A Bounded Uncertainty Approach to Multi-Robot Localization

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computational complexity
cooperative systems
linear programming
multi-robot systems
position control
sensor fusion
bearing measurement
bounded uncertainty approach
computational complexity
configuration space
convex polytopes
linear programming techniques
multirobot localization
multirobot team
range measurements
sensor error
sensor measurements
uncertainty estimation
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Spletzer, John R
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We offer a new approach to the multi-robot localization problem. Using an unknown-but-bounded model for sensor error, we are able to define convex polytopes in the configuration space of the robot team that represent the set of configurations consistent with all sensor measurements. Estimates for the uncertainty in various parameters of the team's configuration such as the absolute position of a single robot, or the relative positions of two or more nodes can be obtained by projecting this polytope onto appropriately chosen subspaces of the configuration space. We propose a novel approach to approximating these projections using linear programming techniques. The approach can handle both bearing and range measurements with a computational complexity scaling polynomially in the number of robots. Finally, the workload is readily distributed - requiring only the communication of sensor measurements between robots. We provide simulation results for this approach implemented on a multi-robot team.

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2003-10-27
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Departmental Papers (CIS)
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2023-05-16T21:43:21.000
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Copyright 2003 IEEE. Reprinted from IEEE/RSJ International Conference on Intelligent Robots and Systems, 2003 (IROS 2003) Volume 2, pages 1258-1264. Publisher URL: http://ieeexplore.ieee.org/xpl/tocresult.jsp?isNumber=27959&page=2 This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
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