Research on Path Planning of Intelligent Warehouse Mobile Robot based on Meta-heuristic Algorithm

In multi-dimensional space, the sample-based motion planning method, that is, the rapid expansion of random tree RRT, has the advantages of probabilistic integrity, fast exploration speed, and no need to map obstacles from the task space to the configuration space. However, the traditional RRT algorithm has some shortcomings, such as low convergence speed in the process of random tree search, unstable orientation, slow tracking speed in complex environments, too many unnecessary nodes, and obstacle constraints, so that the path generated by random sampling contains many unnecessary breakpoints, which leads to the path is not smooth and discontinuous. Therefore, we need to develop an improved RRT algorithm to achieve the purpose of improving the convergence speed of the algorithm while avoiding falling into the local minimum and finally plan an efficient path.