Path Planning Research For Indoor Autonomous Mobile Robot

With the development of public services, warehouse logistics, adventure rescue, medical care and other industries, autonomous navigation mobile robot is facing a huge applicatio n requirements. More and more complex environment puts forward higher requirements for mobile robot navigation technology, and path planning technology is one of the key technologies for mobile robot navigation. Path planning involves the problems of obstacle avoidance, optimization and map building, while it requirements high real-time performance and robustness. Currently, there is still no single path planning method can solve those problems at the same time, therefore, the study for path planning has theoretical and practical significa nce. This paper studies the path planning method of indoor mobile robot taking Pioneer3-DX robot as the research object, and proposes new methods to solve the path planning problem.Path planning methods can be divided into global path planning and local path planning, based on the environment information grasped by the mobile robot. A-star algorithm is a heuristic and global path planning algorithm. Combining two independent drive characterist ics of Pioneer3-DX mobile robot, this paper optimizes the grid map, heuristic function, search strategies, evaluation function and turning corners of A-star method, which can improve the path planning’s performance of obstacle avoidance, timeliness and safety. The APF(artificial potential field) is a local path planning method. This paper analyzes the traditional APF’s problems of GNRON, local minima and lacking global optimization, and optimizes it by improved FIRAS function, filling potential field and regression search, which can improve the path planning’s performance of timeliness and robustness. For the reason that a single path planning algorithm can’t meet the needs of complex environments, this paper proposes a new hybrid path planning method based on improved A-star algorithm and improved APF algorit hm, which can improve the path planning’s performance in global optimization, obstacle avoidance and robustness. This paper verifies the effectiveness and feasibility of the new methods by simulations and experiments on the Pioneer3-DX mobile robot platform.