Affiliation:
1. Department of Computer Science Stanford University Stanford, California 94305
2. Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge, Massachusetts 02139
Abstract
In order for a robot hand to grasp objects stably without using object models, tactile feedback from the fingers is sometimes necessary. This feedback can be used to adjust grasping forces to prevent a part from slipping from a hand. If the angle of force at the object-finger contact can be deter mined, slip can be prevented by the proper adjustment of finger forces. Another important tactile sensing task is finding the edges and corners of an object since they are usually feasible grasping locations.This paper describes how this information can be extracted from the finger-object contact using strain sensors beneath a compliant skin. For determining contact forces, strain mea surements are easier to use than the surface deformation profile. The finger is modeled as an infinite linear elastic half-plane to predict the measured strain for several contact types and forces. The number of sensors required is less than has been proposed for other tactile recognition tasks.A rough upper bound on sensor density requirements for a specific depth is presented that is based on the frequency response of the elastic medium. The effects of different sensor stiffnesses on sensor performance are discussed.
Subject
Applied Mathematics,Artificial Intelligence,Electrical and Electronic Engineering,Mechanical Engineering,Modeling and Simulation,Software
Cited by
70 articles.
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