Research On Positioning And Navigation Methods Of Indoor Mobile Robots

Time has come to the third decade of the 21 st century.With the requirements of Made in China 2025,the development of unmanned driving is in full swing.Unmanned vehicles can be regarded as a four-wheeled mobile robot.This key technology is basically born out of mobile robots.Indoor mobile robots are an important branch of mobile robots and have always been a research hotspot at home and abroad.In order to enable indoor mobile robots to perform autonomous exploration more intelligently,this article conducts in-depth research on the positioning and navigation technology of indoor mobile robots.The main tasks are as follows:(1)Design the basic framework of the indoor mobile robot,select various types of hardware and build an indoor mobile robot platform,and develop based on ROS to realize the autonomous positioning and navigation functions of the indoor mobile robot.(2)Analyzed the more common and widely used SLAM algorithms.In order to solve the problem of incomplete map construction information and frequent drift phenomenon in the pure lidar scheme,a kinematic constraint-based lidar and IMU fusion is proposed the algorithm uses the Extended Kalman Filter(EKF)method to fuse the odometer information with the observation data to achieve more accurate positioning and greatly reduce the drift phenomenon.(3)Research the navigation problem when the map is known,focusing on the Rapidly-exploring Random Tree(RRT)algorithm.An improved algorithm is proposed.Through the dynamic constraints of the indoor mobile robot,the sampling area is limited when the RRT algorithm expands the node,and the nearest node is redefined,and finally smoothed by the Bezier curve to generate a safe,smooth,and satisfying The path required by the kinematics of the indoor mobile robot.(4)Set up an indoor experimental environment to test the positioning and navigation of the indoor mobile robot platform to verify the work done in this article.The experimental results show that the indoor mobile robot platform built in this paper has a significant improvement in positioning accuracy compared with a single lidar sensor,and the mapping is more stable;the navigation function can also operate normally,realizing the autonomous exploration function of the indoor mobile robot.At the same time,the overall experiment also verified the effectiveness,robustness and adaptability of the algorithm.