Control for Localization of Targets Using Range-Only Sensors

Grocholsky, Ben; Stump, Ethan; Shiroma, Pedro Mitsuo; Kumar, Vijay

doi:10.1007/978-3-540-77457-0_18

Cited by 9 publications

(5 citation statements)

References 7 publications

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“…Djugash et al (2006) developed an approach that integrated Simultaneous Localization and Mapping (SLAM) with mobile sensor networks, achieving self-calibration of a network consisting of mobile and stationary nodes with range measurements. Grocholsky et al (2006) used non-linear set-based state estimation techniques for localization of multiple mobile robots with range measurements between platforms.…”

Section: Introductionmentioning

confidence: 99%

Cooperative Localization for Autonomous Underwater Vehicles

Bähr

Leonard

Fallon

2009

The International Journal of Robotics Research

323

143

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Self-localization of an underwater vehicle is particularly challenging due to the absence of Global Positioning System (GPS) reception or features at known positions that could otherwise have been used for position computation. Thus Autonomous Underwater Vehicle (AUV) applications typically require the pre-deployment of a set of beacons.This thesis examines the scenario in which the members of a group of AUVs exchange navigation information with one another so as to improve their individual position estimates.We describe how the underwater environment poses unique challenges to vehicle navigation not encountered in other environments in which robots operate and how cooperation can improve the performance of self-localization. As intra-vehicle communication is crucial to cooperation, we also address the constraints of the communication channel and the effect that these constraints have on the design of cooperation strategies.The classical approaches to underwater self-localization of a single vehicle, as well as more recently developed techniques are presented. We then examine how methods used for cooperating land-vehicles can be transferred to the underwater domain. An algorithm for distributed self-localization, which is designed to take the specific characteristics of the environment into account, is proposed.We also address how correlated position estimates of cooperating vehicles can lead to overconfidence in individual position estimates.Finally, key to any successful cooperative navigation strategy is the incorporation of the relative positioning between vehicles. The performance of localization algorithms with different geometries is analyzed and a distributed algorithm for the dynamic positioning of vehicles, which serve as dedicated navigation beacons for a fleet of AUVs, is proposed.

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Section: Introductionmentioning

confidence: 99%

Cooperative Localization for Autonomous Underwater Vehicles

Bähr

Leonard

Fallon

2009

The International Journal of Robotics Research

323

143

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“…Distributed coordination of teams of autonomous robots has received increasing attention from the control society in the last decade [1,2,3,4], due to the rapid development of computation and communication techniques as well as powerful embedded systems. One typical coordination task is formation keeping, in which a team of mobile agents is required to move collaboratively so that the team manoeuvres as a whole with a prescribed formation shape [5,6,7,8,9,10]. Formation control of mobile agents, finds various applications in engineering fields, such as sensor networks for data collections [11], unmanned aerial vehicles for military missions [12], and satellite formations for deep space exploration [13].…”

Section: Introductionmentioning

confidence: 99%

Coordinate-free formation control of multi-agent systems using rooted graphs

Liu

Lin

Cao

et al. 2018

Systems & Control Letters

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This paper studies how to control large formations of autonomous agents in the plane, assuming that each agent is able to sense relative positions of its neighboring agents with respect to its own local coordinate system. We tackle the problem by adopting two types of controllers. First, we use the classical gradient-based controllers on three leader agents to meet their distance constraints. Second, we develop other type of controllers for follower agents: utilizing the properties of rooted graphs, one is able to design linear controllers incorporating relative positions between the follower agents and their neighbors, to stabilize the overall large formations. The advantages of the proposed method are fourfold: i) fewer constraints on neighboring relationship graphs; ii) simplicity of linear controllers for follower agents; iii) global convergence of the overall formations; iv) implementation in local coordinate systems, in no need of a global coordinate system. Numerical simulations show the effectiveness of the proposed method.

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“…We are particularly interested in solutions to the station keeping problem in which the only signals available to the agent whose position is to be maintained, are noisy range measurements from its neighbors 1 . Work on the range-only station keeping problem already exists [2], [3], [4]. Our approach to station keeping builds on the work initiated in [1] where we treated station keeping as a problem in switched adaptive control.…”

Section: Introductionmentioning

confidence: 99%

Convexification of the range-only station keeping problem

Cao

Morse

2008

2008 American Control Conference

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Abstract-Using concepts from switched adaptive control theory plus a special parameterization of the class of 2 × 2 nonsingular matrices, a tractable and provably correct solution is given to the three landmark station keeping problem in the plane in which range measurements are the only sensed signals upon which station keeping is to be based. The performance of the overall system degrades gracefully in the face of increasing measurement and miss-alignment errors, provided the measurement errors are not too large.

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Control for Localization of Targets Using Range-Only Sensors

Cited by 9 publications

References 7 publications

Cooperative Localization for Autonomous Underwater Vehicles

Cooperative Localization for Autonomous Underwater Vehicles

Coordinate-free formation control of multi-agent systems using rooted graphs

Convexification of the range-only station keeping problem

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