Distributed maximum a posteriori estimation for multi-robot cooperative localization
Esha D. Nerurkar,Stergios I. Roumeliotis,Agostino Martinelli +2 more
- pp 1375-1382
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TLDR
A distributed data-allocation scheme is presented that enables robots to simultaneously process and update their local data and a computationally efficient distributed marginalization of past robot poses is introduced for limiting the size of the optimization problem.Abstract:
This paper presents a distributed Maximum A Posteriori (MAP) estimator for multi-robot Cooperative Localization (CL). As opposed to centralized MAP-based CL, the proposed algorithm reduces the memory and processing requirements by distributing data and computations amongst the robots. Specifically, a distributed data-allocation scheme is presented that enables robots to simultaneously process and update their local data. Additionally, a distributed Conjugate Gradient algorithm is employed that reduces the cost of computing the MAP estimates, while utilizing all available resources in the team and increasing robustness to single-point failures. Finally, a computationally efficient distributed marginalization of past robot poses is introduced for limiting the size of the optimization problem. The communication and computational complexity of the proposed algorithm is described in detail, while extensive simulation studies are presented for validating the performance of the distributed MAP estimator and comparing its accuracy to that of existing approaches.read more
Citations
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Journal ArticleDOI
Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age
Cesar Cadena,Luca Carlone,Henry Carrillo,Yasir Latif,Davide Scaramuzza,José Neira,Ian Reid,John J. Leonard +7 more
TL;DR: Simultaneous localization and mapping (SLAM) as mentioned in this paper consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot moving within it.
Journal ArticleDOI
Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age
Cesar Cadena,Luca Carlone,Henry Carrillo,Yasir Latif,Davide Scaramuzza,José L. Neira,Ian Reid,John J. Leonard +7 more
TL;DR: What is now the de-facto standard formulation for SLAM is presented, covering a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping, theoretical performance guarantees, active SLAM and exploration, and other new frontiers.
Journal ArticleDOI
AUV Navigation and Localization: A Review
TL;DR: A review of the state of the art of AUV navigation and localization, as well as a description of some of the more commonly used methods, are presented and areas of future research potential are highlighted.
Posted Content
Simultaneous Localization And Mapping: Present, Future, and the Robust-Perception Age.
Cesar Cadena,Luca Carlone,Henry Carrillo,Yasir Latif,Davide Scaramuzza,José L. Neira,Ian Reid,John J. Leonard +7 more
TL;DR: What is now the de-facto standard formulation for SLAM is presented, and a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping, theoretical performance guarantees, active SLAM and exploration, and other new frontiers are reviewed.
Journal ArticleDOI
Cooperative AUV Navigation using a Single Maneuvering Surface Craft
TL;DR: This paper investigates an alternative approach that utilizes the position information of a surface vehicle to bound the error and uncertainty of the on-board position estimates of a low-cost AUV.
References
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TL;DR: Numerical Recipes: The Art of Scientific Computing as discussed by the authors is a complete text and reference book on scientific computing with over 100 new routines (now well over 300 in all), plus upgraded versions of many of the original routines, with many new topics presented at the same accessible level.
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