Improved ACO-based path planning with rollback and death strategies

This paper is concerned with the path planning problem for a class of mobile robot systems in a complex environment. By applying the rollback strategy into the traditional ACO, the ants can return to the previous node if there is no any solution of the algorithm. In this sense, the number of the ants which successfully reach the target is increased. Then, in order to reduce the effect of invalid pheromone on the evolution of ant colony as well as reduce the cost of the time, the death strategy is utilized. Our aim of this paper is to apply the rollback and death strategies into ACO such that the state transfer rule is improved and the composition structure of pheromone is optimized. By giving a certain upper bound of the pheromone of the node, the node whose pheromone exceeds such an upper bound will not be selected. Therefore, the efficiency of the algorithm is greatly improved. Finally, a simulation example is given to illustrate the effectiveness of the proposed algorithm.