Abstract: The path planning problem is a vital problem in the field of mobile robots and is the basis for the development of smart factories.Rapidly-expanding random tree algorithm (RRT algorithm) is widely used in path planning because of its excellent solving performance.Aiming at the problem of low execution efficiency and poor path repeatability of the RRT algorithm when faced with complex maps,a plant growth guidance based RRT path planning algorithm (PG-RRT algorithm) for mobile robot was proposed to improve the stability and efficiency of path optimization.By using three principles followed by plant growth (Phototropism,Obstacle influence characteristics and Negative geotropism),combing variable step technique and inflation technique,the PG dilation guide field used for RRT algorithm can be obtained.Finally,the ideal path is obtained by using the RRT algorithm with random sampling characteristics.Abundant simulations show that the PG-RRT algorithm reduces the number of iterations and obtains better path distance compared to the traditional RRT algorithm and the single PG algorithm.It is noteworthy that the search efficiency of the presented path planning algorithm is improved compared with the A^* algorithm.Moreover,the actual vehicle test of robot verifies the practicability of the PG-RRT algorithm.

Key words: Path planning, Plant growth, Rapidly-expanding random tree algorithm