Research On Path Planning Methods For Cushioned Robots In Dynamic Environments

Path planning is a prerequisite for the normal operation of mobile robots,and it is one of the important contents in the field of mobile robot research.At present,some research results have been achieved on the issue of robot path planning.However,the existing research does not consider the optimality of mobile robot path planning and the safety of robot motion in a dynamic environment.To solve this problem,this thesis takes the cushion robot as the research object,and proposes a fusion algorithm based on the improved A* algorithm and the dynamic window method to study the path planning of the cushion robot in a dynamic environment.The main contents are as follows:A detailed analysis of the cushion robot system model is carried out,and the composition structure of the cushion robot system is introduced.The derivation process of the robot kinematics model is explained.By analyzing the established motion model,the trajectory of the robot and the conversion relationship between the global coordinate system and the local coordinate system are obtained.The global path planning of the cushion robot in a static environment is studied.The environmental information is introduced,and the construction of the environmental model based on the grid map is completed.The A* algorithm is used to solve the global path planning problem in a static environment.The traditional A* algorithm is improved to solve the limitations of the A* algorithm in terms of large amount of calculation and a large amount of redundancy in the calculation process.Experimental results show that the proposed improved A* algorithm can significantly improve the accuracy and search efficiency of the optimal path.The dynamic window method is used to solve the path planning of the cushion robot in a dynamic environment,and an evaluation model that considers the global optimal path is constructed to avoid the dynamic window algorithm from falling into the local optimal problem in the solution process;aiming at the shortcomings of using the improved A*algorithm and the dynamic window method in a dynamic environment,a fusion algorithm is proposed,and the working principle of the fusion algorithm is explained in detail.The experimental simulation results show that the fusion algorithm solves the limitations of using a single algorithm in a dynamic environment,thereby obtaining a shorter path.At the same time,the search efficiency is improved to meet the requirements of robot path planning in a dynamic environment.