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学者姓名：张立伟
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Abstract ：
In recent studies on LiDAR SLAM, the achievement of robust optimized LiDAR odometry is the primary objective. For the mapping part, some studies focus on improving the processing of point cloud, while others aim to the optimization of the result deviation caused by errors. Meanwhile, in the fields of robotics and autonomous driving, multi-sensor fusion solutions based on IMUs are becoming the norm. This paper contributes to the optimization of mapping by leveraging a lightweight LiDAR-inertial state estimator. The proposed method combines information from a 6-axis IMU and a 3D LiDAR to form a tightly-coupled scheme that incorporates iterative error state Kalman filter (IESKF). Due to the continuous error accumulation, trajectory deviations can be significant. To mitigate this, an adaptive distance threshold loop closure detection mechanism is employed. Furthermore, since the algorithm primarily addresses outdoor scenes, ground features collected by sensors account for a significant portion of the computation. Improvements in the ground segmentation method lead to less disturbance during mapping on uneven terrain, enabling the method to effectively ad-dress a wider range of real-world environments. As a result, the proposed method demonstrates excellent stability and accuracy, as verified in experiments conducted on urban dataset and campus environment. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Keyword ：
Errors Errors Iterative methods Iterative methods Mapping Mapping Optical radar Optical radar Optimization Optimization Robotics Robotics
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| GB/T 7714 | Wang, Yuhang , Zhang, Liwei . Lidar-Inertial SLAM Method for Accurate and Robust Mapping [C] . 2024 : 33-44 . |
| MLA | Wang, Yuhang 等. "Lidar-Inertial SLAM Method for Accurate and Robust Mapping" . (2024) : 33-44 . |
| APA | Wang, Yuhang , Zhang, Liwei . Lidar-Inertial SLAM Method for Accurate and Robust Mapping . (2024) : 33-44 . |
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Simultaneous Localization And Mapping (SLAM) is a critical technology for autonomous driving in urban environments. However, in environments with many moving objects, currently available LiDAR-based SLAM methods cannot effectively detect loops as they assume a static environment, resulting in unreliable trajectories. Therefore, in this paper, we propose RB-LIO, a LiDAR SLAM system based on the LIO-SAM framework. The proposed system utilizes a dynamic object segmentation module to mitigate the influence of moving objects with tight-coupled LiDAR inertial odometry. It also corrects the complete 6-DoF loop closure with BoW3D and performs pose graph optimization using GTSAM-ISAM2. We tested RB-LIO on public datasets (KITTI and MulRan) and self-collected datasets and compared it with state-of-the-art SLAM systems such as A-LOAM, LeGO-LOAM, LINS, LIO-SAM, and Fast-LIO2. The experimental results indicate that RB-LIO achieves more than 40% improvement in accuracy and a significant improvement of map quality. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Keyword ：
Image segmentation Image segmentation Object detection Object detection Optical radar Optical radar Robotics Robotics
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| GB/T 7714 | Zhang, Yanzhou , Zhang, Liwei . RB-LIO: A SLAM Solution Applied to Large-Scale Dynamic Scenes with Multiple Moving Objects [C] . 2024 : 180-192 . |
| MLA | Zhang, Yanzhou 等. "RB-LIO: A SLAM Solution Applied to Large-Scale Dynamic Scenes with Multiple Moving Objects" . (2024) : 180-192 . |
| APA | Zhang, Yanzhou , Zhang, Liwei . RB-LIO: A SLAM Solution Applied to Large-Scale Dynamic Scenes with Multiple Moving Objects . (2024) : 180-192 . |
