Research On Path Planning And Obstacle Avoidance Algorithm Of Mobile Robot

With the rapid development of science and technology,mobile robots have been widely used in industry,military,service and other industries.Path planning technology is one of the key technologies for mobile robot to realize intelligence.In order to meet the growing work needs of mobile robot,the research on mobile robot path planning algorithm is of great significance.Therefore,this paper takes the two wheel differential mobile robot as the research object.The research content is to improve the comprehensive performance of the global path planning algorithm in the static environment and the obstacle avoidance ability of the robot in the dynamic environment.Firstly,based on the principle of kinematics,this paper establishes the motion model of two wheeled differential mobile robot,analyzes the common map construction methods and their advantages and disadvantages,and introduces the principles of several classical path planning algorithms.Secondly,a multi factor A~* ant colony algorithm is proposed to solve the problems of too many iterative stability times and single solution goal of ant colony algorithm in global path planning in static environment.The grid method is used to build the robot working map and specify the travel mode to ensure the safety of the route;The initial pheromone of the path setting map obtained by the improved A~*algorithm is used to reduce the blindness of the early search of the ant colony algorithm;The number of turns and the degree of turbulence of the path are introduced as the consideration factors for ant colony to select the road,so as to avoid taking distance as the sole purpose of path planning,so as to meet the actual working needs of the robot;The dynamic adjustment factor of heuristic function is introduced to weaken the function of heuristic function with the increase of iteration times,so as to avoid ant colony algorithm falling into local optimization.Simulation results show that the number of iterations of the improved algorithm is reduced,and the path comprehensive performance index is better than the comparison literature algorithm and the traditional algorithm.Then,aiming at the local path planning problem of mobile robot in dynamic environment,an improved artificial potential field method is proposed in this paper.In order to solve the target unreachable problem of the artificial potential field method,the distance between the mobile robot and the target point is added to the repulsion potential field function to minimize the potential field at the target point;In order to solve the local minimum problem of the artificial potential field method,the idea of simulated annealing is used to help the mobile robot escape from the local minimum;In order to solve the obstacle avoidance problem of dynamic obstacles by artificial potential field method,based on the relative velocity between mobile robot and dynamic obstacles,the velocity potential field function is established to improve the dynamic obstacle avoidance ability of robot.Simulation results show that the improved artificial potential field method can effectively solve the problem of target unreachable and local minimum,and has strong obstacle avoidance ability in dynamic environment.In random environment,compared with literature algorithms,the number of iterations and path length are reduced.Finally,taking the two wheeled differential mobile robot as the experimental object,this paper builds the ROS experimental platform,takes the A~* ant colony algorithm as the global path planner and the improved ant colony algorithm as the local path planner,which verifies the effectiveness and feasibility of the improved algorithm in the actual environment.