A Distributed Optimization Framework for Localization and Formation Control: Applications to Vision-Based Measurements

Tron, Roberto; Thomas, Justin; Loianno, Giuseppe; Daniilidis, Kostas; Kumar, Vijay

doi:10.1109/mcs.2016.2558401

Cited by 122 publications

(18 citation statements)

References 69 publications

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“…Note that the relative positions, bearings, angles, and ratioof-distances can be obtained by vision technology [27]- [29], which can then be regarded as communication-free measurements. In addition, an implicit assumption in this paper is that each follower i and its neighbors N i in (2) are within their sensing ranges.…”

Section: Appendixmentioning

confidence: 99%

“…For example, if agent j is a neighbor of follower i, the implicit assumption is that follower i and the rest agents in N i are within the sensing range of agent j. That is, agent j ∈ N i equipped with vision sensors can obtain relative positions, bearings, angles, or ratio-of-distances with follower i and the rest agents in N i in a communication-free manner [27]- [29]. Agent j ∈ N i can transfer its measured information to follower i through the directed edge (i, j).…”

Section: Appendixmentioning

confidence: 99%

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Distributed Formation Maneuver Control of Multiagent Systems Over Directed Graphs

Xie

2022

IEEE Trans. Cybern.

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This paper studies the problem of integrated distributed network localization and formation maneuver control. We develop an integrated relative-measurement-based scheme, which only uses relative positions, distances, bearings, angles, ratio-of-distances, or their combination to achieve distributed network localization and formation maneuver control in R d (d ≥ 2). By exploring the localizability and invariance of the target formation, the scale, rotation, and translation of the formation can be controlled simultaneously by only tuning the leaders' positions, i.e., the followers do not need to know parameters of the scale, rotation, and translation of the target formation. The proposed method can globally drive the formation errors to zero in finite time over multi-layer d+1-rooted graphs. A simulation example is given to illustrate the theoretical results.

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Section: Appendixmentioning

confidence: 99%

Section: Appendixmentioning

confidence: 99%

Distributed Formation Maneuver Control of Multiagent Systems Over Directed Graphs

Xie

2022

IEEE Trans. Cybern.

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“…where S 2 represents the 2D manifold on the unit sphere in R 3 , and b G ij is the unit vector of the sensing beam expressed in the global coordinate frame. Note that the local bearing information b ij can be measured in agent i's local coordinate frame via onboard cameras [22]. Write (17) in its column vector form…”

Section: Definition Of Bearing In Se(3)mentioning

confidence: 99%

Bearing rigidity and formation stabilization for multiple rigid bodies in <inline-formula><tex-math id="M1">\begin{document}$ SE(3) $\end{document}</tex-math></inline-formula>

Chen¹,

Cao²,

Li³

2019

Numerical Algebra, Control &Amp; Optimization

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In this work, we first distinguish different notions related to bearing rigidity in graph theory and then further investigate the formation stabilization problem for multiple rigid bodies. Different from many previous works on formation control using bearing rigidity, we do not require the use of a shared global coordinate system, which is enabled by extending bearing rigidity theory to multi-agent frameworks embedded in the three dimensional special Euclidean group SE(3) and expressing the needed bearing information in each agent's local coordinate system. Here, each agent is modeled by a rigid body with 3 DOFs in translation and 3 DOFs in rotation. One key step in our approach is to define the bearing rigidity matrix in SE(3) and construct the necessary and sufficient conditions for infinitesimal bearing rigidity. In the end, a gradient-based bearing formation control algorithm is proposed to stabilize formations of multiple rigid bodies in SE(3).

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“…9,16,29,30 RBFCA requires measuring the relative bearings between agents. Compared with the relative position or distance measurements, the relative bearing measurements are often more accessible and cheaper, 31 and can be obtained by on-board camera 32 or sensor arrays. 33 In RBFCA, the bearing rigidity theory (BRT) has proven to be an important tool.…”

Section: Introductionmentioning

confidence: 99%

Bearing‐based formation control of second‐order multiagent systems with bounded disturbances

Xu,

Zelazo,

2023

Intl J Robust & Nonlinear

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This article investigates the bearing‐based formation control problem for second‐order multiagent systems (SMS) in the presence of the bounded disturbances in their models. The main contributions of this article are listed as follows: (1) We extend the bearing formation control to SMS. (2) We propose two novel robust distributed bearing formation control laws. In the first control law, the bearing measurement in the global inertial frame is required. This control law guarantees that the inter‐agent bearings converge to the desired bearings. The second control law requires obtaining the local bearing measurements and relative orientation measurements. This control law guarantees that the inter‐agent bearings converge to the desired bearings and the orientation of each agent converges to a common orientation. Some simulations are conducted, and simulation results verify the effectiveness of the proposed control laws.

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A Distributed Optimization Framework for Localization and Formation Control: Applications to Vision-Based Measurements

Cited by 122 publications

References 69 publications

Distributed Formation Maneuver Control of Multiagent Systems Over Directed Graphs

Distributed Formation Maneuver Control of Multiagent Systems Over Directed Graphs

Bearing rigidity and formation stabilization for multiple rigid bodies in <inline-formula><tex-math id="M1">\begin{document}$ SE(3) $\end{document}</tex-math></inline-formula>

Bearing‐based formation control of second‐order multiagent systems with bounded disturbances

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