Research On Indoor Mobile Robot Navigation Technology Based On BIM

With the development of science and technology,the applications of mobile robots continue to expand.Different from traditional industrial robots,indoor mobile robots face more complex tasks and environments,which presents greater technical challenges for their autonomous navigation.The Simultaneous Localization and Mapping(SLAM)method is the mainstream method to solve environment perception,localization,and navigation problems in the field of mobile robotics.However,this method faces issues such as high computational costs and long acquisition times for prior information,making it unsuitable for large indoor environments with complex structures.This thesis aims to solve this problem,and studies an indoor mobile robot navigation technology based on Building Information Modeling(BIM),which utilizes BIM information to construct indoor maps,perform localization,and plan paths for mobile robots.The research of this thesis is outlined as follows:Firstly,this thesis studies the indoor mobile robot navigation technology and the kinematics model of mobile robot,analyzes the application shortcomings of traditional technology.The feasibility of using BIM-based navigation technology is then explained,and a BIM-based mobile robot navigation system architecture is proposed.The indoor mapping process using laser SLAM is studied,and a multi-level map was constructed by parsing and extracting BIM information based on IFC.Secondly,the Monte Carlo localization(MCL)algorithm and its adaptive variants are derived based on the principles of particle filtering.Aiming at the problems of slow particle swarm convergence and low point cloud alignment,an AMCL algorithm for fusing visual information is proposed based on the node information provided by BIM.Scanning matching is introduced to optimize point cloud alignment.Then,this thesis proposes a path security improvement method based on BIM and an adaptive coefficient describing the complexity of the environment into the heuristic function to solve the low efficiency and lack of safety considerations in traditional A* algorithms.The simulation results show that the search time of the improved A* algorithm is reduced by 65% compared with the traditional A* algorithm when the path length is similar.The improved A* algorithm is combined with the Timed Elastic Band(TEB)algorithm t to improve the local obstacle avoidance ability of the mobile robot.Finally,the ROS mobile robot with lidar and monocular camera is used to construct a map based on the actual environment’s BIM model,and indoor localization and path planning are performed based on the map to achieve mobile robot autonomous navigation.