Research On Path Planning And Obstacle Avoidance Algorithm Of Mobile Robot In Dynamic Environment

With the continuous development of mobile robot technology,its application scenarios are becoming more and more extensive.Wheeled mobile robots not only have the characteristics of flexible movement,fast speed and high efficiency,but also are suitable for operations in complex dynamic environments.Path planning is the first of the normal operations of mobile robots.Through the expansion and promotion of wheeled mobile robot applications,its operating environment is complicated,the operating objects are vertical,the operating performance is high quality,and the operating efficiency is highly efficient.Path planning and static and dynamic obstacle avoidance are the main problem of its application,with high-quality planning and obstacle avoidance algorithm research results,has always been a research hotspot.Here,the wheeled mobile robot is used as the research object,the improved A *(A-Star)algorithm,the artificial potential field method and the hybrid algorithm are used to realize the path of the wheeled mobile robot in a dynamic environment.The main research contents are as follows:Firstly,the nonholonomic system and nonholonomic constraints of the wheeled mobile robot are analyzed in detail,and the kinematic model of the wheeled mobile robot is established.In the multi-objective operating environment,for the global path planning problem of wheeled mobile robots,the improved A * algorithm and the target cost function are used to determine the priority of all target points in the environment,and the target points with the highest current priority are searched in turn to achieve a single search can plan a safe path to reach multiple target points.At the same time,based on the nonholonomic constraints of the wheeled mobile robot,an adaptive arc optimization algorithm is used to optimize the global path.In view of the problem that the traditional A* search algorithm uses a fixed search step and leads to poor search flexibility,this paper gives a weighted obstacle step adjustment algorithm,which enables the search step size to be adjusted adaptively according to the number of surrounding obstacles.It improves search flexibility.The simulation results show that the improved A * algorithm has a shorter path and a smaller turning angle than the traditional A * algorithm,which improves the effectiveness and practicability of the search path of the wheeled mobile robot.Secondly,for the problem of local path planning for wheeled mobile robots in dynamic environments,the conventional artificial potential field method is improved to overcome the local optimization problems of the traditional artificial potential field method.Aiming at the poor target reachability and low index of the artificial potential field method,based on constraints such as the distance between the mobile robot and the target point and the mobile robot's own acceleration,an improved repulsion function method is given to improve the target's reachability.Aiming at the local oscillation problem of the artificial potential field method,the escape force method is given,which not only eliminates the local oscillation in the algorithm search process,but also realizes the automatic search of feasible channels,and solves the minimum trap problem of the traditional artificial potential field method.The simulation results show that the improved artificial potential field method is more flexible and more reliable than the traditional artificial potential field method.Finally,for the path planning of wheeled mobile robots in a dynamic environment,a hybrid algorithm combining global path planning and local path planning algorithms is proposed to complete the path planning of wheeled mobile robots.Considering the shortcomings of the artificial potential field method in sub-optimal local path planning,the dynamic window method is improved,using the established kinematic model of the wheeled mobile robot and considering the non-holonomic constraints of the mobile robot,to avoid dynamic obstacles and achieve dynamic path planning.The tracking method of preview target deviation angle is used to track the dynamic target point,which successfully captures the dynamic target point and improves the efficiency of algorithm search.Simulation experiments are carried out,and the results show that the proposed hybrid algorithm is feasible and practical for path search in dynamic environments.