Modified Genetic Algorithm-based Robot Path Planning to Avoid Static Obstacles Collision

摘要

In this paper, a modified Genetic Algorithm is presented for mobile robot path planning applications in a known environment. The algorithm provides the optimal path using the modified variable-length chromosomes study using the fitness function, which calculates the path length of the chromosomes such that the large path lengths are eliminated. The proposed algorithm uses the 8-way movement robot instead of the conventionally adopted 4-way movement commonly used in such applications. The results obtained using the proposed modified Genetic Algorithm during the study are compared with other approaches to the Genetic Algorithm. The proposed algorithm shows improvement in the convergence speed, provides better flexibility, provides shorter path length, and reduces the total time.