DocumentCode :
617902
Title :
Robot path planning in an environment with many terrains based on interval multi-objective PSO
Author :
Na Geng ; Dunwei Gong ; Yong Zhang
Author_Institution :
Sch. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou, China
fYear :
2013
fDate :
20-23 June 2013
Firstpage :
813
Lastpage :
820
Abstract :
In order to solve the problem of path planning in an environment with many terrains, we propose a method based on interval multi-objective Particle Swarm Optimization (PSO). First, the environment is modeled by the line partition method, and then, according to the distribution of the polygonal lines which form the robot path and taking the velocity´s disturbance into consideration, robot´s passing time is formulated as an interval by combining Local Optimal Criterion (LOC), and the path´s danger degree is estimated through the area ratio between the robot path and the danger source. In addition, the path length is also calculated as an optimization objective. As a result, the robot path planning problem is modeled as an optimization problem with three objectives. Finally, the interval multiobjective PSO is employed to solve the problem above. Simulation and experimental results verify the effectiveness of the proposed method.
Keywords :
mobile robots; particle swarm optimisation; path planning; LOC; interval multiobjective PSO; line partition method; local optimal criterion; particle swarm optimization; path danger degree; polygonal line distribution; robot passing time; robot path planning problem; terrain; velocity disturbance; Educational institutions; Evolutionary computation; Mathematical model; Optimization; Path planning; Robot kinematics; interval multi-objective optimization; many terrains; mobile robot; particle swarm optimization; path planning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2013 IEEE Congress on
Conference_Location :
Cancun
Print_ISBN :
978-1-4799-0453-2
Electronic_ISBN :
978-1-4799-0452-5
Type :
conf
DOI :
10.1109/CEC.2013.6557652
Filename :
6557652
Link To Document :
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