volume 3: Manufacturing Equipment and Systems
  • Los Angeles, California, USA, June 4–8, 2017
  • Conference Sponsors: Manufacturing Engineering Division
  • ISBN: 978-0-7918-5074-9
  • Copyright © 2017 by ASME

abstract

Robotic bin picking requires using a perception system to estimate the posture of parts in the bin. The selected singulation plan should be robust with respect to perception uncertainties. If the estimated posture is significantly different from the actual posture, then the singulation plan may fail during execution. In such cases, the singulation process will need to be repeated. We are interested in selecting singulation plans that minimize the expected task completion time. In order to estimate the expected task completion time for a proposed singulation plan, we need to estimate the probability of success and the plan execution time. Robotic bin picking needs to be done in real-time. Therefore candidate singulation plans need to be generated and evaluated in real-time. This paper presents an approach for utilizing computationally efficient simulations for on-line evaluation of singulation plans. Results from physical experiments match well with predictions obtained from simulations.

Copyright © 2017 by ASME

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