By Topic

Behavior control for a mobile robot by multihierarchical neural network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Sekiguchi, M. ; Fujitsu Lab. Ltd., Kawasaki, Japan ; Negata, S. ; Asakawa, K.

A mobile robot with behavior controlled by a neural network, and its learning method are presented. The robot has four wheels and travels with two motors; it has twelve sensors for detecting internal conditions and changes in environment. The sensor signals are fed into the input layer of the network, and the network outputs motor control commands. The network model is divided into two subnetworks connected to each other with a short-term memory to process time-dependent data. The robot can learn various habits by changing the patterns to be taught. One example, the habits to play a cops-and-robbers game, was taught. Through training, the robots learned habits such as capture and escape

Published in:

Robotics and Automation, 1989. Proceedings., 1989 IEEE International Conference on

Date of Conference:

14-19 May 1989