Static and Dynamic Representations for Tactile Contact-Angle Estimation with Event-Based Sensors
2026-06-02 • Robotics
Robotics
AI summaryⓘ
The authors studied how to estimate the angle of contact on a robot's touch sensor using special event-based data that records changes quickly. They compared three ways to represent this data: one showing recent activity, one showing a more stable picture, and one combining both. All methods were very fast, taking less than 10 milliseconds to process. The stable representation performed best overall, giving more accurate angle estimates and handling different speeds and pressures better than the others.
event-based tactile sensingcontact-angle estimationNeuroTac sensorspatial contour representationdynamic representationstatic representationprocessing latencymean absolute error (MAE)robotic manipulationsensor rolling
Authors
Yanhui Lu, Efi Psomopoulou, Benjamin Ward-Cherrier
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.