2022/10/22 by Michael A. Lin, Emilio Reyes, Lin, Michael A. +5 · 2 citations
Engineering · Neuroscience · #FOS: Computer and information sciences #Industrial Vision Systems and Defect Detection #Robot Manipulation and Learning #Robotics (cs.RO) #Tactile and Sensory Interactions
paper · pdf · doi:10.48550/arxiv.2210.12387
openalex publication_date 2022/10/22 · openalex created_date 2022/10/31 · openalex updated_date 2026/07/28
Perceiving the environment through touch is important for robots to reach in cluttered environments, but devising a way to sense without disturbing objects is challenging. This work presents the design and modelling of whisker-inspired sensors that attach to the surface of a robot manipulator to sense its surrounding through light contacts. We obtain a sensor model using a calibration process that applies to straight and curved whiskers. We then propose a sensing algorithm using Bayesian filtering to localize contact points. The algorithm combines the accurate proprioceptive sensing of the robot and sensor readings from the deflections of the whiskers. Our results show that our algorithm is able to track contact points with sub-millimeter accuracy, outperforming a baseline method. Finally, we demonstrate our sensor and perception method in a real-world system where a robot moves in between free-standing objects and uses the whisker sensors to track contacts tracing object contours.