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.

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