Whisker-Inspired Tactile Sensing for Contact Localization on Robot Manipulators

TL;DR

This paper introduces whisker-inspired tactile sensors for robots, enabling precise contact localization through light touches, with a Bayesian filtering algorithm achieving sub-millimeter accuracy in cluttered environments.

Contribution

The work presents a novel whisker-inspired sensor design and a Bayesian filtering-based localization algorithm, improving contact detection accuracy on robotic manipulators.

Findings

Contact points localized with sub-millimeter accuracy

Sensor outperforms baseline methods in contact tracking

Successfully demonstrated in real-world cluttered environments

Abstract

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.