ER‐Mapping: An extrinsic robust coloured mapping system using residual evaluation and selection  

作　　者：Changjian Jiang Zeyu Wan Ruilan Gao Yu Zhang 

机构地区：[1]State Key Laboratory of Industrial Control Technology,College of Control Science and Engineering,Zhejiang University,Hangzhou,China [2]Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province,Hangzhou,China

出　　处：《IET Cyber-Systems and Robotics》2024年第2期97-108,共12页智能系统与机器人（英文）

基　　金：This work was supported by STI 2030‐Major Projects No.2021ZD0201403,in part by NSFC 62088101 Autonomous Intelligent Unmanned Systems.

摘　　要：The colour-enhanced point cloud map is increasingly being employed in fields such as robotics,3D reconstruction and virtual reality.The authors propose ER-Mapping(Extrinsic Robust coloured Mapping system using residual evaluation and selection).ER-Mapping consists of two components:the simultaneous localisation and mapping(SLAM)subsystem and the colouring subsystem.The SLAM subsystem reconstructs the geometric structure,where it employs a dynamic threshold-based residual selection in LiDAR-inertial odometry to improve mapping accuracy.On the other hand,the col-ouring subsystem focuses on recovering texture information from input images and innovatively utilises 3D–2D feature selection and optimisation methods,eliminating the need for strict hardware time synchronisation and highly accurate extrinsic parameters.Experiments were conducted in both indoor and outdoor environments.The results demonstrate that our system can enhance accuracy,reduce computational costs and achieve extrinsic robustness.

关 键 词：robot vision sensor fusion simultaneous localisation and mapping(robots) 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] TP391.41[自动化与计算机技术—控制科学与工程]