基于无损检测匹配和地面约束的复杂环境下地面机器人三维SLAM

IF 1.9 4区 计算机科学 Q3 ENGINEERING, INDUSTRIAL
Yilong Jiang, Ting Wang, Shiliang Shao, Lebing Wang
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引用次数: 1

摘要

目的在大规模环境和非结构化场景下,传统的激光探测与测距(LiDAR)同步定位与制图(SLAM)算法的精度和鲁棒性降低,甚至可能完全无效。为了克服这些问题,本研究旨在提出一种基于地面移动机器人的3D LiDAR SLAM方法,该方法利用3D LiDAR融合惯性测量单元(IMU)建立环境地图并实现实时定位。设计/方法/方法首先,我们使用基于局部地图的正态分布变换(NDT)算法和相应的运动预测模型在前端进行点云配准。其次,将点云特征与IMU角度约束、地面约束和重力约束紧密耦合,在后端进行基于图的优化。随后,通过增加闭环检测来减小累积误差。使用包含室内和室外场景的公共数据集对该算法进行了测试。结果表明,该算法具有较高的精度和鲁棒性。为了提高SLAM的精度和鲁棒性,本文提出的方法在前端引入无损检测算法,在后端设计地面约束和重力约束。将该方法应用于复杂环境下的地面移动机器人实验,取得了满意的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3D SLAM based on NDT matching and ground constraints for ground robots in complex environments
Purpose In large-scale environments and unstructured scenarios, the accuracy and robustness of traditional light detection and ranging (LiDAR) simultaneous localization and mapping (SLAM) algorithms are reduced, and the algorithms might even be completely ineffective. To overcome these problems, this study aims to propose a 3D LiDAR SLAM method for ground-based mobile robots, which uses a 3D LiDAR fusion inertial measurement unit (IMU) to establish an environment map and realize real-time localization. Design/methodology/approach First, we use a normal distributions transform (NDT) algorithm based on a local map with a corresponding motion prediction model for point cloud registration in the front-end. Next, point cloud features are tightly coupled with IMU angle constraints, ground constraints and gravity constraints for graph-based optimization in the back-end. Subsequently, the cumulative error is reduced by adding loop closure detection. Findings The algorithm is tested using a public data set containing indoor and outdoor scenarios. The results confirm that the proposed algorithm has high accuracy and robustness. Originality/value To improve the accuracy and robustness of SLAM, this method proposed in the paper introduced the NDT algorithm in the front-end and designed ground constraints and gravity constraints in the back-end. The proposed method has a satisfactory performance when applied to ground-based mobile robots in complex environments experiments.
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来源期刊
CiteScore
4.50
自引率
16.70%
发文量
86
审稿时长
5.7 months
期刊介绍: Industrial Robot publishes peer reviewed research articles, technology reviews and specially commissioned case studies. Each issue includes high quality content covering all aspects of robotic technology, and reflecting the most interesting and strategically important research and development activities from around the world. The journal’s policy of not publishing work that has only been tested in simulation means that only the very best and most practical research articles are included. This ensures that the material that is published has real relevance and value for commercial manufacturing and research organizations. Industrial Robot''s coverage includes, but is not restricted to: Automatic assembly Flexible manufacturing Programming optimisation Simulation and offline programming Service robots Autonomous robots Swarm intelligence Humanoid robots Prosthetics and exoskeletons Machine intelligence Military robots Underwater and aerial robots Cooperative robots Flexible grippers and tactile sensing Robot vision Teleoperation Mobile robots Search and rescue robots Robot welding Collision avoidance Robotic machining Surgical robots Call for Papers 2020 AI for Autonomous Unmanned Systems Agricultural Robot Brain-Computer Interfaces for Human-Robot Interaction Cooperative Robots Robots for Environmental Monitoring Rehabilitation Robots Wearable Robotics/Exoskeletons.
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