aiqbench analysis
This study demonstrates that static representations outperform dynamic and combined approaches for contact-angle estimation using event-based tactile sensors, achieving sub-10ms latency and lower error margins across varying motion speeds. The findings validate the efficacy of persistent contact state recovery for high-frequency robotic manipulation tasks, offering a robust solution for handling motion interruptions without sacrificing processing speed.
Static and Dynamic Representations for Tactile Contact-Angle Estimation with Event-Based Sensors
arXiv:2606.03545v1 Announce Type: new Abstract: Event-based tactile sensing offers low-latency signal acquisition for contact-rich robotic interaction. This paper investigates contact-angle estimation using event streams from an event-based tactile sensor (NeuroTac) and compares three event-derived spatial contour representations: a dynamic representation capturing recent event activity, a static representation recovering a more persistent contact state, and their combined representation. Across the evaluated motion scenarios, all representation pipelines exhibited P99 processing latency below 10 ms at all tested sampling intervals, demonstrating their potential for high-frequency event-based tactile angle estimation in robotic manipulation. The static representation consistently achieved marginally better performance than the dynamic and combined representations under scenario-specific training, yielding a mean overall MAE of 0.160{\deg} during continuous sensor rolling and a stop-phase mean MAE of 0.251{\deg} during randomly inserted motion interruptions. It also exhibited smaller performance fluctuations across speed and indentation depth variations than the other two representations.
Abstract:Event-based tactile sensing offers low-latency signal acquisition for contact-rich robotic interaction. This paper investigates contact-angle estimation using event streams from an event-based tactile sensor (NeuroTac) and compares three event-derived spatial contour representations: a dynamic representation capturing recent event activity, a static representation recovering a more persistent contact state, and their combined representation. Across the evaluated motion scenarios, all representation pipelines exhibited P99 processing latency below 10 ms at all tested sampling intervals, demonstrating their potential for high-frequency event-based tactile angle estimation in robotic manipulation. The static representation consistently achieved marginally better performance than the dynamic and combined representations under scenario-specific training, yielding a mean overall MAE of 0.160° during continuous sensor rolling and a stop-phase mean MAE of 0.251° during randomly inserted motion interruptions. It also exhibited smaller performance fluctuations across speed and indentation depth variations than the other two representations.
8 pages, 8 figures. Submitted to IEEE Robotics and Automation Letters (RAL), under review
Robotics (cs.RO)
arXiv:2606.03545 [cs.RO]
(or arXiv:2606.03545v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2606.03545 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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Full text under the publisher's open licence · 248 words