DocumentCode
2840273
Title
Global path planning method of mobile robot in uncertain environment
Author
Zhang, Qian ; Li, Ming ; Wang, Xuesong
Author_Institution
Sch. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou, China
fYear
2010
fDate
26-28 May 2010
Firstpage
4320
Lastpage
4324
Abstract
Path planning is one of the key technologies in the robot research. The aim of it is to find the shortest safe path in the objective environments. Firstly, the robot is transformed into particle by expanding obstacles method; the obstacle is transformed into particle by multi-round enveloping method. Secondly, we make the Voronoi graph of the particles of obstacle and find the skeleton topology about the feasible path. Following, a new arithmetic named heuristic bidirectional ant colony algorithm is proposed by joining the merit of ant colony algorithm, Dijkstra algorithm and heuristic algorithm, with which we can find the shortest path of the skeleton topology. After transforming the path planning into n-dimensions quadrate feasible region by coordinate transformation and solving it with particle swarm optimization, the optimization of the path planning is acquired.
Keywords
computational geometry; mobile robots; optimisation; path planning; position control; topology; uncertain systems; Dijkstra algorithm; Voronoi graph; ant colony algorithm; coordinate transformation; global path planning method; mobile robot; objective environments; robot research; skeleton topology; uncertain environment; Ant colony optimization; Heuristic algorithms; Intelligent robots; Mobile robots; Optimization methods; Particle swarm optimization; Path planning; Robot kinematics; Skeleton; Topology; Heuristic Bidirectional Ant Colony Algorithm; Particle Swarm Optimization; Path Planning; Voronoi Graph;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location
Xuzhou
Print_ISBN
978-1-4244-5181-4
Electronic_ISBN
978-1-4244-5182-1
Type
conf
DOI
10.1109/CCDC.2010.5498378
Filename
5498378
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