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ICRA
2009
IEEE

Cooperative multi-robot localization under communication constraints

9 years 8 months ago
Cooperative multi-robot localization under communication constraints
— This paper addresses the problem of cooperative localization (CL) under severe communication constraints. Specifically, we present minimum mean square error (MMSE) and maximum a posteriori (MAP) estimators that can process measurements quantized with as little as one bit per measurement. During CL, each robot quantizes and broadcasts its measurements and receives the quantized observations of its teammates. The quantization process is based on the appropriate selection of thresholds, computed using the current state estimates, that minimize the estimation error metric considered. Extensive simulations demonstrate that the proposed Iteratively-Quantized Extended Kalman filter (IQEKF) and the Iteratively Quantized MAP (IQMAP) estimator achieve performance indistinguishable of that of their real-valued counterparts (EKF and MAP, respectively) when using as few as 4 bits for quantizing each robot measurement.
Nikolas Trawny, Stergios I. Roumeliotis, Georgios
Added 23 May 2010
Updated 23 May 2010
Type Conference
Year 2009
Where ICRA
Authors Nikolas Trawny, Stergios I. Roumeliotis, Georgios B. Giannakis
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