Graph-Based Observability Analysis of Bearing-Only Cooperative Localization

Sharma, Rajnikant; Beard, Randal W.; Taylor, Clark N.; Quebe, Stephen

doi:10.1109/tro.2011.2172699

Cited by 79 publications

(43 citation statements)

References 21 publications

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“…The idea of using landmarks to aid in localization has been addressed previously in [14], [16]. There are also a number of techniques that use so-called proxy landmarks arXiv:1802.07652v2 [math.OC] 10 Jul 2018…”

Section: A Related Workmentioning

confidence: 99%

“…If the system is observable and linear, a bound on the uncertainty in the estimation error can be related to the the eigenvalues of the observability grammian [15]. For the problem of localization of UVs, authors in [14] have shown that each UV requires bearing measurements from two distinct landmarks for observability of the system; the observability of the system is shown using Lie derivative theory. An important problem that arises in this context is that of landmark placement, i.e., given a route for the UV, to place landmarks so that the system is always observable; this would in turn ensure the error in state estimates of the position and heading of the UV, obtained using the estimation algorithms, remain bounded [15].…”

Section: Introductionmentioning

confidence: 99%

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Landmark Placement for Localization in a GPS-denied Environment

Sundar

Srinivasan

Misra

et al. 2018

2018 Annual American Control Conference (ACC)

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Path planning algorithms for unmanned aerial or ground vehicles, in many surveillance applications, rely on Global Positioning System (GPS) information for localization. However, disruption of GPS signals, by intention or otherwise, can render these plans and algorithms ineffective. This article provides a way of addressing this issue by utilizing stationary landmarks to aid localization in such GPS-disrupted or GPSdenied environment. In particular, given the vehicle's path, we formulate a landmark-placement problem and present algorithms to place the minimum number of landmarks while satisfying the localization, sensing, and collision-avoidance constraints. The performance of such a placement is also evaluated via extensive simulations on ground robots.

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Section: A Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Landmark Placement for Localization in a GPS-denied Environment

Sundar

Srinivasan

Misra

et al. 2018

2018 Annual American Control Conference (ACC)

Self Cite

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“…rank(O)=n), a mobile robot can estimates its own state from the mea surements. Several robot researchers have utilized this analysis method [1] [2] [3], and we also employed the non linear observability matrix in our research.…”

Section: Observability Analysismentioning

confidence: 99%

“…They showed that unobservable measurements were misunder stood as observable due to linearization errors. R. Sharma et al [3] determined the maximum rank in a coopera tive localization problem and verified that robots require a minimum of two known landmarks to estimate their over all state.…”

Section: Introductionmentioning

confidence: 99%

Observability analysis of 2D geometric features using the condition number for SLAM applications

Yeon

Doh

2013

2013 13th International Conference on Control, Automation and Systems (ICCAS 2013)

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Observability analysis is a very powerful tool for discriminating whether a robot can estimate its own state. However, this method cannot investigate how much of the system is observable. This is a major problem from a state estimation perspective because there is too much noise in real environments. Therefore, although the system (or a mobile robot) is observable, it cannot estimate its own state. To address this problem, we propose an observability analysis method that uses the condition number. Mathematically, the condition number of matrix represents a degree of robustness to noise. We utilize this property of the condition number to investigate the degree of observability. In other words, the condition number of the observability matrix demonstrates the feasibility of state estimation and the robustness of its feasibility for estimation.

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“…However, they only studied the observability properties of two robots, and the collaborative localization problem was resolved with respect to a relative reference, i.e., the pose of the second vehicle was estimated with respect to the first vehicle. An inspiring work focusing on the observability analysis of bearing-only collaborative localization system is found in [19]. They derived the maximum rank of the observability matrix without global information and show that to achieve full observability, all nodes must connect to at least two external infrastructures with known location.…”

Section: Introductionmentioning

confidence: 99%

Range-only Collaborative Localization for Ground Vehicles

Shi¹,

Cui²,

Zhao³

et al. 2019

Proceedings of the 32nd International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+ 201

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High-accuracy absolute localization for a team of vehicles is essential when accomplishing various kinds of tasks. As a promising approach, collaborative localization fuses the individual motion measurements and the inter-vehicle measurements to collaboratively estimate the states. In this paper, we focus on the range-only collaborative localization, which specifies the inter-vehicle measurements as inter-vehicle ranging measurements. We first investigate the observability properties of the system and derive that to achieve bounded localization errors, two vehicles are required to remain static like external infrastructures. Under the guide of the observability analysis, we then propose our range-only collaborative localization system which categorize the ground vehicles into two static vehicles and dynamic vehicles. The vehicles are connected utilizing a UWB network that is capable of both producing inter-vehicle ranging measurements and communication. Simulation results validate the observability analysis and demonstrate that collaborative localization is capable of achieving higher accuracy when utilizing the inter-vehicle measurements. Extensive experimental results are performed for a team of 3 and 5 vehicles. The real-world results illustrate that our proposed system enables accurate and real-time estimation of all vehicles' absolute poses.

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Graph-Based Observability Analysis of Bearing-Only Cooperative Localization

Cited by 79 publications

References 21 publications

Landmark Placement for Localization in a GPS-denied Environment

Landmark Placement for Localization in a GPS-denied Environment

Observability analysis of 2D geometric features using the condition number for SLAM applications

Range-only Collaborative Localization for Ground Vehicles

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