TY - GEN
T1 - Performance bounds for cooperative simultaneous localization and mapping (C-SLAM)
AU - Mourikis, Anastasios I.
AU - Roumeliotis, Stergios
N1 - Publisher Copyright:
© 2005 Massachusetts Institute of Technology.
Copyright:
Copyright 2016 Elsevier B.V., All rights reserved.
PY - 2005
Y1 - 2005
N2 - In this paper we study the time evolution of the position estimates' covariance in Cooperative Simultaneous Localization and Mapping (C-SLAM), and obtain analytical upper bounds for the positioning uncertainty. The derived bounds provide descriptions of the asymptotic positioning performance of a team of robots in a mapping task, as a function of the characteristics of the proprioceptive and exteroceptive sensors of the robots, and of the graph of relative position measurements recorded by the robots. A study of the properties of the Riccati recursion which describes the propagation of uncertainty through time, yields (i) the guaranteed accuracy for a robot team in a given C-SLAM application, as well as (ii) the maximum expected steady-state uncertainty of the robots and landmarks, when the spatial distribution of features in the environment can be modeled by a known distribution. The theoretical results are validated by simulation experiments.
AB - In this paper we study the time evolution of the position estimates' covariance in Cooperative Simultaneous Localization and Mapping (C-SLAM), and obtain analytical upper bounds for the positioning uncertainty. The derived bounds provide descriptions of the asymptotic positioning performance of a team of robots in a mapping task, as a function of the characteristics of the proprioceptive and exteroceptive sensors of the robots, and of the graph of relative position measurements recorded by the robots. A study of the properties of the Riccati recursion which describes the propagation of uncertainty through time, yields (i) the guaranteed accuracy for a robot team in a given C-SLAM application, as well as (ii) the maximum expected steady-state uncertainty of the robots and landmarks, when the spatial distribution of features in the environment can be modeled by a known distribution. The theoretical results are validated by simulation experiments.
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M3 - Conference contribution
AN - SCOPUS:84959510358
SN - 9780262701143
T3 - Robotics: Science and Systems
SP - 73
EP - 80
BT - Robotics
A2 - Thrun, Sebastian
A2 - Sukhatme, Gaurav
A2 - Schaal, Stefan
A2 - Brock, Oliver
PB - MIT Press Journals
T2 - International Conference on Robotics: Science and Systems, RSS 2005
Y2 - 8 June 2005 through 11 June 2005
ER -