Paper Info
Title
Single beacon based multi-robot cooperative localization using Moving Horizon Estimation
Abstract
This paper studies three-dimensional multi-robot Cooperative Localization (CL) problem. Most of existing CL strategies adopt Extended Kalman Filter (EKF) or Maximum a Posteriori (MAP). In this paper, a novel approach based on Moving Horizon Estimation (MHE) is proposed. The main contribution of this paper is twofold: 1) MHE is integrated with EKF for three-dimensional CL using single mobile beacon, which can bound localization error, impose various constraints on states and noises, and make use of previous range measurements for current estimation. 2) A sufficient condition on observability of multi-robot CL is derived by using Fisher Information Matrix. Simulation is conducted to verify that the proposed MHE based CL algorithm outperforms EKF based method in terms of localization accuracy, and two scenarios where our algorithm is superior to EKF are discussed.
Year
DOI
Venue
2014
10.1109/ICRA.2014.6907069
ICRA
Keywords
Field
DocType
ekf,localization error,kalman filters,maximum likelihood estimation,moving horizon estimation,matrix algebra,mobile robots,multi-robot systems,motion estimation,fisher information matrix,multirobot cooperative localization,cl problem,slam (robots),mhe,mobile beacon,extended kalman filter,maximum a posteriori,map,nonlinear filters
Observability,Extended Kalman filter,Control theory,Moving horizon estimation,Control engineering,Fisher information,Maximum a posteriori estimation,Engineering,Invariant extended Kalman filter,Robot
Conference
Volume
Issue
ISSN
2014
1
1050-4729
Citations 
PageRank 
References 
1
0.36
14
Authors
4
Name
Order
Citations
PageRank
Sen Wang127921.15
Ling Chen2364.03
Dongbing Gu376972.81
Huosheng Hu42009220.95