A Complete Coverage Path Planning Method for Mobile Robot in Uncertain Environments

Author

Qiu, Xuena ; Song, Jiatao ; Zhang, Xuejun ; Liu, Shirong

Author_Institution

Coll. of Electron. & Inf. Eng., Ningbo Univ. of Technol.

Volume

2

fYear

0

fDate

0-0 0

Firstpage

8892

Lastpage

8896

Abstract

In this paper, a novel complete coverage path planning method based on the biologically inspired neural networks, rolling path planning and heuristic searching approach is presented for mobile robot motion planning with obstacles avoidance. The biologically inspired neural network is used to model the environment and calculate the environment information, while the rolling planning technique and the heuristic searching algorithm are utilized for the path planning. Simulation studies show that the proposed method is very effective for the dynamic uncertain environments

Keywords

collision avoidance; heuristic programming; mobile robots; neurocontrollers; search problems; uncertain systems; biologically inspired neural networks; complete coverage path planning; dynamic uncertain environments; heuristic searching; mobile robot; motion planning; obstacle avoidance; rolling path planning; shortest tangent; Biological system modeling; Biomembranes; Educational institutions; Equations; Mobile robots; Motion planning; Neural networks; Neurons; Path planning; Robotics and automation; biologically inspired neural network; complete coverage path planning; rolling planning; the shortest tangent;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713719

Filename

1713719