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A RAM-based neural network for collision avoidance in a mobile robot

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4 Author(s)
Q. Yao ; Dept. of Electr. & Comput. Eng., Missouri Univ., Rolla, MO, USA ; D. Beetner ; D. C. Wunsch ; B. Osterloh

A RAM-based neural network is being developed for a mobile robot controlled by a simple microprocessor system. Conventional neural networks often require a powerful and sophisticated computer system. Training a multi-layer neural network requires repeated presentation of training data, which often results in very long learning time. The goal for this paper is to demonstrate that RAM-based neural networks are a suitable choice for embedded applications with few computational resources. This functionality is demonstrated in a simple robot powered by an 8051 microcontroller with 512 bytes of RAM. The RAM-based neural network allows the robot to detect and avoid obstacles in real time.

Published in:

Neural Networks, 2003. Proceedings of the International Joint Conference on  (Volume:4 )

Date of Conference:

20-24 July 2003