Research On Hybrid Path Planning For Mobile Robot

Mobile robots,as a product of the development of modern science and technology,are widely used in the fields of spaceflight,medical treatment,industry and so on.Path planning is the research focus in the field of mobile robot technology,which has strong scientific research value.At present,there are a lot of research results about the path planning of mobile robot based on the known environment and the static obstacle,but it is still a difficult problem for the robot path planning in the presence of dynamic obstacles.In this paper,based on the requirements of the selected research topics,the path planning problem of mobile robot in the presence of static environment and dynamic obstacles is studied.In this paper,it is first to construct an environmental map for the global path planning,and use the grid method to construct the environment map;The traditional ant colony algorithm in the global path planning has a slow convergence rate and poor path quality when planning the path,this paper presents an improved ant colony algorithm.The algorithm first introduces an obstacle rejection weight and the new heuristic factor to the path selection probability,which improves the ability of obstacle avoidance path and increase the diversity of path selection.Then,by adjusting the local and global pheromone updating method,which improves the quality of convergence and efficiency and the path search algorithm.In order to prevent the algorithm from stagnation,the new path is obtained by using the cross operation,which makes the global search of the algorithm more efficient.The simulation results show that the performance of the improved algorithm is superior to other algorithms.Then,according to the local path planning for mobile robot hybrid path planning,this paper uses the rolling window method for local path planning and uses a new local target point selection method to solve the local local target points,the local target will make the robot local planning into a local minima.And the motion trajectory of linear prediction model dynamic obstacle and obstacle avoidance strategy are analyzed,and puts forward a dynamic programming based on the rolling window.By adding temporary static and dynamic obstacles in the simulation environment,the mobile robot can effectively avoid in time.According to the global and local path planning shortcomings,proposes an improved ant colony algorithm combined with rolling window algorithm hybrid path planning algorithm,the hybrid algorithm using improved ant colony algorithm for planning in the global static environment to find a global optimal path.Then,the mobile robot walks on the best global path and using the rolling window method for local obstacle avoidance.In the meantime,to predict the trajectory of dynamic obstacle avoidance behavior to make corresponding and ensure that the mobile robot can be real-time to avoid dynamic obstacles.When the mobile robot successfully avoid obstacles,along the original global optimal path planning good driving.The simulation results show that the mobile robot can be used to predict and avoid the obstacles in the static environment and the dynamic obstacles.