Real-time Obstacle Avoidance Strategy for Mobile Robot Based On Improved Coordinating Potential Field with Genetic Algorithm

Author

Cen, Yuwan ; Wang, Lihua ; Zhang, Handong

Author_Institution

Anhui Univ. of Technol., Anhui

fYear

2007

fDate

1-3 Oct. 2007

Firstpage

415

Lastpage

419

Abstract

To overcome the problems during navigation of mobile robots in dynamic environment using the traditional artificial potential field (APF) method, a novel improved method called coordinating potential field (CPF) is proposed. The local potential field is constructed by using local subgoals, which obtained by updating dynamic windows. The questions of local minima, oscillation between multiple obstacles and real-time dynamic obstacle avoidance are solved. At last multi-objective parameter optimization is implemented by using adaptive genetic algorithm. Simulation results indicate that this strategy is practicable and effective.

Keywords

adaptive control; collision avoidance; genetic algorithms; mobile robots; optimal control; adaptive genetic algorithm; artificial potential field method; coordinating potential field; dynamic environment; dynamic window update; mobile robot navigation; multiobjective parameter optimization; real-time obstacle avoidance; Algorithm design and analysis; Artificial intelligence; Control systems; Genetic algorithms; Mobile robots; Navigation; Real time systems; Robot kinematics; Robot sensing systems; Safety; Mobile robots; adaptive genetic algorithm; artificial coordinating potential field (CPF); artificial potential field (APF); real-time obstacle avoidance;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Applications, 2007. CCA 2007. IEEE International Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4244-0442-1

Electronic_ISBN

978-1-4244-0443-8

Type

conf

DOI

10.1109/CCA.2007.4389266

Filename

4389266