Research On Path Planning Algorithm Of Mobile Robot In Dynamic Environment

With the rapid development of the new generation of information technology,the market demand of mobile robot is increasing.At the same time,its application scenarios are becoming more and more extensive,and the requirements for robot positioning,planning and control are increasing.Focusing on the problem of path planning,this paper improves the shortcomings of three algorithms in global path planning and local path planning to improve the adaptability of mobile robot in dynamic environment.First of all,for the Rapidly exploring random tree(RRT)algorithm in a static environment,randomly selecting sampling points and expanding tree nodes does not consider the shortage of robot kinematic constraints,adopting the target bias method and constraining the steering angle of the robot to improve The sampling point selection method enhances the smoothness of the path.Aiming at the problem that when unknown obstacles block the planned path,the initial algorithm discards the historical nodes,rebuilds the random tree,and increases the amount of calculation.The RE-RRT(Replan-RRT)algorithm is proposed.Utilize,speed up the algorithm to re-search for feasible paths.The simulation results show that the improved algorithm has better path optimization efficiency and the ability to deal with unknown obstacles.Secondly,for the path planning problem of wheeled mobile robot in dynamic environment,a hybrid algorithm combining global path planning and local path planning algorithm is proposed.Aiming at the problem that the informed RRT * algorithm uses fixed step size to expand the random tree,which has poor flexibility,when expanding the random tree,the inner angle of the triangle is calculated according to the target point,sampling point and nearest parent node,and the step size is adjusted adaptively.At the same time,corridor constraint and time redistribution method are used to optimize the path to make the path meet the constraints of robot linear velocity and linear acceleration.The local extremum problem of the traditional artificial potential field method is solved by improving the artificial potential field method and adding global path sub target points.Simulation results show that the proposed algorithm is more feasible in dynamic environment.Finally,since the path obtained by the artificial potential field method is not the optimal solution in the dynamic environment,the dynamic window method considering the kinematic constraints of the robot is selected to realize the path planning task of the mobile robot in the dynamic environment.The problem that the robot falls into local minimum is solved by adding the incremental subfunction of robot travel distance and the distance subfunction from the robot to the target point.At the same time,considering the relationship between the relative speed and distance between the robot and dynamic obstacles,a fuzzy controller is designed to adjust the weight of the trajectory evaluation function in real time to enhance the ability of the robot to avoid obstacles dynamically.Simulation results show that the proposed algorithm can effectively avoid dynamic obstacles,and the change frequency of robot linear velocity and angular velocity is small,and the path solution result is better.