TCB Publications - Abstract

TCB Publications - Abstract

Michael Zeller, Rajeev Sharma, and Klaus Schulten. Learning the perceptual control manifold for sensor-based robot path planning. In Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA'97), pp. 48-53. IEEE Computer Society Press, 1997.

ZELL97A The Perceptual Control Manifold is a recently introduced concept that extends the notion of the robot configuration space to include sensor feedback for robot motion planning. In this paper, we propose a framework for sensor-based robot motion planning using the Topology Representing Network algorithm to develop a learned representation of the Perceptual Control Manifold. The topology preserving features of the neural network lend themselves to yield, after learning, a diffusion-based path planning strategy for flexible obstacle avoidance. Simulations on path control and flexible obstacle avoidance demonstrate the feasibility of this approach for motion planning and illustrate the potential for further robotic applications.

Download Full Text

The manuscripts available on our site are provided for your personal use only and may not be retransmitted or redistributed without written permissions from the paper's publisher and author. You may not upload any of this site's material to any public server, on-line service, network, or bulletin board without prior written permission from the publisher and author. You may not make copies for any commercial purpose. Reproduction or storage of materials retrieved from this web site is subject to the U.S. Copyright Act of 1976, Title 17 U.S.C.

Download full text: PDF ( 1.2MB), PS (242.3KB)