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HANDLING PERCEPTION UNCERTAINTY IN SIMULATION BASED SINGULATION PLANNING FOR ROBOTIC BIN PICKING.

Nithyananda B Kumbla1, Shantanu Thakar2, Krishnanand N Kaipa3

  • 1Department of Mechanical Engineering, University of Maryland, College Park, MD, USA.

Journal of Computing and Information Science in Engineering
|June 19, 2018
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Summary
This summary is machine-generated.

This study introduces efficient simulations for robotic bin picking, improving real-time part singulation by minimizing expected task completion time despite perception uncertainties. Results show simulations accurately predict real-world performance.

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Area of Science:

  • Robotics
  • Computer Vision
  • Artificial Intelligence

Background:

  • Robotic bin picking relies on perception systems to determine part pose, but uncertainties can lead to singulation plan failures and repeated attempts.
  • Minimizing expected task completion time is crucial for efficient robotic bin picking operations.

Purpose of the Study:

  • To develop an approach for generating and evaluating robotic bin picking singulation plans in real-time.
  • To minimize the expected task completion time by accounting for perception uncertainties and plan execution time.

Main Methods:

  • Utilizing computationally efficient simulations to generate candidate singulation plans.
  • Estimating the probability of success and execution time for each plan to determine expected task completion time.

Main Results:

  • The proposed simulation approach enables real-time generation and evaluation of singulation plans.
  • Predictions from simulations closely matched results from physical experiments, validating the approach.

Conclusions:

  • Computationally efficient simulations are effective for developing robust robotic bin picking singulation plans.
  • The approach successfully minimizes expected task completion time by addressing perception uncertainties in real-time.