LIFNS: Design of a novel Lidar-IMU fusion navigation system for AGVs in smart factories

Yiduo Li, Peiqing Li, Qipeng Li, Xinzhao Wu, Zhuoran Li
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Abstract

Traditional Automated Guided Vehicle (AGV) robots commonly employ 2D plane navigation systems. However, with the expansion of AGV application scenarios and the increasing complexity of structures, the limitations of existing 2D navigation systems have become more pronounced, rendering them inadequate for addressing these challenges. To tackle this issue, this paper proposes a novel navigation system suitable for AGV robots composed of fused Lidar and Inertial Measurement Unit (IMU), named as Lidar-IMU Fusion Navigation System (LIFNS). LIFNS primarily comprises mapping, localization, and fused path planning modules. In the mapping module, a 3D point cloud map for precise 3D localization and a 2D grid map for path planning are constructed using multiple-line Lidar and IMU. For the localization module, a fusion localization approach is introduced, combining IMU data with Normal Distributions Transform (NDT) point cloud registration through Unscented Kalman Filtering (UKF). Finally, global path planning is executed using the A* algorithm on the grid map, while local path planning utilizes the Timed-Elastic Band (TEB) algorithm. The effectiveness and universality of LIFNS are validated through simulation experiments and real-world deployment tests. The experimental results demonstrate that LIFNS achieves centimeter-level accuracy in both mapping and localization, effectively alleviating the issues of low precision and significant limitations present in traditional AGV robots. This positions LIFNS with promising applications in enclosed settings such as smart factories, industrial parks, and healthcare facilities.
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LIFNS:为智能工厂中的 AGV 设计新型激光雷达-IMU 融合导航系统
传统的自动导引车(AGV)机器人通常采用二维平面导航系统。然而,随着 AGV 应用场景的扩展和结构的日益复杂,现有 2D 导航系统的局限性日益凸显,已不足以应对这些挑战。针对这一问题,本文提出了一种由激光雷达和惯性测量单元(IMU)融合而成的适用于 AGV 机器人的新型导航系统,即激光雷达-IMU 融合导航系统(LIFNS)。LIFNS 主要包括测绘、定位和融合路径规划模块。在绘图模块中,利用多线激光雷达和 IMU 构建用于精确 3D 定位的 3D 点云图和用于路径规划的 2D 网格图。在定位模块中,引入了一种融合定位方法,通过无痕卡尔曼滤波(UKF)将 IMU 数据与正态分布变换(NDT)点云注册相结合。最后,在网格图上使用 A* 算法执行全局路径规划,而局部路径规划则使用定时松紧带(TEB)算法。通过模拟实验和实际部署测试,验证了 LIFNS 的有效性和通用性。实验结果表明,LIFNS 在绘图和定位方面都达到了厘米级精度,有效缓解了传统 AGV 机器人精度低和局限性大的问题。这使得 LIFNS 在智能工厂、工业园区和医疗设施等封闭环境中的应用前景广阔。
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来源期刊
CiteScore
5.10
自引率
30.80%
发文量
167
审稿时长
5.1 months
期刊介绍: Manufacturing industries throughout the world are changing very rapidly. New concepts and methods are being developed and exploited to enable efficient and effective manufacturing. Existing manufacturing processes are being improved to meet the requirements of lean and agile manufacturing. The aim of the Journal of Engineering Manufacture is to provide a focus for these developments in engineering manufacture by publishing original papers and review papers covering technological and scientific research, developments and management implementation in manufacturing. This journal is also peer reviewed. Contributions are welcomed in the broad areas of manufacturing processes, manufacturing technology and factory automation, digital manufacturing, design and manufacturing systems including management relevant to engineering manufacture. Of particular interest at the present time would be papers concerned with digital manufacturing, metrology enabled manufacturing, smart factory, additive manufacturing and composites as well as specialist manufacturing fields like nanotechnology, sustainable & clean manufacturing and bio-manufacturing. Articles may be Research Papers, Reviews, Technical Notes, or Short Communications.
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