By Topic

Neural-fuzzy hybrid system for mobile robot path-planning in a partially known environment

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

2 Author(s)
Ro, P.I. ; Dept. of Mech. & Aerosp. Eng., North Carolina State Univ., Raleigh, NC, USA ; Lee, B.R.

In this paper, a neural-fuzzy hybrid control approach is proposed for controlling a mobile robot that can avoid an unexpected obstacle in a navigational space. First, to describe the global structure of a known environment, a heuristic dominant collision-free space band is introduced. Based on the band, the moving information in the known environment is trained to a neural controller. Then, during the execution of a mobile robot navigation moving information at each position is given from the neural controller. If the mobile robot encounters an unexpected obstacle, a fuzzy controller is activated to adjust the moving information given from the neural controller to avoid the unexpected obstacle. When the robot has safely avoided the obstacle and resume the originally taught path, the fuzzy controller is deactivated. Some numerical examples are presented to demonstrate the planning algorithm

Published in:

American Control Conference, Proceedings of the 1995  (Volume:1 )

Date of Conference:

21-23 Jun 1995