Selfish and coordinative planning for multiple mobile robots by genetic algorithm

A novel strategy for coordination of multiple autonomous robots by using genetic algorithms (GAs) is presented. When a mobile robot moves from a point to a goal point, it is necessary to plan an optimal or feasible path for it, avoiding obstructions in its way and minimizing costs such as time, energy, and distance. This planning is referred to as selfish planning. When many robots move in the same space, it is necessary to select the most reasonable path so as to avoid collisions with other robots and to minimize the cost. This planning is referred to as coordinative planning. The GAs are search algorithms based on the mechanics of natural selection and natural genetics. The GAs are applied to both the selfish planning and the coordinative planning of multiple mobile robots