Research On Path Planning Of Mobile Robot Based On Improved Ant Colony Algorithm

The birth of mobile robots not only can improve the production efficiency of the automation industry,reduce production costs,but also can replace human beings to work in some dangerous environments or areas that are unreachable to human beings,which greatly promotes social development and progress.Many experts at home and abroad have invested in the research of mobile robots.Path planning technology is the research focus.It is the basis for mobile robots to go from the starting position to the working position and complete various tasks independently.A lot of researches have been done on this and corresponding solutions have been proposed.However,path planning is still a difficult point in complex environments,and it is difficult to achieve the desired results.The ant colony algorithm has achieved good results in solving the global optimization problem and is widely used in various fields.However,in complex environments,the ant colony algorithm path planning is prone to slow convergence,and the obtained solution is not optimal.The cause of the problem and propose an improvement strategy.Firstly,according to the starting point and target point position information,the global favorable area is selected to increase its initial pheromone value,and the pheromone initial value is unevenly distributed to improve the previous ant search efficiency;then the obstacle avoidance strategy is added to a'void blind search in the ant search path process.A large number of cross paths are generated and the number of ant deadlocks is effectively reduced.Finally,the pseudo-random transfer strategy controlled by dynamic parameters is used to propose high-quality ant pheromone update rules,adaptively adjust the pheromone volatilization coefficient,and improve the overall performance of the algorithm.Perform secondary planning based on the planned path information.The experimental results show that the improved ant colony algorithm has a faster convergence rate,which can find the global optimal solution and effectively reduce the energy loss of mobile robots.Based on the research of two-dimensional plane path planning,the three-dimensional space is divided into two planes,and then each plane is rasterized.The pheromone is stored in the path rnode instead of the original way stored in the path.Reduce pheromone Storage space,and carry out three-dimensional spatial path planning research based on hierarchical search.In view of the complex three-dimensional environment and changeable geomorphology,the obstacle avoidance strategy is added,the path heuristic information is improved,a new heuristic function is constructed,and according to the location information of the starting point and the target point as well as the direction of progress,In order to improve the efficiency of ant search,the initial value of path node pheromone is distributed unevenly.After each iteration,according to the renewal rule of high quality ants,the deadlock ants which have not reached the target point are abandoned,and the iterative threshold is set.When the algorithm tends to converge,the pheromone volatilization factor is adjusted adaptively,so as to avoid the algorithm falling into a stagnant state.The comparison and analysis of experiments show that the improved algorithm can find an optimal path safely,quickly and effectively in three-dimensional environment,which not only effectively reduces the convergence times of the algorithm,but also has a higher global search ability.