Wheel-Legged SLAM: Indoor LiDAR-Inertial SLAM Integrating Kinematic Model of Wheel-Legged Robots

被引:0
作者
Wen, Yan [1 ]
Li, Ying [1 ]
Shang, Qingyi [1 ]
Jiang, Chaoyang [1 ]
Hou, Hongyu [1 ]
Liu, Hui [1 ]
Zhang, Yifan [1 ]
Han, Lijin [1 ]
机构
[1] Beijing Inst Technol, Sch Mech Engn, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
Robots; Simultaneous localization and mapping; Kinematics; Robot sensing systems; Laser radar; Location awareness; Optimization; Legged locomotion; Estimation; Accuracy; SLAM; wheel-legged robots; multi-sensor fusion; kinematic model; indoors;
D O I
10.1109/LRA.2024.3521184
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
SLAM is the key technique for localization and surrounding perception in indoor environments. However, the dynamic posture adjustments of wheel-legged robots cast new challenges that affect the accuracy of localization. Therefore, this letter presents the Wheel-Legged SLAM, a novel indoor SLAM method for wheel-legged robots. The contributions of this research include the effective fusion of a dual LiDAR system for enhancing the robustness in degenerative indoor settings, the vertical correction factor for reducing the Z-axis drift and the gravity re-estimation factor for improving the pose accuracy. Extensive experiments in various indoor environments, including factories, corridors, and underground garages, demonstrate the robustness and accuracy of the proposed approach. The results indicate that the method proposed in this letter enhances the robustness of the LiDAR-inertial SLAM indoors, significantly improves the localization accuracy and reduces accumulative errors for the wheel-legged robot.
引用
收藏
页码:1273 / 1280
页数:8
相关论文
共 20 条
[1]  
Dellaert F., 2012, Tech Rep. 2
[2]   Square root SAM: Simultaneous localization and mapping via square root information smoothing [J].
Dellaert, Frank ;
Kaess, Michael .
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 2006, 25 (12) :1181-1203
[3]  
Hartley R, 2018, IEEE INT CONF ROBOT, P4422
[4]  
Jiang XY, 2016, IEEE ICARM 2016 - 2016 INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS AND MECHATRONICS (ICARM), P107, DOI 10.1109/ICARM.2016.7606903
[5]   iSAM: Incremental Smoothing and Mapping [J].
Kaess, Michael ;
Ranganathan, Ananth ;
Dellaert, Frank .
IEEE TRANSACTIONS ON ROBOTICS, 2008, 24 (06) :1365-1378
[6]  
Khairuddin AR, 2015, PROCEEDINGS 5TH IEEE INTERNATIONAL CONFERENCE ON CONTROL SYSTEM, COMPUTING AND ENGINEERING (ICCSCE 2015), P85, DOI 10.1109/ICCSCE.2015.7482163
[7]   Periodic SLAM: Using Cyclic Constraints to Improve the Performance of Visual-Inertial SLAM on Legged Robots [J].
Kumar, Hans ;
Payne, J. Joe ;
Travers, Matthew ;
Johnson, Aaron M. ;
Choset, Howie .
2022 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, ICRA 2022, 2022, :9477-9483
[8]   An Intensity-Augmented LiDAR-Inertial SLAM for Solid-State LiDARs in Degenerated Environments [J].
Li, Haisong ;
Tian, Bailing ;
Shen, Hongming ;
Lu, Junjie .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 71
[9]  
Li TW, 2017, 2017 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (IEEE ROBIO 2017), P2496, DOI 10.1109/ROBIO.2017.8324795
[10]  
Schnipke E., 2015, Paper 0715