Planning multi-paths using speciation in genetic algorithms

Author

Hocaoglu, Cem ; Sanderson, Arthur C.

Author_Institution

Dept. of Electr. Comput. & Syst. Eng., Rensselaer Polytech. Inst., Troy, NY, USA

fYear

1996

Firstpage

378

Lastpage

383

Abstract

A path planning algorithm is developed based on a minimal representation size cluster genetic algorithm (MRSC GA). The algorithm utilizes evolutionary computation techniques for planning paths for mobile robots, piano-movers problems and N-link manipulators. MRSC GA is used for generating multi-paths to provide alternative solutions to the path planning problem. The generation of alternative solutions is especially important for planning paths in dynamic environments. A novel iterative multi-resolution path representation is used as a basis for the GA coding. The effectiveness of the algorithm is demonstrated on a number of 2D path planning problems

Keywords

genetic algorithms; iterative methods; mobile robots; path planning; 2D path planning problems; N-link manipulators; dynamic environments; evolutionary computation techniques; genetic algorithms; iterative multi-resolution path representation; minimal representation size cluster genetic algorithm; mobile robots; multi-path generation; multi-path planning; path planning algorithm; piano-movers problems; speciation; Agile manufacturing; Algorithm design and analysis; Clustering algorithms; Computer aided manufacturing; Evolutionary computation; Genetic algorithms; Iterative algorithms; Navigation; Path planning; Robots;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 1996., Proceedings of IEEE International Conference on

Conference_Location

Nagoya

Print_ISBN

0-7803-2902-3

Type

conf

DOI

10.1109/ICEC.1996.542393

Filename

542393