By Topic

The collision avoidance planning in multi-robot system by genetic fuzzy control algorithm

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)
Yan Yongjie ; No.28 Res. Inst., China Electron. Technol. Corp., Nanjing ; Zhang Yan

A collision-avoidance planning method in multi-robot system based on genetic algorithm optimized by fuzzy logic control is designed, which include a simplified three-tier structure: avoid robot, avoid static obstacles and moving to the goal. These actions reason independently, and take information from different sensors as inputs; all the outputs are next anticipant movement of robot. Then, it synthesizes the outputs of three actions based on the priority and weight. Subsequently, GA is used to optimize the width and central value of membership functions. Through the off-line self-optimization of fuzzy controller, a group of optimum parameters is gotten. The simulation results show that genetic algorithm improves the navigation performance of robot.

Published in:

Robotics and Biomimetics, 2008. ROBIO 2008. IEEE International Conference on

Date of Conference:

22-25 Feb. 2009