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Addressing Perception Uncertainty Induced Failure Modes in Robotic Bin-Picking

Published

Author(s)

Krishnanand N. Kaipa, Akshaya S. Kankanhalli-Nag, Nithyananda B. Kumbla, Shaurya Shriyam, Srudeep Somnaath Thevendria-Karthic, Jeremy Marvel, Satyandra K. Gupta

Abstract

We present a comprehensive approach to handle perception uncertainty to reduce failure rates in robotic bin-picking. Our focus is on mixed-bins. We identify the main failure modes at various stages of the bin-picking task and present methods to recover from them. If uncertainty in part detection leads to perception failure, then human intervention is invoked. Our approach estimates the confidence in the part match provided by an automated perception system, which is used to detect perception failures. Human intervention is also invoked if uncertainty in estimated part location and orientation leads to a singulation planning failure. We have developed a user interface that enables remote human interventions when necessary. Finally, if uncertainty in part posture in the gripper leads to failure in placing the part with the desired accuracy, sensor-less fine-positioning moves are used to correct the final placement errors. We have developed a fine-positioning planner with a suite of fine-motion strategies that offer different tradeoffs between completion time and postural accuracy at the destination. We report our observations from system characterization experiments with a dual-armed Baxter robot, equipped with a Ensenso three dimensional camera, to perform bin-picking on mixed-bins.
Citation
Robotics and Computer-Integrated Manufacturing
Volume
42

Keywords

robot perception, bin picking, human-robot interaction

Citation

Kaipa, K. , Kankanhalli-Nag, A. , Kumbla, N. , Shriyam, S. , Thevendria-Karthic, S. , Marvel, J. and Gupta, S. (2016), Addressing Perception Uncertainty Induced Failure Modes in Robotic Bin-Picking, Robotics and Computer-Integrated Manufacturing, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=920186 (Accessed May 22, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created May 2, 2016, Updated October 12, 2021