Home /Research /Force estimation and slip detection/classification for grip control using a biomimetic tactile sensor
MANIPULATION

Force estimation and slip detection/classification for grip control using a biomimetic tactile sensor

Zhe Su, Karol Hausman, Yevgen Chebotar, Artem Molchanov, Gerald E. Loeb, Gaurav S. Sukhatme, Stefan Schaal

Year
2015
Citations
215

Abstract

We introduce and evaluate contact-based techniques to estimate tactile properties and detect manipulation events using a biomimetic tactile sensor. In particular, we estimate finger forces, and detect and classify slip events. In addition, we present a grip force controller that uses the estimation results to gently pick up objects of various weights and texture. The estimation techniques and the grip controller are experimentally evaluated on a robotic system consisting of Barrett arms and hands. Our results indicate that we are able to accurately estimate forces acting in all directions, detect the incipient slip, and classify slip with over 80% success rate.

Keywords

Tactile sensorSlip (aerodynamics)Artificial intelligenceComputer scienceComputer visionContact forceNormal forceEngineeringControl theory (sociology)Robot

Related papers

Browse all MANIPULATION papers