Ultra-Fast Lightweight Incipient Slip Detection Using Hyperdimensional Computing with the PapillArray Tactile Sensor

Le résumé fourni par la source

Timely detection of incipient slip is critical for delicate robotic grasping and dexterous manipulation. However, existing learning-based methods suffer from detection latency and high computational demands. In this paper, we present an ultra-fast lightweight incipient slip detection framework based on hyperdimensional (HD) computing, using the PapillArray optical tactile sensor. Our approach introduces a novel graphical-spatial-temporal HD encoding scheme coupled with a context-driven training and inference strategy, achieving a slip detection accuracy of 91.78% in offline evaluation. The resulting model is exceptionally compact and highly edge-compatible, with a size of only 0.375 kB. Furthermore, hardware acceleration on an FPGA enables inference within 0.42 microseconds, representing an over 10^4 speedup compared to optimized CPU implementations. Online robotic experiments involving grip-force control based on the proposed slip detection method further validate its practical effectiveness. This work offers a practical and scalable solution for real-time slip detection in robotic manipulation tasks.

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