Random set approach to distributed multivehicle SLAM
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TLDR
The developed algorithm represents - to the best of the authors’ knowledge - the first attempt to solve in a fully decentralized way the multi-vehicle SLAM problem within the RFS framework.About:
This article is published in IFAC-PapersOnLine.The article was published on 2017-07-01 and is currently open access. It has received 24 citations till now. The article focuses on the topics: Simultaneous localization and mapping.read more
Citations
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Journal ArticleDOI
5G mmWave Cooperative Positioning and Mapping Using Multi-Model PHD Filter and Map Fusion
TL;DR: A new method for cooperative vehicle positioning and mapping of the radio environment is proposed, comprising a multiple-model probability hypothesis density filter and a map fusion routine, which is able to consider different types of objects and different fields of views.
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Distributed multi-sensor multi-view fusion based on generalized covariance intersection
TL;DR: An efficient and robust distributed fusion algorithm combining the Generalized Covariance Intersection (GCI) rule with a suitable Clustering Algorithm (CA) is proposed that decomposes each posterior PHD into well-separated components (clusters).
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Recent advances in multisensor multitarget tracking using random finite set
TL;DR: An overview of recent advances in multisensor multitarget tracking based on the random finite set (RFS) approach and two robust multitarget density-averaging approaches, arithmetic- and geometric-average fusion, are addressed in detail for various RFSs.
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Fusion of Labeled RFS Densities With Minimum Information Loss
TL;DR: It is shown theoretically that label matching can be solved as a separate problem with respect to LRFS density fusion by resorting to the MIL criterion.
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Gaussian Mixture Particle Jump-Markov-CPHD Fusion for Multitarget Tracking Using Sensors With Limited Views
TL;DR: The concepts of zero-forcing and zero-avoiding originally used in density approximation are introduced to elucidate a key difference between geometric and arithmetic averaging approaches, which are extended for joint target-state and mode fusion with regard to each PO-FoV.
References
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Consensus and Cooperation in Networked Multi-Agent Systems
TL;DR: A theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees is provided.
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A solution to the simultaneous localization and map building (SLAM) problem
TL;DR: The paper proves that a solution to the SLAM problem is indeed possible and discusses a number of key issues raised by the solution including suboptimal map-building algorithms and map management.
Journal ArticleDOI
Multitarget Bayes filtering via first-order multitarget moments
TL;DR: Recursion Bayes filter equations for the probability hypothesis density are derived that account for multiple sensors, nonconstant probability of detection, Poisson false alarms, and appearance, spawning, and disappearance of targets and it is shown that the PHD is a best-fit approximation of the multitarget posterior in an information-theoretic sense.
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The Gaussian Mixture Probability Hypothesis Density Filter
Ba-Ngu Vo,Wing-Kin Ma +1 more
TL;DR: Under linear, Gaussian assumptions on the target dynamics and birth process, the posterior intensity at any time step is a Gaussian mixture and closed-form recursions for propagating the means, covariances, and weights of the constituent Gaussian components of the posteriorintensity are derived.
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A Consistent Metric for Performance Evaluation of Multi-Object Filters
TL;DR: This paper outlines the inconsistencies of existing metrics in the context of multi- object miss-distances for performance evaluation, and proposes a new mathematically and intuitively consistent metric that addresses the drawbacks of current multi-object performance evaluation metrics.