Neuromorphic Event-Based Slip Detection and suppression in Robotic Grasping and Manipulation

• URL: http://arxiv.org/abs/2004.07386v1
• Date: Wed, 15 Apr 2020 23:12:30 GMT
• Title: Neuromorphic Event-Based Slip Detection and suppression in Robotic Grasping and Manipulation
• Authors: Rajkumar Muthusamy, Xiaoqian Huang, Yahya Zweiri, Lakmal Seneviratne and Dongming Gan
• Abstract summary: A novel vision-based finger system for slip detection and suppression is proposed. A threshold method is devised to autonomously sample noise in real-time to improve slip detection. A fuzzy based suppression strategy using incipient slip feedback is proposed for regulating the grip force.
• Score: 1.0674604700001966
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Slip detection is essential for robots to make robust grasping and fine manipulation. In this paper, a novel dynamic vision-based finger system for slip detection and suppression is proposed. We also present a baseline and feature based approach to detect object slips under illumination and vibration uncertainty. A threshold method is devised to autonomously sample noise in real-time to improve slip detection. Moreover, a fuzzy based suppression strategy using incipient slip feedback is proposed for regulating the grip force. A comprehensive experimental study of our proposed approaches under uncertainty and system for high-performance precision manipulation are presented. We also propose a slip metric to evaluate such performance quantitatively. Results indicate that the system can effectively detect incipient slip events at a sampling rate of 2kHz ($\Delta t = 500\mu s$) and suppress them before a gross slip occurs. The event-based approach holds promises to high precision manipulation task requirement in industrial manufacturing and household services.

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