Improved Ant Colony Algorithm for Multi Objective Search of Group Robots
In multi-target search,it is easy for swarm robots to repeatedly search each other in the target search process,mainly because the Ant colony optimization algorithms relies on repeated operations in the pheromone update process,a multi-objective search method for swarm robots based on improved ant colony algorithm is proposed.For the pheromone concentration update rule in Ant colony optimization algorithms,the maximum and minimum cross principle is adopted to improve,and the pheromone up-date method based on path selection probability and path length is obtained.Combined with rasterisation processing,target fruits calculation,dynamic adjustment of search step size,state transition probability and final unit selection of roulette wheel gam-bling,the swarm robot can search multiple targets.Testing was conducted in both static and dynamic environments,through the distance between each robot,the distance between the robot and the obstacle,and the arrival situation between the robot and the target,it was found that the proposed method accurately avoided the obstacle at an ideal distance and successfully searched for all targets,the application effect of the method is good.
Improving Ant Colony AlgorithmPheromone UpdatingGroup RobotsRoulette StrategyMulti Objective Search
万方数据
维普