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In this paper, we present a lightweight, integrated LiDAR SLAM system designed for high efficiency and robust loop closure detection. Our evaluation focuses on LiDAR-based platforms with limited on-board computation capabilities in long-distance and large-scale scenarios. We identify that front-end only SLAM systems are prone to drift due to accumulated errors in pose estimation. To mitigate this issue, we propose two enhancements: 1) the implementation of an incremental kd tree (ikd-tree) data structure for efficient map management, and 2) the utilization of Normal Distribution Descriptor (NDD) for loop closure detection, combined with GTSAM for global optimization, which effectively corrects the final trajectory of the algorithm. Finally, we validate our proposed method using the KITTI and MulRan datasets and benchmark it against the FLOAM system. The experimental results reveal that our method surpasses FLOAM in terms of computational efficiency by 26.21% and 53.53%, and in terms of accuracy by 36.88% and 84.76% on the KITTI and MulRan datasets, respectively. These findings demonstrate the potential of our lightweight integrated LiDAR SLAM system to significantly improve both efficiency and accuracy in challenging environments, making it a valuable contribution to the field of SLAM research. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Keyword ：
Computational efficiency Computational efficiency Global optimization Global optimization Information management Information management Normal distribution Normal distribution Optical radar Optical radar Trees (mathematics) Trees (mathematics)
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| GB/T 7714 | Yin, Guoqiang , Zhang, Liwei . Robust Real-Time Optimized LiDAR Odometry with Loop Closure Detection [C] . 2024 : 322-333 . |
| MLA | Yin, Guoqiang 等. "Robust Real-Time Optimized LiDAR Odometry with Loop Closure Detection" . (2024) : 322-333 . |
| APA | Yin, Guoqiang , Zhang, Liwei . Robust Real-Time Optimized LiDAR Odometry with Loop Closure Detection . (2024) : 322-333 . |
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Purpose: In order to improve the isolation capability of the longitudinal vibration of the shafting system in the low frequency range, a lever-type isolator with negative stiffness (LTINS) was proposed. Methods: The LTINS arranged in parallel with the thrust bearing to isolate the longitudinal fluctuating force transmitted from the propeller-shaft to its foundation. The Rayleigh–Ritz method is used to establish the longitudinal dynamic model of the propeller-shaft-LTINS system. Results: The force transmissibility of the coupled system is formulated, and computed results are compared with those solutions obtained from the finite element method. A stability analysis is carried out based on the equivalent static and dynamic stiffness of the thrust bearing of the shafting system. A comparison study is conducted to compare the isolation performance of the proposed isolator with the traditional isolator such as the dynamic anti-resonance vibration isolator (DAVI), absorber such as the dynamic vibration absorber (DVA), and dynamic vibration absorber with negative stiffness (DVANS). Parametric optimization is carried out to investigate the impact of the parameters of the LTINS on its isolation performance. Conclusion: The results indicated that the proposed control method can achieve a much wider bandwidth than that of the traditional vibration control scheme with a much smaller mass ratio. © Springer Nature Singapore Pte Ltd. 2024.
Keyword ：
Axial vibration control Axial vibration control Lever-type isolator with negative stiffness Lever-type isolator with negative stiffness Rayleigh–Ritz method Rayleigh–Ritz method Shafting system Shafting system Thrust bearing Thrust bearing
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| GB/T 7714 | Liu, N. , Lei, X. , Lin, F. et al. Longitudinal Vibration Transmission Suppression for Propeller-Shaft System by a Lever-Type Isolator with Negative Stiffness [J]. | Journal of Vibration Engineering and Technologies , 2024 . |
| MLA | Liu, N. et al. "Longitudinal Vibration Transmission Suppression for Propeller-Shaft System by a Lever-Type Isolator with Negative Stiffness" . | Journal of Vibration Engineering and Technologies (2024) . |
| APA | Liu, N. , Lei, X. , Lin, F. , Zhang, L. , Yang, J. . Longitudinal Vibration Transmission Suppression for Propeller-Shaft System by a Lever-Type Isolator with Negative Stiffness . | Journal of Vibration Engineering and Technologies , 2024 . |
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Abstract ：
