Research On Path Planning Algorithm For Mobile Robots In Complex Environment

In the field of mobile robot research,path planning technology has always been a hot topic.Nowadays,the working environment of mobile robots is becoming more and more complex,and it is of great research significance and practical value to achieve safe and effective path planning as an important guarantee for them to accomplish various complex tasks.In this paper,the Rapidly-expanding Random Tree(RRT*)algorithm and the Dynamic Window Approach(DWA)are used to achieve path planning for mobile robots based on narrow and dense static and dynamic obstacle environments.(1)To address the problems of low efficiency of RRT* algorithm path planning in narrow and dense static obstacle environment,the existence of redundant nodes in the path and path non-smoothness,a static path planning algorithm based on bidirectional dynamic target bias RRT* is proposed.Firstly,the one-way random expansion of the RRT* algorithm is replaced by a two-way dynamic biased target expansion node,so that the generated path nodes have a clear direction and improve the planning efficiency of the algorithm;secondly,in order to optimize the path length,the greedy algorithm is used to remove the redundant nodes in the path,and a cubic Bessel curve is used to smooth the planned folded path,so as to generate a shorter and smoother path;finally Simulation experiments show the superiority of the proposed algorithm in terms of path planning efficiency and path quality.(2)To address the problem that the DWA algorithm cannot obtain the optimal path in the dynamic obstacle environment,a dynamic path planning algorithm incorporating improved RRT* and DWA is proposed.Firstly,by eliminating the dangerous nodes generated by the RRT* algorithm,the safety of the global path is ensured;secondly,in order to solve the problem that the DWA algorithm lacks the guidance of the global path resulting in a long path,by introducing the deviation evaluation function,the DWA algorithm is made to track the global optimal path planned by the improved RRT* algorithm,thus realizing the fusion of the RRT* algorithm and the DWA algorithm;finally,the simulation experiments show that the proposed fusion algorithm can effectively track the global optimal path in the dynamic environment,but the dynamic obstacle avoidance effect is poor.(3)To address the problem of the poor dynamic obstacle avoidance effect of the RRT*and DWA fusion algorithm in the dynamic obstacle environment,an improved RRT* and DWA dynamic path planning algorithm based on a new obstacle avoidance strategy is proposed.When an unknown obstacle appears on the global path,a secondary weight adjustment and path correction mechanism is designed to avoid the obstacle and return to the original optimal path in time by adjusting the weight of the DWA algorithm evaluation function twice;when a moving obstacle appears in the environment,a new safe dynamic obstacle avoidance strategy is designed to detect the danger distance in advance and drive away from the danger area safely by steering and accelerating.The final simulation experiments show that the proposed algorithm can ensure safe obstacle avoidance while tracking the global optimal path.