DocumentCode
3478412
Title
Optimal robot path planning based on danger degree map
Author
Xue, Yinghua ; Tian, Guohui ; Huang, Bin
Author_Institution
Sch. of Control Sci. & Eng., Shandong Univ., Jinan, China
fYear
2009
fDate
5-7 Aug. 2009
Firstpage
1040
Lastpage
1045
Abstract
A modified path planning approach is presented for mobile robot in the paper. First a new environment model called danger degree map (DDM) is constructed in order to provide more rich environment information than grids map. Then the equidistant distributed PSO whose fitness function is the weighted sum of the path length and the path danger degree is introduced to get a more reliable path than conventional PSO method, but it is not suitable for some specific environment. In order to expand the application scope of PSO, we proposed non-equidistant distributed PSO method based on the rate of change of barrier, which can enhance the adaptability to the environment. The algorithm present in the paper not only has a simple model and a rapid convergence, but also can avoid obstacles automatically and can obtain optimal path in different environments. Simulation results demonstrate the effectiveness and feasibility of the proposed methods.
Keywords
adaptive control; mobile robots; optimal control; particle swarm optimisation; path planning; adaptability; danger degree map; equidistant distributed PSO; fitness function; mobile robot; optimal robot path planning; particle swarm optimisation; Artificial neural networks; Distributed decision making; Genetic algorithms; Iterative algorithms; Logistics; Mobile robots; Optimal control; Particle swarm optimization; Path planning; Robotics and automation; danger degree map; non-equidistant distributed PSO; particle swarm optimization(PSO); robot path planning;
fLanguage
English
Publisher
ieee
Conference_Titel
Automation and Logistics, 2009. ICAL '09. IEEE International Conference on
Conference_Location
Shenyang
Print_ISBN
978-1-4244-4794-7
Electronic_ISBN
978-1-4244-4795-4
Type
conf
DOI
10.1109/ICAL.2009.5262573
Filename
5262573
Link To Document