The Research On Simultaneous Localization And Map Construction On Of Mobile Robot Based On ROS

With the advent of the era of industrialization 4.0,robots have been involved in many fields such as industry,military,and medical care.Researchers and application developers are increasingly aware of the importance of mobile robot technology.Simultaneous Location Mapping(SLAM)has become a research hotspot.The autonomous navigation and path planning functions of robots must rely on SLAM technology,so the application of SLAM is of great significance.In view of the advantages of the robot operation system(ROS)in code reuse and real-time performance,the simultaneous positioning of ROS-based mobile robots and map construction are studied in the following aspects:Firstly,the basic principles and methods of SLAM for mobile robots are described.The mathematical models are used to describe the SLAM movement model and observation model.By comparing the three methods of the environmental map representation in the SLAM problem of mobile robots,the grid map is used to represent the robot's acquisition.Environmental maps and the use of particle filtering to achieve autonomous robot positioning.Then,based on an information fusion system consisting of a laser range finder,odometer,gyroscope,optical encoder,acquisition control board,and core control board,an upper computer interface written in C++ and Python was used as the indoor display.Composition system.The SLAM experiment and path planning experiment of the office environment were completed on the robot.Finally,a Kinect sensor is added to the platform to collect color images and depth images of the office environment,feature matching is performed on any two adjacent color images,and the position of the corresponding feature point pair in the three-dimensional space is acquired by combining the depth image data,and the nearest The neighborhood algorithm iteratively solves the rigid body transformation matrix to complete the accurate registration and build a three-dimensional map of the office environment.The experimental results show that the indoor composition system constructed in this paper can efficiently collect environmental information and obtain the dense and accurate feature points of the map.The feature information in the vertical direction can be accurately obtained in the three-dimensional map,which has certain reference value for SLAM research.There are 34 figures and 67 Reference in this paper.