Research Of An Improving HAA Algorithm For Mobile Robot Path Planning

Path planning is a key technology of robots,with the high prosperity of artificial intelligence,which is extensively implemented in the fields of daily life,safeguarding country,resource development and detection.At present,most of the research on path planning is based on the study of algorithms,however,each algorithm has dual characteristics,which leads it still an important study to choose the appropriate path planning algorithm based on different scenarios to complete path planning and meet specific task requirements.At the same time,there are some limitations for the path planning of a single algorithm in complex environments,therefore,this paper makes relevant improvements for the problems that the A*algorithm is prone to generate redundant nodes,and the artificial potential field method is easy to fall into local optimization or unattainable goal.Then hybrid the improved A* algorithm and the improved artificial potential field method constitute HAA to plan the route in the scenes with moving obstacles.The specific research content is summarized below:1.The path planning of the A* algorithm under the fully known scenario information is studied,for dealing with the condition that the traditional A*algorithm is prone to generate redundant nodes in the process of path planning,not only the distance but also the obstacle avoidance,smoothing,slope,and steering angle are considered in the heuristic function,the redundant nodes can be reduced and the path can be planned in a shorter possible time.Eventually,contrasting with the other algorithm further to confirm that the improved algorithm possesses excellent performance.2.To study the path planning problem in the circumstance with moving obstacles,the artificial potential field method is first applied to implement path planning in the local area with moving obstacles,through the construction principle of this method,the reasons for the local optimal and unreachable goals are analyzed,then the distance threshold and gravity guidance factor are introduced for related improvement,and the dynamic obstacle avoidance ability of the improved algorithm is verified by simulation.Facing global path searching in circumstances with moving obstacles,the HAA algorithm is proposed.Firstly,walking along the complete path planned by the improved A* algorithm,the trajectory of dynamic obstacles is predicted by the autoregressive model when dynamic obstacles are detected in the detection range of the robot,and regarding these trajectories as static obstacles.meanwhile,the global path node within the detection range is regarded as the local target point,then combined with obstacle information,the improved artificial potential field method completes local dynamic obstacle avoidance and returns to the global path node.Finally,the simulation demonstrates that the hybrid algorithm can find a global path and dodge moving obstacles.