There have been very few demonstrations ofthe application ofVLSI neural networks to real world problems. Yet there are many signal processing, pattern recognition or optimization problems where a large number of competing hypotheses need to be explored in parallel, most often in real time. The massive parallelism of VLSI neural network devices, with one multiplier circuit per synapse, is ideally suited to such problems. In this paper, we present preliminary results from our design for a real time robot navigation system based on VLSI neural network modules.

There have been very few demonstrations ofthe application ofVLSI neural networks to real world problems. Yet there are many signal processing, pattern recognition or optimization problems where a large number of competing hypotheses need to be explored in parallel, most often in real time. The massive parallelism of VLSI neural network devices, with one multiplier circuit per synapse, is ideally suited to such problems. In this paper, we present preliminary results from our design for a real time robot navigation system based on VLSI neural network modules. This is a - Also: RSRE, Great Malvern, Worcester, WR14 3PS 422 Real-time Autonomous Robot Navigation Using VLSI Neural Networks 423 real world problem which has not been fully solved by traditional AI methods; even when partial solutions have been proposed and implemented, these have required vast computational resources, usually remote from the robot and linked to it via an umbilical cord. 2 OVERVIEW The aim of our work is to develop an autonomous vehicle capable of real-time navigation, including obstacle avoidance, in a known indoor environment.