Abstract

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.

Meeting Name

International Joint Conference on Neural Networks, 2003 (2003: Jul. 20-24, Portland, OR)

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

8051 Microcontroller; RAM-Based Neural Network; Collision Avoidance; Embedded Applications; Microprocessor System; Mobile Robots; Multi-Layer Neural Network Training; Neurocontrollers; Random-Access Storage

International Standard Book Number (ISBN)

0-7803-7898-9

International Standard Serial Number (ISSN)

1098-7576

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2003 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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