Estimating the Localizability in Tunnel-like Environments using LiDAR and UWB

Zhen, Weikun; Scherer, Sebastian

doi:10.1109/icra.2019.8794167

Cited by 63 publications

(30 citation statements)

References 18 publications

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“…Zheng et al proposed a probabilistic sensor fusion method to combine IMU, LiDAR, and UWB for robot navigation in tunnel-like Environments. Experimental results show that the proposed method can achieve a robust localization result inside a long straight tunnel [30].…”

Section: Related Workmentioning

confidence: 95%

Toward Elderly Care: A Phase-Difference-of-Arrival Assisted Ultra-Wideband Positioning Method in Smart Home

Zhang

Duan

2020

IEEE Access

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Location-based services (LBSs) for elderly care is a trending topic in smart homes. The key issue is the high accurate positioning for the elderly. Ultra-wideband (UWB) is a centimeter-level positioning accuracy in line-of-sight (LOS) environments. However, most of existing UWB positioning methods need non-line-of-sight (NLOS) identification and compensation, and thus leading to severe deterioration in positioning accuracy in presence of complex indoor environments where the elderly lived. This article proposes a phase-difference-of-arrival (PDOA) assisted UWB positioning method (PDOA-UWB) for elderly care. In our positioning framework, we first calculate the phase difference of arrival from PDOA chip integrated in the UWB base stations (BSs) to obtain a coarse location of the elderly, which is further used to distinguish which nearby BSs are in LOS environments and which are in NLOS environments. Then, a PDOA-UWB positioning solution is derived to improve the positioning accuracy of the elderly. Compared with some existing methods, our method achieves higher accuracy with less NLOS compensation, and is easier to be implemented in complex indoor environments for simple practical engineering applications. Experimental results show the efficacy of our proposed method. INDEX TERMS Phase-difference-of-arrival (PDOA), location-based services (LBSs), ultra-wideband (UWB) positioning, smart home, indoor positioning

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Section: Related Workmentioning

confidence: 95%

Toward Elderly Care: A Phase-Difference-of-Arrival Assisted Ultra-Wideband Positioning Method in Smart Home

Zhang

Duan

2020

IEEE Access

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“…Our developed utilities also export the colored point map from R 3 LIVE or the offline meshed map into commonly used file formats such as "pcd" 15 , "ply" 16 , "obj" 17 and etc. As a TABLE III: The relative pose error in Experiment-3.…”

Section: A Mesh Reconstruction and Texturingmentioning

confidence: 99%

“…However, for LiDAR-based SLAM systems, they would easily fail in those scenarios with no enough geometry features, especially for solid-state LiDARs which typically have limited FoV [11]. To address this problem, fusing LiDAR with other sensors such as camera [12]- [15] and Ultra-wideband (UWB) [16,17] can improve the system's robustness and accuracy. In particular, various of LiDAR-Visual fusion frameworks have been proposed recently in the robotics community [18].…”

Section: Introductionmentioning

confidence: 99%

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R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package

Lin¹,

Zhang²

2021

Preprint

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In this letter, we propose a novel LiDAR-Inertial-Visual sensor fusion framework termed R 3 LIVE, which takes advantage of measurement of LiDAR, inertial, and visual sensors to achieve robust and accurate state estimation. R 3 LIVE is contained of two subsystems, the LiDAR-inertial odometry (LIO) and visual-inertial odometry (VIO). The LIO subsystem (FAST-LIO) takes advantage of the measurement from LiDAR and inertial sensors and builds the geometry structure of (i.e. the position of 3D points) global maps. The VIO subsystem utilizes the data of visual-inertial sensors and renders the map's texture (i.e. the color of 3D points). More specifically, the VIO subsystem fuses the visual data directly and effectively by minimizing the frame-to-map photometric error. The developed system R 3 LIVE is developed based on our previous work R 2 LIVE, with careful architecture design and implementation. Experiment results show that the resultant system achieves more robustness and higher accuracy in state estimation than current counterparts (see our attached video 1 ). R 3 LIVE is a versatile and well-engineered system toward various possible applications, which can not only serve as a SLAM system for real-time robotic applications, but can also reconstruct the dense, precise, RGB-colored 3D maps for applications like surveying and mapping. Moreover, to make R 3 LIVE more extensible, we develop a series of offline utilities for reconstructing and texturing meshes, which further minimizes the gap between R 3 LIVE and various of 3D applications such as simulators, video games and etc (see our demos video 2 ). To share our findings and make contributions to the community, we open source R 3 LIVE on our Github 3 , including all of our codes, software utilities, and the mechanical design of our device.

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“…[7] [8] proposed to integrate the information provided by 3D laser scan, UWB, and INS in a filter-based way such as error state Kalman filter (ESKF) or extend Kalman filter (EKF). But [5] [6] [8] do not consider the degeneration situation and [7] cannot acquire the prior information of UWB automatically.…”

Section: Related Workmentioning

confidence: 99%

Anti-degenerated UWB-LiDAR Localization for Automatic Road Roller in Tunnel

Shen¹,

Chen²,

Yang³

et al. 2021

Preprint

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The automatic road roller, as a popular type of construction robot, has attracted much interest from both the industry and the research community in recent years. However, when it comes to tunnels where the degeneration issues are prone to happen, it is still a challenging problem to provide an accurate positioning result for the robot. In this paper, we aim to deal with this problem by fusing LiDAR and UWB measurements based on optimization. In the proposed localization method, the directions of non-degeneration will be constrained and the covariance of UWB reconstruction will be introduced to improve the accuracy of localization. Apart from these, a method that can extract the feature of the inner wall of tunnels to assist positioning is also presented in this paper. To evaluate the effectiveness of the proposed method, three experiments with real road roller were carried out and the results show that our method can achieve better performance than the existing methods and can be applied to automatic road roller working inside tunnels. Finally, we discuss the feasibility of deploying the system in real applications and make several recommendations.

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Estimating the Localizability in Tunnel-like Environments using LiDAR and UWB

Cited by 63 publications

References 18 publications

Toward Elderly Care: A Phase-Difference-of-Arrival Assisted Ultra-Wideband Positioning Method in Smart Home

Toward Elderly Care: A Phase-Difference-of-Arrival Assisted Ultra-Wideband Positioning Method in Smart Home

R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package

Anti-degenerated UWB-LiDAR Localization for Automatic Road Roller in Tunnel

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