Title :
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
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;
Conference_Titel :
Evolutionary Computation, 1996., Proceedings of IEEE International Conference on
Conference_Location :
Nagoya
Print_ISBN :
0-7803-2902-3
DOI :
10.1109/ICEC.1996.542393
