Research On Path Planning Of Mobile Robot Based On Iterative A* Algorithm And Bug Algorithm

With the rapid development of science and technology,industrialization and automation construction,the application of robots has been further popularized.Autonomous mobile robots are now a hot field in the field of robot research,and path planning technology plays a very important role in the related research of mobile robots.The key role is also the basis for deeper applications and research on mobile robots.Although intelligent algorithms are emerging in an endless stream,many of which are also applied to the path planning of mobile robots,but there is no single path planning algorithm can meet the mobile robot in the face of all the changes of external environment,path planning for mobile robot technology research still has very important significance.Because a robot needs to rely on a map to describe its current environment information when it is moving,it is very important for a mobile robot to establish a reliable map.Therefore,this article uses a grid map based on the main representation method of the map in robotics.The model is used as the basis of the path planning research in this article to construct a map model of the real environment.For this part of the content,after theoretical analysis,the Gmapping algorithm is selected and the robot platform built by the laboratory is used to realize the construction of the grid map.In the path planning of mobile robots,this article mainly studies and analyzes the Bug algorithm and some improved A* algorithms.It is found that although these algorithms can plan better paths in a specific map environment,they can plan paths in other different spatial environments.There is still room for improvement.This paper proposes an improved algorithm of iterative A* algorithm and Bug algorithm,that is,when the robot is driving to the target position,it first judges whether the robot encounters an obstacle,and when the robot encounters an obstacle,the improved A* algorithm is used for path search.When the robot does not encounter obstacles,the Bug2 algorithm is used to search for the path,and the advantages of the two algorithms are combined to plan the path.At the same time,it also solves the problem of the Bug2 algorithm judging that the target point is unreachable;Then,redundant points are eliminated and smoothed on the planned path to further optimize the path.Finally,this paper uses MATLAB R2014 b to perform simulation verification in the constructed raster map environment and other map environments.The experimental results show that the improved algorithm in this paper is better than the Dijkstra algorithm,the traditional A* algorithm and the two improved A* algorithms in the number of access nodes and search time.And the path length has been greatly improved,and the planned path is better.At the same time,the improved algorithm in this paper also has good applicability,stability and feasibility in other different environment maps.