The processing of 3D point clouds from laser scanning is still challenging in self-driving perception and positioning community. Ground segmentation is the key topic, splitting out the ground point cloud effectively reduces the amount of data and increases the speed of subsequent point cloud clustering and feature point extraction. The ground points segmented in SLAM can be used as constraints for back-end optimisation, improving the accuracy of map building and localisation. After the ground segmentation is completed, it can be used as a passable area for vehicle path planning. Existing approaches are based on the assumption that the ground is plane, but unfortunately the ground is not a plane, with a large number of slopes, roadsides, and parts of the ground even rugged and full of obstacles. In order to solve the ground segmentation problem, this paper proposes a ground segmentation method based on polar grid. The main contributions of this paper include: (1) We divide a frame of point cloud space into several regions, each of which is divided into several grids, based on the scanning characteristics of the LIDAR. (2) The plane was fitted based on the improved RANSAC algorithm for each of the previously divided grids. Experiments with KITTI and campus real environment datasets show that the sensitivity of our proposed method can reach more than 98% and the specificity is below 10%. The proposed algorithm can effectively and correctly separate the ground from the point cloud, even on slopes and the ground with many obstacles. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Keyword ：
Motion planning Motion planning Optical radar Optical radar
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| GB/T 7714 | Zhou, Jiyang , Zhang, Liwei . Polar Grid Based Point Cloud Ground Segmentation [C] . 2023 : 632-643 . |
| MLA | Zhou, Jiyang et al. "Polar Grid Based Point Cloud Ground Segmentation" . (2023) : 632-643 . |
| APA | Zhou, Jiyang , Zhang, Liwei . Polar Grid Based Point Cloud Ground Segmentation . (2023) : 632-643 . |
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At present, most of the traditional algorithms for mobile robot autonomous exploration in unknown environments use frontier as a guide and adopt greedy strategies for determining the next exploration target. They generate new frontier as new regions of the map, and thus the cycle repeats itself to finally complete the exploration of unknown environments. In this paper, we propose a region clustering-based approach for autonomous exploration of mobile robots in complex environments. Our approach incorporates the concept of region clustering at its global level based on the current advanced hierarchical exploration framework. The robot is more inclined to finish exploring a certain region of the map first, thereby minimizing the robot’s repetitive exploration of explored regions. Mobile robot autonomous exploration experiments were implemented in our college campus. The experimental results show that the average exploration trajectory length was reduced by 14.03%, and the average exploration time was reduced by 16.15%, respectively. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Keyword ：
Mobile robots Mobile robots
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| GB/T 7714 | Zheng, Haoping , Zhang, Liwei , Chen, Meng . Region Clustering for Mobile Robot Autonomous Exploration in Unknown Environment [C] . 2023 : 371-388 . |
| MLA | Zheng, Haoping et al. "Region Clustering for Mobile Robot Autonomous Exploration in Unknown Environment" . (2023) : 371-388 . |
| APA | Zheng, Haoping , Zhang, Liwei , Chen, Meng . Region Clustering for Mobile Robot Autonomous Exploration in Unknown Environment . (2023) : 371-388 . |
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Abstract ：
本发明涉及一种激光SLAM的回环检测方法，步骤1：获取单帧三维点云数据及其同步IMU信息；步骤2：将当前帧点云分割为个单元空间，将单元空间数据分别存入矩阵，以此构建第一描述符；将分割后的点云数据与IMU信息存入B向量，以此构建第二描述符；步骤3：用步骤2所述历史帧的第二描述符构建KDTree；步骤4：用第二描述符进行最近邻搜索，从KDTree中找出n个候选相似帧；将候选相似帧与当前点云根据第一描述符进行匹配，根据匹配结果是否符合阈值判断候选相似帧中是否存在闭环，若存在，得出当前帧与回环帧的相对旋转变化。本发明实现移动机器人在室外场景以及局部路段相似性程度高的场景中精度更高、鲁棒性更强的回环检测以及地图构建方法。
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| GB/T 7714 | 张立伟 , 刘洁琳 , 徐光进 et al. 一种激光SLAM的回环检测方法 : CN202110775299.8[P]. | 2021-07-08 . |
| MLA | 张立伟 et al. "一种激光SLAM的回环检测方法" : CN202110775299.8. | 2021-07-08 . |
