基于多传感器紧耦合的工程机械定位与建图系统

doi:10.3901/JME.2023.24.323

机械工程学报 ›› 2023, Vol. 59 ›› Issue (24): 323-333.doi: 10.3901/JME.2023.24.323

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基于多传感器紧耦合的工程机械定位与建图系统

任好玲^1,2, 吴江东^1,2, 林添良^1,2, 张春晖^1,2, 李玉坤^1,2

1. 华侨大学机电及自动化学院厦门 361021;
2. 福建省移动机械绿色智能驱动与传动重点实验室厦门 361021

收稿日期:2023-01-11 修回日期:2023-08-02 出版日期:2023-12-20 发布日期:2024-03-05
通讯作者: 林添良(通信作者),男,1983年出生,博士,教授,博士研究生导师。主要研究方向为工程机械的电动化和智能化技术。E-mail:ltlkxl@163.com
作者简介:任好玲,女,1978年出生,博士,副教授,硕士研究生导师。主要研究方向为工程机械电动化与智能化技术。E-mail:happyrhlly@126.com
基金资助:
国家自然科学基金(52175051,52275055)、福建省高校产学合作(2022H6007&2022H6028)和福建省自然科学基金重点(2021J02013)资助项目

Construction Machinery Localization and Mapping System Based on Multi-sensor Tight Coupling

REN Haoling^1,2, WU Jiangdong^1,2, LIN Tianliang^1,2, ZHANG Chunhui^1,2, LI Yukun^1,2

1. College of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021;
2. Fujian Provincial Key Laboratory of Green Intelligent Drive and Transmission for Mobile Machinery, Xiamen 361021

Received:2023-01-11 Revised:2023-08-02 Online:2023-12-20 Published:2024-03-05

摘要/Abstract

摘要： 工程机械工况复杂、作业环境恶劣，实现工程机械无人驾驶将带来显著的社会效益和经济价值。工程机械不同于普通乘用车，为实现无人驾驶工程机械在多复杂工况下的高鲁棒性定位，采用多传感器紧耦合的同步定位与建图系统(Simultaneous localization and mapping, SLAM)。针对现有SLAM前端算法计算冗余、计算效率低下等问题，采用基于点线、点面特征匹配的方法，结合局部地图配准，有效降低点云配准时的数据量，避免计算冗余。针对现有激光融合SLAM无回环检测的问题，基于空间近邻原则结合正态分布变换算法将回环检测机制引入SLAM系统，有效降低SLAM系统建图的全局误差。针对工程机械作业环境定位与建图易退化的问题，在点线、点面特征匹配的基础上，创立了残差自适应反馈机制，使得迭代方程求解快速收敛而不发散。仿真和实车试验结果证明该套SLAM系统能够有效解决工程机械在桥梁、长廊等作业场景下的建图退化问题，建图速度大大提高，能够满足工程机械实时定位与建图的需求。

关键词: 无人驾驶, 工程机械, 同步定位与建图, 特征匹配, 回环检测, 残差自适应反馈

Abstract: The working conditions of construction machinery are complex and the working environment is harsh. The realization of unmanned driving of construction machinery will bring significant social benefits and economic value. Construction machinery is different from ordinary passenger vehicles. In order to achieve high robust localization of driverless construction machinery under multiple complex working conditions, a multi-sensor tight coupled simultaneous localization and mapping (SLAM) system is used. Aiming at the problems of computational redundancy and low computational efficiency of the existing SLAM front-end algorithm, a method based on point line and point surface feature matching is adopted, combined with local map registration, which effectively reduces the amount of data on point cloud registration and avoids computational redundancy. Aiming at the problem of loopless detection of laser fusion SLAM, the loop closure detection mechanism is introduced into the SLAM system based on the spatial nearest neighbor principle and the normal distribution transformation algorithm, which effectively reduces the global error of the SLAM system mapping. Aiming at the problem of easy degradation in the localization and mapping of construction machinery working environment, based on the matching of point line and point surface features, a residual adaptive feedback mechanism is established, which makes the iterative equation solution converge quickly without divergence. The simulation and real vehicle test results show that this SLAM system can effectively solve the problem of map building degradation of construction machinery in bridge, corridor and other operating scenarios, and the speed of map building is greatly improved, which can meet the requirements of real-time localization and mapping of construction machinery.

Key words: unmanned driving, construction machinery, simultaneous localization and mapping, feature matching, loop closure detection, residual adaptive feedback

中图分类号:

TP242

任好玲, 吴江东, 林添良, 张春晖, 李玉坤. 基于多传感器紧耦合的工程机械定位与建图系统[J]. 机械工程学报, 2023, 59(24): 323-333.

REN Haoling, WU Jiangdong, LIN Tianliang, ZHANG Chunhui, LI Yukun. Construction Machinery Localization and Mapping System Based on Multi-sensor Tight Coupling[J]. Journal of Mechanical Engineering, 2023, 59(24): 323-333.

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基于多传感器紧耦合的工程机械定位与建图系统

Construction Machinery Localization and Mapping System Based on Multi-sensor Tight Coupling

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