Mouse colony optimization algorithm for mobile robot path planning

Abstract

Robot path planning in a static environment is studied and mouse colony optimization is proposed after studying the mice' behavior of searching for food.Environment factor and experience factor are introduced.By using iterative method,the experience factor is updated after each search to find the best robot path in a static environment.Prohibition strategies are developed and thus path deadlocks are effectively avoided.Theoretic analysis and experimental results show that this algorithm enables the robot to rapidly find the optimal path and safely avoid collisions and it has advantages over other algorithms of the kind.