By Topic

Experience-based and tactile-driven dynamic grasp control

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Jan Steffen ; Neuroinformatics Group, Faculty of Technology, University of Bielefeld, Germany ; Robert Haschke ; Helge Ritter

Algorithms for dextrous robot grasping always have to cope with the challenge of achieving high object specialisation for a wide range of grasping contexts. In this paper, we present a tactile-driven approach that dynamically uses the robot's grasping experience to address this issue. During the grasp movement, the current contact information is used to dynamically adapt the grasping control by targeting the best matching posture from the experience base. Thus, the robot recalls and actuates a grasp it already successfully performed in a similar tactile context. To efficiently represent the experience, we introduce the grasp manifold assuming that grasp postures form a smooth manifold in hand posture space. We present a simple way of providing approximations of grasp manifolds using self-organising maps (SOMs). The algorithm is evaluated on three different geometry primitives - box, cylinder and sphere - in a physics-based computer simulation.

Published in:

2007 IEEE/RSJ International Conference on Intelligent Robots and Systems

Date of Conference:

Oct. 29 2007-Nov. 2 2007