Research On Path Planning Algorithm Based On Mobile Robot

With the rapid development of science and technology,robots have been widely used in many fields.As an intelligent mobile robot integrating environmental perception,dynamic decision-making and planning,behavior control and execution,it plays an important role in the development of society.Autonomous navigation is the basic function of mobile robots and the prerequisite for completing obstacle avoidance tasks.Therefore,how to efficiently plan a safe,smooth and globally optimal path is an important issue in the field of mobile robot path planning.Today ’s working environment has become more complex,filled with many uncontrollable unknown dynamic obstacles,which has higher requirements for the path planning ability of mobile robots.In the path planning of mobile robots,the effectiveness,real-time performance of the algorithm and the ability to avoid unknown obstacles determine whether the mobile robot can effectively complete the task.In this paper,the twowheel differential mobile robot is taken as the research object.The effectiveness,safety and real-time performance of the global path planning algorithm of the mobile robot in the static environment and the local path planning algorithm in the environment with unknown dynamic obstacles are studied.The specific research contents are as follows :(1)The traditional A~* algorithm and its principle are analyzed.Aiming at the problem of low search efficiency of traditional A~* algorithm in large size and complex environment,an improved method of adaptive dynamic weighting of heuristic function according to the proportion of obstacles on the map is proposed to dynamically modify the heuristic function.Aiming at the problems of many search nodes and large memory consumption in traditional A~* algorithm,an improved method based on jump point search strategy is proposed,which reduces the search area and improves the search efficiency of the algorithm.Aiming at the problem that the actual volume of obstacles and mobile robots will increase the collision risk and reduce the safety performance of mobile robots,a method of intelligent obstacle expansion is proposed to keep a safe distance between the improved path and obstacles,reduce the collision risk,improve the safety performance and reduce the map space occupancy.Experiments in different environments show that the improved A~* algorithm has shorter running time,lower risk coefficient,fewer evaluation nodes and better comprehensive performance.(2)Aiming at the problem that global path planning is difficult to solve unknown obstacles in dynamic environment,an improved algorithm combining improved A~* algorithm and dynamic window method is proposed.An improved target azimuth evaluation function is constructed with global path information as reference.The extracted key path points are used as the process target points of the improved algorithm,which improves the global optimality of the algorithm.The experimental results show that the improved algorithm combining the improved A~* algorithm and the dynamic window method can effectively track the global path,give full play to the real-time performance of local path planning,and ensure the optimality of the path.(3)The simulation experiment platform of mobile robot based on ROS is built.The static and dynamic simulation experiment environment is created by using Gazebo simulation software,and the current simulation environment is mapped by using Rviz visualization tool and SLAM.In different simulation environments,the fusion algorithm of improved A~*algorithm and dynamic window method is verified.The experimental results verify the effectiveness and feasibility of the algorithm.