Immune Evolution Algorithm Based Dynamic Path Planning Approach for the Soccer Robot

The aim of this paper is to design an efficient and fast immune evolution algorithm for solving path planning pro- gram of soccer robot. The idea is to accurately read the inherent drawbacks of existing immune algorithms (IA) and propose new techniques to resolve them. The basic features of IA dealt in this paper are: hypermutation mechanism, clone expansion, immune memory and several other fea- tures related to initialization and selection of candidate so- lution present in a population set. Dealing with the above- mentioned features we have proposed an improved immune evolution algorithm (IEA). The algorithm is described in de- tail and the simulation experiment is carried out. The effec- tiveness of the approach is shown by the experiment result.