广东工业大学学报2026，Vol.43Issue(3)：106-115,10.DOI:10.12052/gdutxb.250136
基于因子图优化的船舶作业车间履带式打磨机器人定位算法
Factor Graph Optimization-based Localization Algorithm for Tracked Sanding Robots in Marine Job Shops
摘要
Abstract
Aiming at the problems of dynamic environmental changes,a lack of natural environmental characteristics,and the dependence on the number of reflector columns of the traditional trilateral localization algorithm based on reflective columns under the ship segmentation operation environment,an improved positioning strategy by introducing sensors such as Light Detection and Ranging,Inertial Measurement Unit(IMU),and odometer,and fusing multi-source sensor data is proposed.The algorithm fuses trilateral positioning with the iterative closest point(ICP)algorithm for point cloud matching for positioning and introduces a factor graph optimization framework to achieve multi-source data fusion.The experimental platform is built to carry out the localization test,and the static X/Y/heading localization error reaches 12.876 mm,4.273 mm and 0.000 3 rad respectively,and the X/Y/heading localization error under dynamic and complex conditions reaches 33.364 mm,16.95 mm and 0.026 3 rad respectively,which is better than the traditional method in terms of accuracy and robustness.The experimental results show that the proposed localization strategy reduces the static X/Y/heading localization error by more than 5.1%compared with the traditional trilateral localization and Kalman filtering,and reduces the dynamic complex X/Y/heading localization error by more than 14.5%.关键词
三边定位/激光雷达/迭代最近点/因子图优化/多源数据融合Key words
trilateral positioning/light detection and ranging/iterative closest point/factor graph optimization/multi-source data fusion分类
交通工程引用本文复制引用
王海龙,宴聪,梁杰,邓聪..基于因子图优化的船舶作业车间履带式打磨机器人定位算法[J].广东工业大学学报,2026,43(3):106-115,10.基金项目
广东省自然科学基金资助项目(2021A1515011839) （2021A1515011839）
