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

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 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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