Path planning of mobile robot based on multi-sensor information fusion

Mobile robot is a very important branch of robotics. In practice, the performance of mobile robot is required to be higher and higher. It is required that mobile robot can adapt to different complex environments through its own intelligent system to achieve the established functional goals. Compared with traditional path planning with single sensor information, Kalman filter is used to fuse multi-sensor information, and path planning method based on improved dynamic artificial potential field method is studied. Using the improved dynamic artificial potential field method, the robot can also achieve optimal path planning and obstacle avoidance in complex dynamic environment. The simulation results show that the proposed algorithm is feasible.