Performance analysis of multirobot cooperative localization

Anastasios I. Mourikis; Stergios I. Roumeliotis

doi:10.1109/TRO.2006.878957

Performance analysis of multirobot cooperative localization

Anastasios I. Mourikis
, Stergios I. Roumeliotis

Computer Science and Engineering

Research output: Contribution to journal › Article › peer-review

206 Scopus citations

Abstract

This paper studies the accuracy of position estimation for groups of mobile robots performing cooperative localization. We consider the case of teams comprised of possibly heterogeneous robots and provide analytical expressions for the upper bound on their expected positioning uncertainty. This bound is determined as a function of the sensors' noise covariance and the eigenvalues of the relative position measurement graph (RPMG), i.e., the weighted directed graph which represents the network of robot-to-robot exteroceptive measurements. The RPMG is employed as a key element in this analysis, and its properties are related to the localization performance of the team. It is shown that, for a robot group of a certain size, the maximum expected rate of uncertainty increase is independent of the accuracy and number of relative position measurements and depends only on the accuracy of the proprioceptive and orientation sensors on the robots. Additionally, the effects of changes in the topology of the RPMG are studied, and it is shown that, at steady-state, these reconfigurations do not inflict any loss in localization precision. Experimental data, as well as simulation results that validate the theoretical analysis, are presented.

Original language	English (US)
Pages (from-to)	666-681
Number of pages	16
Journal	IEEE Transactions on Robotics
Volume	22
Issue number	4
DOIs	https://doi.org/10.1109/TRO.2006.878957
State	Published - Aug 2006

Bibliographical note

Funding Information:
Manuscript received July 8, 2005; revised January 20, 2006. This paper was recommended for publication by Associate Editor D. Fox and Editors I. Walker and K. Lynch upon evaluation of the reviewers’ comments. This work was supported in part by the University of Minnesota GiA Award, DTC, in part by the Jet Propulsion Laboratory under Grants 1248696 and 1251073, and in part by the National Science Foundation ITR, under Grant EIA-0324864. This paper was presented in part at the IEEE International Conference on Robotics and Automation, New Orleans, LA, April/May 2004.

Keywords

Cooperative localization (CL)
Kalman filtering
Multirobot localization
Positioning accuracy
Relative position measurement graph (RPMG)
Sensor sharing

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10.1109/TRO.2006.878957

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title = "Performance analysis of multirobot cooperative localization",

abstract = "This paper studies the accuracy of position estimation for groups of mobile robots performing cooperative localization. We consider the case of teams comprised of possibly heterogeneous robots and provide analytical expressions for the upper bound on their expected positioning uncertainty. This bound is determined as a function of the sensors' noise covariance and the eigenvalues of the relative position measurement graph (RPMG), i.e., the weighted directed graph which represents the network of robot-to-robot exteroceptive measurements. The RPMG is employed as a key element in this analysis, and its properties are related to the localization performance of the team. It is shown that, for a robot group of a certain size, the maximum expected rate of uncertainty increase is independent of the accuracy and number of relative position measurements and depends only on the accuracy of the proprioceptive and orientation sensors on the robots. Additionally, the effects of changes in the topology of the RPMG are studied, and it is shown that, at steady-state, these reconfigurations do not inflict any loss in localization precision. Experimental data, as well as simulation results that validate the theoretical analysis, are presented.",

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note = "Funding Information: Manuscript received July 8, 2005; revised January 20, 2006. This paper was recommended for publication by Associate Editor D. Fox and Editors I. Walker and K. Lynch upon evaluation of the reviewers{\textquoteright} comments. This work was supported in part by the University of Minnesota GiA Award, DTC, in part by the Jet Propulsion Laboratory under Grants 1248696 and 1251073, and in part by the National Science Foundation ITR, under Grant EIA-0324864. This paper was presented in part at the IEEE International Conference on Robotics and Automation, New Orleans, LA, April/May 2004.",

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N2 - This paper studies the accuracy of position estimation for groups of mobile robots performing cooperative localization. We consider the case of teams comprised of possibly heterogeneous robots and provide analytical expressions for the upper bound on their expected positioning uncertainty. This bound is determined as a function of the sensors' noise covariance and the eigenvalues of the relative position measurement graph (RPMG), i.e., the weighted directed graph which represents the network of robot-to-robot exteroceptive measurements. The RPMG is employed as a key element in this analysis, and its properties are related to the localization performance of the team. It is shown that, for a robot group of a certain size, the maximum expected rate of uncertainty increase is independent of the accuracy and number of relative position measurements and depends only on the accuracy of the proprioceptive and orientation sensors on the robots. Additionally, the effects of changes in the topology of the RPMG are studied, and it is shown that, at steady-state, these reconfigurations do not inflict any loss in localization precision. Experimental data, as well as simulation results that validate the theoretical analysis, are presented.

AB - This paper studies the accuracy of position estimation for groups of mobile robots performing cooperative localization. We consider the case of teams comprised of possibly heterogeneous robots and provide analytical expressions for the upper bound on their expected positioning uncertainty. This bound is determined as a function of the sensors' noise covariance and the eigenvalues of the relative position measurement graph (RPMG), i.e., the weighted directed graph which represents the network of robot-to-robot exteroceptive measurements. The RPMG is employed as a key element in this analysis, and its properties are related to the localization performance of the team. It is shown that, for a robot group of a certain size, the maximum expected rate of uncertainty increase is independent of the accuracy and number of relative position measurements and depends only on the accuracy of the proprioceptive and orientation sensors on the robots. Additionally, the effects of changes in the topology of the RPMG are studied, and it is shown that, at steady-state, these reconfigurations do not inflict any loss in localization precision. Experimental data, as well as simulation results that validate the theoretical analysis, are presented.

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KW - Relative position measurement graph (RPMG)

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Performance analysis of multirobot cooperative localization

Abstract

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