Towards Robust Autonomous Grasping with Reflexes Using High-Bandwidth Sensing and Actuation
Author(s)
SaLoutos, Andrew; Kim, Hongmin; Stanger-Jones, Elijah; Guo, Menglong; Kim, Sangbae
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Modern robotic manipulation systems fall short of human manipulation skills partly because they rely on closing
feedback loops exclusively around vision data, which reduces system bandwidth and speed. By developing autonomous grasping reflexes that rely on high-bandwidth force, contact, and proximity data, the overall system speed and robustness can be increased while reducing reliance on vision data. We are developing a new system built around a low-inertia, high-speed arm with nimble fingers that combines a high-level trajectory planner operating at less than 1 Hz with low-level autonomous reflex controllers running upwards of 300 Hz. We characterize the reflex system by comparing the volume of the set of successful grasps for a naive baseline controller and variations of our reflexive grasping controller, finding that our controller expands the set of successful grasps by 55% relative to the baseline. We also deploy our reflexive grasping controller with
a simple vision-based planner in an autonomous clutter clearing task, achieving a grasp success rate above 90% while clearing over 100 items.
Description
2023 IEEE International Conference on Robotics and Automation (ICRA 2023) May 29 - June 2, 2023. London, UK
Date issued
2023-05-29Department
Massachusetts Institute of Technology. Department of Mechanical EngineeringJournal
2023 IEEE International Conference on Robotics and Automation (ICRA)
Publisher
IEEE
Citation
SaLoutos, Andrew, Kim, Hongmin, Stanger-Jones, Elijah, Guo, Menglong and Kim, Sangbae. 2023. "Towards Robust Autonomous Grasping with Reflexes Using High-Bandwidth Sensing and Actuation." 2023 IEEE International Conference on Robotics and Automation (ICRA).
Version: Author's final manuscript