Abstract
Robot Path Planning (RPP) is solved using Genetic Algorithm (GA) principle for collision-free navigation for the three dimensional static space to find the optimal path. In this paper, Layered Approach is employed where the whole three dimensional space is considered as layers of two dimensional spaces to accomplish the RPP to reach the target by avoiding obstacles and find the shortest path. The quality of the path is ensured by nearest neighbourhood approach. Implementation of the principle of GA to solve RPP is effective where the environment contains huge number of solution paths compared to the classical methods to obtain the shortest path from source to target. This approach is tested for different number of layers and the results are tabled. The path generated and optimal path obtained by the implementation of this approach has been compared with the cost of the optimal path obtained manually.
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