Path planning using neighborhood based crowding differential evolution

Abstract

Path planning problems are known as one of the most important techniques used in robot navigation. The task of path planning is to find several short and collision-free paths. Various optimization algorithms have used to handle path planning problems. Neighborhood based crowding differential evolution (NCDE) is an effective multi-modal optimization algorithm. It is able to locate multiple optima in a single run. In this paper, Bezier curve concept and NCDE are used to solve path planning problems. It is compared with several other methods and the results show that NCDE is able to generate satisfactory solutions. It can provide several alternative optimal paths in one single run for all the tested problems.