Fully Decentralized Cooperative Localization of a Robot Team: An Efficient and Centralized Equivalent Solution

Mu, Hua; Dai, Mengyuan; Gao, Ming; Pan, Xianfei

doi:10.1007/978-3-642-40852-6_53

Cited by 2 publications

(3 citation statements)

References 8 publications

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“…Notice that (16) requires matrix inversio, and take elementary row transformation as the method for matrix inversion. The computational complexity of (14), (15), (16), (17), and (18) is ( 2 2 ), ( 3 3 ),…”

Section: Analysis Of Computational Complexitymentioning

confidence: 99%

“…From the perspective of probabilistic graphical models in artificial intelligence, Lauritzen introduced a method for modeling and local computing of exact mean and covariance in dynamic systems based on JT [13]. The most remarkable advantage of the JT algorithm to other decentralized algorithms is that the JT algorithm has equivalent precision to centralized EKF [14]. Thus it is possible to develop a new decentralized cooperative navigation algorithm for formation flying spacecrafts.…”

Section: Introductionmentioning

confidence: 99%

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Decentralized State Estimation Algorithm of Centralized Equivalent Precision for Formation Flying Spacecrafts Based on Junction Tree

Dai

et al. 2015

International Journal of Aerospace Engineering

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As centralized state estimation algorithms for formation flying spacecraft would suffer from high computational burdens when the scale of the formation increases, it is necessary to develop decentralized algorithms. To the state of the art, most decentralized algorithms for formation flying are derived from centralized EKF by simplification and decoupling, rendering suboptimal estimations. In this paper, typical decentralized state estimation algorithms are reviewed, and a new scheme for decentralized algorithms is proposed. In the new solution, the system is modeled as a dynamic Bayesian network (DBN). A probabilistic graphical method named junction tree (JT) is used to analyze the hidden distributed structure of the DBNs. Inference on JT is a decentralized form of centralized Bayesian estimation (BE), which is a modularized three-step procedure of receiving messages, collecting evidences, and generating messages. As KF is a special case of BE, the new solution based on JT is equivalent in precision to centralized KF in theory. A cooperative navigation example of a three-satellite formation is used to test the decentralized algorithms. Simulation results indicate that JT has the best precision among all current decentralized algorithms.

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Section: Analysis Of Computational Complexitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Decentralized State Estimation Algorithm of Centralized Equivalent Precision for Formation Flying Spacecrafts Based on Junction Tree

Dai

et al. 2015

International Journal of Aerospace Engineering

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“…Mu et al 14 introduces a decentralized solution to the problem of cooperative localization for robot teams based on JT, and summarizes the basic operations on conditional Gaussian (CG) distributions for linear time invariant (LTI) systems. 15 Inspired from achievements in related fields, this research is intended to introduce a new method of orbit determination for satellite constellations based on crosslinks. Instead of the traditional state space model, the problem is formulated in dynamical Bayesian network (DBN) in ''Problem formulations'' section, which would motivate the design of our solution.…”

Section: Introductionmentioning

confidence: 99%

Junction-tree-based cooperative orbit determination for crosslink-augmented satellite constellations

Dai

2015

Proceedings of the Institution of Mechanical Engineers, Part G:

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The lack of ground-tracking resources has become a primary bottleneck for the Chinese BeiDou navigation satellite system. As crosslinks have been widely recognized as a promising augmentation for the autonomous navigation of the global navigation satellite system, this article studies a new decentralized data fusion method for orbit determination of crosslink-augmented satellite constellations. In the new solution, the system is modeled as a probabilistic graphical model, the dynamical Bayesian network, and a graphical method named junction tree is introduced to analyze the structure of the system. By dividing and arranging the predictions and estimations of junction tree in a proper sequence, a new decentralized solution with centralized equivalent precision is designed. As the solution requires satellites in the constellation cooperating with each other through communications and measurements, it is named junction-tree-based cooperative orbit determination. Simulation results indicate that junction-tree-based cooperative orbit determination has centralized equivalent precision and good robustness after satellite failures, whereas centralized solutions such as extended Kalman filter may suffer from processing center malfunctions. Junction-tree-based cooperative orbit determination could not only serve as an optional choice for global navigation satellite system autonomous navigation but also be used as a general scheme for decentralized data fusion in cooperative systems such as unmanned aerial vehicle formations and so on.

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Fully Decentralized Cooperative Localization of a Robot Team: An Efficient and Centralized Equivalent Solution

Cited by 2 publications

References 8 publications

Decentralized State Estimation Algorithm of Centralized Equivalent Precision for Formation Flying Spacecrafts Based on Junction Tree

Decentralized State Estimation Algorithm of Centralized Equivalent Precision for Formation Flying Spacecrafts Based on Junction Tree

Junction-tree-based cooperative orbit determination for crosslink-augmented satellite constellations

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