Planning multi-paths using speciation in genetic algorithms

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.