TCB Publications - Abstract

Michael Zeller, Rajeev Sharma, and Klaus Schulten. Vision-based robot motion planning using a topology representing neural network. In Jens Kalkkuhl, Ken Hunt, Rafal Zbikowski, and Andrzej Dzielinski, editors, Applications of Neural Adaptive Control Technology, volume 17 of World Scientific Series in Robotics and Intelligent Systems, pp. 181-204. World Scientific Publishing, 1997.

ZELL97 The goal of integrating sensors into robot motion planning has incited recent research efforts. The Perceptual Control Manifold serves this goal extending the notion of the robot configuration space to include sensor space. In this paper, we develop a framework for sensor-based motion planning of robotic manipulators 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. We demonstrate the capabilities of topology preserving maps using an industrial robot simulator and a pneumatically driven robot arm (SoftArm).

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