Analysis on Observability and Performance of INS-Range Integrated Navigation System Under Urban Flight Environment

Lee, Byungjin; Kim, Dong-gyun; Lee, Juhwan; Sung, Sangkyung

doi:10.1007/s42835-020-00510-w

Cited by 6 publications

(4 citation statements)

References 20 publications

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“…However, in some cases, only one wall and floor on the horizontal axis can satisfy a full rank [12]. Therefore, we introduced the conditional number to determine the sensitivity of the matrix.…”

Section: Three-dimensional Point Cloud Map-based Observabilitymentioning

confidence: 99%

“…Figure 11 shows the path generated by the exploration algorithm and the map generated by driving the path. The black dots and orange lines show the map generated by SLAM [12] and SLAM's position estimate when the LiDAR maximum distance is 50 m. The green dots and purple line show the map generated by SLAM and the SLAM's position estimate when the LiDAR maximum distance is 10 m. Both conditions are the result of adjusting only the maximum LiDAR range on the same dataset. We can see that the error is significant in situations where the sensor's performance is limited.…”

Section: Lidar Max Range: 50 Mmentioning

confidence: 99%

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Design and Verification of Observability-Driven Autonomous Vehicle Exploration Using LiDAR SLAM

Kim,

Lee,

Sung

2024

Aerospace

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This paper explores the research topic of enhancing the reliability of unmanned mobile exploration using LiDAR SLAM. Specifically, it proposes a technique to analyze waypoints where 3D LiDAR SLAM can be smoothly performed in potential exploration areas and points where there is a risk of divergence in navigation estimation. The goal is to improve exploration performance by presenting a method that secures these candidate regions. The analysis employs a 3D geometric observability matrix and its condition number to discriminate waypoints. Subsequently, the discriminated values are applied to path planning, resulting in the derivation of a final destination path connecting waypoints with a satisfactory SLAM position and attitude estimation performance. To validate the proposed technique, performance analysis was initially conducted using the Gazebo simulator. Additionally, experiments were performed with an autonomous unmanned vehicle in a real-world environment.

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Section: Three-dimensional Point Cloud Map-based Observabilitymentioning

confidence: 99%

Section: Lidar Max Range: 50 Mmentioning

confidence: 99%

Design and Verification of Observability-Driven Autonomous Vehicle Exploration Using LiDAR SLAM

Kim,

Lee,

Sung

2024

Aerospace

Self Cite

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“…The measurement is defined in the relationship between the wall and a specific posi tion P. Therefore, the size of the measurement matrix usually increases with the numbe of walls [18].…”

Section: Observability Modelmentioning

confidence: 99%

Observability-Driven Path Planning Design for Securing Three-Dimensional Navigation Performance of LiDAR SLAM

2023

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This paper presents an efficient method for securing navigation performance by suppressing divergence risk of LiDAR SLAM through a newly proposed geometric observability analysis in a three-dimensional point cloud map. For this, observability characteristics are introduced that quantitatively evaluate the quality of the geometric distribution of the features. To be specific, this study adapts a 3D geometric observability matrix and the associated condition number for developing numerical benefit. In an extensive application, we implemented path planning in which the enhanced SLAM performs smoothly based on the proposed method. Finally, to validate the performance of the proposed algorithm, a simulation study was performed using the high-fidelity Gazebo simulator, where the path planning strategy of a drone depending on navigation quality is demonstrated. Additionally, an indoor autonomous vehicle experimental result is presented to support the effectiveness of the proposed algorithm.

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“…Hermann et al, (1977) first consider system observability in the control field. Nowadays, this theory is widely applied in many other fields (Wang et al, 2018;Lee et al, 2020). The observability matrix is computed and if the matrix rank is full, it indicates that the positioning system is observable.…”

mentioning

confidence: 99%

A GPS/BDS Based Train Positioning Method Using Non-differential Range Measurements

Jiang,

Zhou,

Wang

et al. 2024

Preprint

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Compared with pseudorange measurement, carrier phase tracking is much less noisy, which can provide accurate positioning solutions. The existing carrier phase-based positioning methods rely on precise ephemeris or base station, which may cause poor real-time and increase complexity in the system. To simplify the calculation model and achieve accurate navigation solutions with a stand-alone receiver, a new GPS/BDS based real-time non-differential positioning method is proposed. Due to the need to estimate the ambiguity terms of carrier phase measurements, the dimension of the state is larger than that of the measurement, the system observability is evaluated via the observability degrees. Both the train test on Beijing- Shenyang high speed railway and simulation were carried out, and the results confirm that the multi-constellation method can improve the positioning accuracy compared with stand-alone cases. The position and velocity Root Mean Square of the proposed method are (0.9022 m, 0.9140 m, 1.1621 m) and (0.0818 m/s, 0.0958m/s, 0.0289m/s) in the north, east, down directions. The proposed method has improved positioning performance in terms of accuracy and observability compared with different combinations of measurement methods.

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Analysis on Observability and Performance of INS-Range Integrated Navigation System Under Urban Flight Environment

Cited by 6 publications

References 20 publications

Design and Verification of Observability-Driven Autonomous Vehicle Exploration Using LiDAR SLAM

Design and Verification of Observability-Driven Autonomous Vehicle Exploration Using LiDAR SLAM

Observability-Driven Path Planning Design for Securing Three-Dimensional Navigation Performance of LiDAR SLAM

A GPS/BDS Based Train Positioning Method Using Non-differential Range Measurements

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