| APA | 张立伟 , 刘洁琳 , 徐光进 , 何炳蔚 . 一种激光SLAM的回环检测方法 : CN202110775299.8. | 2021-07-08 . |
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本发明提出基于并行树搜索的桁架装配序列规划方法，包括以下步骤：步骤S1：根据目标桁架结构生成无向图，对各个杆件赋予相应的权重，存储于并行树搜索的主模式中；步骤S2：根据桁架结构建立若干个子模式及对应的根结点，各子模式分别扩展多叉树，逐层生成叶子结点；步骤S3：判断各子模式的最优解是否产生冲突，并由主模式中的判别机制进行选择决策；步骤S4：各子模式将得到的最优叶子结点信息返回主模式，主模式将已连接的杆件对应的序列号设置为不可读状态；步骤S5：子模式逐步扩展到无可扩展的杆件列表时，由主模式判断目标桁架结构是否被完全扩展，由此判断是否结束搜索程序；本发明能够快速有效的获取符合稳定性要求的桁架并行装配序列。
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| GB/T 7714 | 张立伟 , 林晓丹 , 陈睿函 et al. 基于并行树搜索的桁架装配序列规划方法 : CN202110767902.8[P]. | 2021-07-07 . |
| MLA | 张立伟 et al. "基于并行树搜索的桁架装配序列规划方法" : CN202110767902.8. | 2021-07-07 . |
| APA | 张立伟 , 林晓丹 , 陈睿函 , 何炳蔚 . 基于并行树搜索的桁架装配序列规划方法 : CN202110767902.8. | 2021-07-07 . |
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Rapidly-exploring Random Tree (RRT) algorithm is widely used in path planning, while the RRT is inefficient for robotic exploration in large-scale environments with multi-obstacles and narrow entrances. Here, we propose a Hybrid Frontier Detection (HFD) strategy for autonomous exploration which incorporates a variable step-size random tree global frontier detector, a multi-root nodes random tree frontier detector, and a grid-based frontier detector algorithm. The proposed strategy enables a robot to quickly search for the frontier in real-time. Compared with the traditional RRT-based strategy, the exploration time and traveling length of the proposed HFD strategy are respectively decreased by over 15% and 12% in the simulation environment and decreased by over 14% and 11% under the same experimental conditions in the experimental environment. The results indicate that the HFD strategy effectively solves the problem of autonomous exploration in the environment with multi-obstacles and narrow entrances. © 2021 IEEE.
Keyword ：
Motion planning Motion planning Robotics Robotics Robot programming Robot programming Robots Robots Trees (mathematics) Trees (mathematics)
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| GB/T 7714 | Xu, Guangjin , Zhang, Liwei , Chen, Meng et al. Hybrid Frontier Detection Strategy for Autonomous Exploration in Multi-obstacles Environment [C] . 2021 : 1909-1915 . |
| MLA | Xu, Guangjin et al. "Hybrid Frontier Detection Strategy for Autonomous Exploration in Multi-obstacles Environment" . (2021) : 1909-1915 . |
| APA | Xu, Guangjin , Zhang, Liwei , Chen, Meng , He, Bingwei . Hybrid Frontier Detection Strategy for Autonomous Exploration in Multi-obstacles Environment . (2021) : 1909-1915 . |
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The key of robots operating autonomously in dynamic environments is understanding the dynamic characteristics of objects. This paper aims to detect dynamic objects and reconstruct 3D static maps from consecutive scans of scenes. Our work starts from an encode-decode network, which receives two range maps provided by a Velodyne HDL-64 laser scanner and outputs dynamic probability of each point. Since the soft segmentation produced by the network tends to be smooth, a 3D fully connected CRF (Conditional Random Field) is proposed to improve the segmentation performance. Experiments on both the public datasets and real-word platform demonstrate the effectiveness of our method.
Keyword ：
CRF CRF Dynamic objects detection Dynamic objects detection Encode-decode network Encode-decode network Robot vision Robot vision Static maps reconstruction Static maps reconstruction
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| GB/T 7714 | Zou, Cheng , He, Bingwei , Zhu, Mingzhu et al. Encode-decode network with fully connected CRF for dynamic objects detection and static maps reconstruction [J]. | SIGNAL PROCESSING-IMAGE COMMUNICATION , 2021 , 95 . |
| MLA | Zou, Cheng et al. "Encode-decode network with fully connected CRF for dynamic objects detection and static maps reconstruction" . | SIGNAL PROCESSING-IMAGE COMMUNICATION 95 (2021) . |
| APA | Zou, Cheng , He, Bingwei , Zhu, Mingzhu , Zhang, Liwei , Zhang, Jianwei . Encode-decode network with fully connected CRF for dynamic objects detection and static maps reconstruction . | SIGNAL PROCESSING-IMAGE COMMUNICATION , 2021 , 95 . |
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