Dynamic Environment Robot Path Planning Using Hierarchical Evolutionary Algorithms

The problem of path planning deals with the computation of an optimal path of the robot, from source to destination, such that it does not collide with any obstacle on its path. In this paper we solve the problem of path planning separately in two hierarchies. The coarser hierarchy finds the path in a static environment consisting of the entire robotic map. The resolution of the map is reduced for computational speedup. The finer hierarchy takes a section of the map and computes the path for both static and dynamic environments. Both the hierarchies make use of Evolutionary Algorithm for planning. Both these hierarchies optimize as the robot travels in the map. The static environment path gets more and more optimized along with generations. Hence an extra setup cost is not required like other evolutionary approaches. The finer hierarchy makes the robot easily escape from the moving obstacle, almost following the path shown by the coarser hierarchy. This hierarchy extrapolates the movements of the various objects by assuming them to be moving with same speed and direction. Experimentation was done in a variety of scenarios with static and mobile obstacles. In all the cases the robot could optimally reach the goal. Further the robot was even able to escape from the sudden occurrences of obstacles.