Research On Global Path Planning For Mobile Robot

Mobile robot is an important research achievement in the human science.In recent years,mobile robot comes into the spotlight along with the higher pursuit of quality of life.It can not only explore fields that people can't reach,but also help people to do boring and heavy work.Path planning is the primary problem in the research of mobile robots.Only by allowing robots to walk along on a planned path can the task be completed successfully.Therefore,the paper studies the existing path planning methods of mobile robot,analyzing the advantages and disadvantages of each method,the problems which exist in the specific methods are studied,the reasons are found out and the corresponding improvement methods are put forward.The main work of this article is as follows:1 In this paper,using the grid map modeling of the environment,because the grid size directly affects the accuracy of path planning of mobile robot,So the grid factor is designed first when the grid map is built,and then establish the obstacle coordinates and obstacle information is translated into the environment coordinates,the most determined after eight mobile robot exploration in the direction in the grid map.2 The paper targets at slow convergence speed and poor path quality in mobile robot global path planning using ant colony algorithm and A* algorithm,Fast Ant Colony Algorithm and Weighted detection A* algorithm are adopted to improve it.In Fast Ant Colony Algorithm,tendency exploration is adopted and pheromone coefficient is optimized,finally the redundant path is removed.The Weighted detection A* algorithm turns the heuristic function into a function which is determined the distance and angle,and the separated nodes are the detected by line of sight detection.Since these two algorithms are based on raster map for simulation experiments,paths of two algorithms are compared in the same environment,and do further research on the adaptability of each algorithm.3 In order to allow the mobile robot complete the work in any complex environment,the global path planning of mobile robot based on S-RRT algorithm is proposed in this paper.The convergence factor and smooth processing are added to the S-RRT algorithm,and the problem that the search is easy to fall into local minimum.The experimental results show that the algorithm not only inherits all the advantages of the original RRT algorithm,but also improves the speed of algorithm convergence,and makes the planned mobile robot path tend to the best path.Finally,in order to verify the low requirements of the S-RRT algorithm to the environment and the suitable of various environments,the path planning of mobile robots under different environmental maps is carried out.