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

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 vibratio...

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Veröffentlicht in:IEEE access 2020, Vol.8, p.153364-153384
Hauptverfasser: Muthusamy, Rajkumar, Huang, Xiaoqian, Zweiri, Yahya, Seneviratne, Lakmal, Gan, Dongming
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Sprache:eng
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Zusammenfassung: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 and object feature events in real-time to improve slip detection and suppression. 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. For a class of objects, results indicate that the system can effectively detect incipient slip events at a sampling rate of 2kHz (Δt = 500μs) 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.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3017738