Time-Relative RTK-GNSS: GNSS Loop Closure in Pose Graph Optimization

Suzuki, Taro

doi:10.1109/lra.2020.3003861

Cited by 35 publications

(15 citation statements)

References 19 publications

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“…Compared with the feature point method, the direct method can estimate denser maps and is more robust to scenes with insignificant textures, but the direct method is more sensitive to illumination changes and has difficulty handling closed-loop detection [9]. Among them, the feature point method is the more commonly used method, while the direct method has only been proposed in recent years [10]. In the back-end part, SLAM methods usually transform the whole problem into a maximizing a posteriori probability estimation (MAP) problem, using the data association provided by the front-end to estimate both the positional and surrounding environment maps [11].…”

Section: Current Status Of Researchmentioning

confidence: 99%

[Retracted] Combined GNSS/SLAM‐Based High Accuracy Indoor Dynamic Target Localization Method

Zhang

Li³

et al. 2021

Wireless Communications and Mobile Computing

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As the indoor dynamic target localization does not detect and repair the circumferential jump value in time, which leads to large position and attitude errors and low-velocity stability, a combined Global Navigation Satellite System/Simultaneous Localization and Mapping- (GNSS/SLAM-) based high-precision indoor dynamic target localization method is proposed. The method uses Empirical Mode Decomposition (EMD) to decompose the noisy signal, obtains the noise energy as the dominant mode from the decomposed components, extracts the useful signal energy as the main dividing point, removes the high-frequency signal, constructs the low-frequency component to realize low-pass filtering and denoising, selects a suitable threshold processing function to make the high-frequency signal component retain the detailed signal effectively to realize high-frequency component denoising, detects and fixes the circumferential jump of the observed data, and detects and fixes the circumferential jump of each frequency. The indoor dynamic target positioning method is established by combining GNSS/SLAM to achieve high accuracy target positioning. The experimental results show that the position and attitude errors are small, and the velocity is stable, which indicates that the position information is closer to the dynamic target, i.e., the target positioning is more accurate. To address the problems of scale drift and frequent initialization due to environmental factors in monocular vision SLAM, an Ultra Wideband (UWB)/vision fusion localization model that takes into account the scale factor is proposed, which can give full play to the complementary characteristics between UWB and vision; solve the problems of visual initialization, scale ambiguity, and absolute spatial reference; and improve UWB localization accuracy and localization frequency as well as reducing the number of base stations. The model can reliably achieve 0.2 m accuracy in indoor environments with sparse texture or frequent light changes.

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Section: Current Status Of Researchmentioning

confidence: 99%

[Retracted] Combined GNSS/SLAM‐Based High Accuracy Indoor Dynamic Target Localization Method

Zhang

Li³

et al. 2021

Wireless Communications and Mobile Computing

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“…This would be appropriate in many applications where the acceptable path-tracking error is larger outdoors in open space than indoors. As a consequence of the relative framework, our algorithm only requires relative accuracy of GNSS so loop-closure techniques to increase single-point GNSS accuracy [33] could also be explored.…”

Section: Discussionmentioning

confidence: 99%

Relatively Lazy: Indoor-Outdoor Navigation Using Vision and GNSS

Congram

Barfoot

2021

2021 18th Conference on Robots and Vision (CRV)

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Visual Teach and Repeat (VT&R) has shown relative navigation is a robust and efficient solution for autonomous vision-based path following in difficult environments. Adding additional absolute sensors such as Global Navigation Satellite Systems (GNSS) has the potential to expand the domain of VT&R to environments where the ability to visually localize is not guaranteed. Our method of lazy mapping and delaying estimation until a path-tracking error is needed avoids the need to estimate absolute states. As a result, map optimization is not required and paths can be driven immediately after being taught. We validate our approach on a real robot through an experiment in a joint indoor-outdoor environment comprising 3.5km of autonomous route repeating across a variety of lighting conditions. We achieve smooth error signals throughout the runs despite large sections of dropout for each sensor.

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“…Unfortunately, conventional wireless positioning technologies represented by global navigation satellite system (GNSS) and terrestrial cellular-based positioning are vulnerable to jamming attacks [9]. For the widely used GNSS systems, their services cover almost all regions of the world and could achieve centimeter-level accuracy with high-end equipment in open-sky environments [10], [11]. However, the positioning services provided by GNSS rely on satellites operating in orbit at altitudes ranging from 19 to 35 thousand km [12].…”

Section: A Motivationmentioning

confidence: 99%

Feasibility Study of UAV-Assisted Anti-Jamming Positioning

Wang

Liu

et al. 2021

IEEE Trans. Veh. Technol.

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As the cost and technical difficulty of jamming devices continue to decrease, jamming has become one of the major threats to positioning service. Unfortunately, most conventional wireless positioning technologies are vulnerable to jamming attacks due to inherent shortcomings like weak signal strength and unfavorable anchor geometry. Thanks to their high operational flexibility, unmanned aerial vehicles (UAVs) could be a promising solution to the above challenges. Therefore, in this article, we propose a UAV-assisted anti-jamming positioning system, in which multiple UAVs first utilize time-difference-ofarrival (TDoA) measurements from ground reference stations and double-response two-way ranging (DR-TWR) measurements from UAV-to-UAV links to perform self-localization as well as clock synchronization, and then act as anchor nodes to provide TDoA positioning service for ground users in the presence of jamming. To evaluate the feasibility and performance of the proposed system, we first derive the Cramér-Rao lower bound (CRLB) of UAV self-localization. Then, the impacts of UAV position uncertainty and synchronization errors caused by jamming on positioning service are modeled, and the theoretical root-mean-square error (RMSE) of user position estimate is further derived. Numerical results demonstrate that the proposed system is a promising alternative to existing positioning systems when their services are disrupted by jamming. The most notable advantage of the proposed system is that it is fully compatible with existing user equipment terminals and positioning methods. Index Terms-Unmanned aerial vehicle (UAV), anti-jamming positioning, time-difference-of-arrival (TDoA), double-response two-way ranging (DR-TWR).

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Time-Relative RTK-GNSS: GNSS Loop Closure in Pose Graph Optimization

Cited by 35 publications

References 19 publications

[Retracted] Combined GNSS/SLAM‐Based High Accuracy Indoor Dynamic Target Localization Method

[Retracted] Combined GNSS/SLAM‐Based High Accuracy Indoor Dynamic Target Localization Method

Relatively Lazy: Indoor-Outdoor Navigation Using Vision and GNSS

Feasibility Study of UAV-Assisted Anti-Jamming Positioning

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