Optimal sensor scheduling for resource-constrained localization of mobile robot formations

Anastasios I. Mourikis; Stergios I. Roumeliotis

doi:10.1109/TRO.2006.878947

Optimal sensor scheduling for resource-constrained localization of mobile robot formations

Anastasios I. Mourikis, Stergios I. Roumeliotis

Computer Science and Engineering

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84 Scopus citations

Abstract

This paper addresses the problem of resource allocation in formations of mobile robots localizing as a group. Each robot receives measurements from various sensors that provide relative (robot-to-robot) and absolute positioning information. Constraints on the sensors' bandwidth, as well as communication and processing requirements, limit the number of measurements that are available or can be processed at each time step. The localization uncertainty of the group, determined by the covariance matrix of the equivalent continuous-time system at steady state, is expressed as a function of the sensor measurements' frequencies. The trace of the weighted covariance matrix is selected as the optimization criterion, under linear constraints on the measuring frequency of each sensor and the cumulative rate of the extended Kalman filter updates. This formulation leads to a convex optimization problem (semidefinite program) whose solution provides the sensing frequencies, for each sensor on every robot, required in order to maximize the positioning accuracy of the group. Simulation and experimental results are presented that demonstrate the applicability of this method and provide insight into the properties of the resource-constrained cooperative localization problem.

Original language	English (US)
Pages (from-to)	917-931
Number of pages	15
Journal	IEEE Transactions on Robotics
Volume	22
Issue number	5
DOIs	https://doi.org/10.1109/TRO.2006.878947
State	Published - Oct 2006

Bibliographical note

Funding Information:
Manuscript received July 28, 2005; revised February 18, 2006. This paper was recommended for publication by Associate Editor W. Burgard and Editor L. Parker upon evaluation of the reviewers’ comments. This work was supported in part by the University of Minnesota (DTC), in part by the Jet Propulsion Laboratory under Grants 1251073, 1260245, and 1263201, and in part by the National Science Foundation under ITR-0324864 and MRI-0420836. This paper was presented in part at the Robotics: Science and Systems Conference, Cambridge, MA, June 2005 The authors are with the Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455 USA (e-mail: mourikis@cs. umn.edu; stergios@cs.umn.edu). Digital Object Identifier 10.1109/TRO.2006.878947

Keywords

Multirobot localization
Resource-constrained localization
Robot formations
Semidefinite program
Sensor scheduling

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abstract = "This paper addresses the problem of resource allocation in formations of mobile robots localizing as a group. Each robot receives measurements from various sensors that provide relative (robot-to-robot) and absolute positioning information. Constraints on the sensors' bandwidth, as well as communication and processing requirements, limit the number of measurements that are available or can be processed at each time step. The localization uncertainty of the group, determined by the covariance matrix of the equivalent continuous-time system at steady state, is expressed as a function of the sensor measurements' frequencies. The trace of the weighted covariance matrix is selected as the optimization criterion, under linear constraints on the measuring frequency of each sensor and the cumulative rate of the extended Kalman filter updates. This formulation leads to a convex optimization problem (semidefinite program) whose solution provides the sensing frequencies, for each sensor on every robot, required in order to maximize the positioning accuracy of the group. Simulation and experimental results are presented that demonstrate the applicability of this method and provide insight into the properties of the resource-constrained cooperative localization problem.",

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Optimal sensor scheduling for resource-constrained localization of mobile robot formations

Abstract

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Keywords

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