同时定位和映射
激光雷达
运动学
机器人
计算机科学
惯性参考系
惯性测量装置
步行机器人
人工智能
计算机视觉
移动机器人
遥感
地质学
物理
量子力学
经典力学
作者
Yan Wen,Ying Li,Qingyi Shang,Chaoyang Jiang,Hongyu Hou,Hui Liu,Yifan Zhang,Lijin Han
标识
DOI:10.1109/lra.2024.3521184
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.
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