基于UWB融合定位的室内自动泊车系统设计与国产化验证OA

To address the problems of low positioning accuracy and difficult parking in indoor parking garages,an IoT-based autonomous parking system enabled by ultra-wideband(UWB)cooperative localization was developed.The system adopted a"infrastructure-vehicle"distributed architecture built on robot operating system 2(ROS2),supporting multi-vehicle management and global trajectory distribution.To improve UWB stability under non-line-of-sight(NLOS)and multipath conditions,a multi-stage fusion method was proposed,consisting of ranging preprocessing,spherical position-ing,and an improved adaptive extended Kalman filter(IAEKF).For planning and control,feasible trajectories were gener-ated by integrating an improved A* algorithm with smooth curve refinement,and a credibility-aware model predictive control(MPC)strategy was introduced to enhance tracking robustness under fluctuating localization quality.Experimen-tal results showed that the proposed system outperforms five localization methods in both positioning accuracy and con-trol robustness in complex environments.Moreover,with the proposed fusion algorithm applied to the domestic UWB chip MK8000,the overall performance approached that of systems based on the DW1000 chip,demonstrating the feasibil-ity of a low-cost and domestically deployable autonomous parking solution.