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The aim of this paper is to design an efficient and fast immune evolution algorithm for solving path planning program 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 features related to initialization and selection of candidate solution 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 detail and the simulation experiment is carried out. The effectiveness of the approach is shown by the experiment result.