Research On Path Planning Of Mobile Robot In Complex Environment

Path planning is an important part of mobile robot research field,and it is a prerequisite for mobile robot to complete complex tasks.This paper improves the classical ant colony algorithm,and then combines it with the improved artificial potential field method to improve the path planning efficiency of mobile robot in complex environment.The main research contents of this paper are as follows:Firstly,the classical ant colony algorithm is improved from three aspects: initial pheromone distribution,transfer probability and global pheromone update.The initialization of pheromones is improved,which solves the problems of slow searching speed at the beginning of the algorithm.In terms of the distribution of initial pheromones,this paper considers the distance between the internal node and the diagonal line of the grid map,and if the distance is shorter,the concentration of pheromone is relatively higher.This method solves the problem of the ants in the early search blindness.The risk factor of the next feasible node is considered in the formula of the transfer probability of the ant,which can reduce the probability of the algorithm getting into local optimal.In the aspect of the update of global pheromone,this paper reduces the pheromones released by the ants on the worst path,and increases the pheromones released by the ants on the optimal path,the risk factor of the next feasible is also considered in the aspect of the update of global pheromone,this improved method can increase the convergence speed of the algorithm and prevent the algorithm from getting into local optimum.Secondly,the problem of not reaching the target point in the classical artificial potential field method is improved,and the repulsion function is adjusted by considering the distance from the current position to the target point without increasing the repulsion force.Finally,a fusion optimization algorithm based on improved ant colony algorithm and improved artificial potential field method is proposed to improve the efficiency of path planning in complex environment.The fusion method is as follows: this paper uses the improved ant colony algorithm to obtain the optimal path in the static environment,and then takes the optimal path turning point as the sub-target of the improved artificial potential field method for local path planning.In the end,this paper uses Matlab2016 b to simulate and improve the environment complexity by adding obstacles.Then,the integrated optimization algorithm is compared with the improved ant colony algorithm to verify the efficiency of the integrated optimization algorithm.