A hybrid estimation framework for cooperative localization under communication constraints

Esha D. Nerurkar, Ke X. Zhou, Stergios I. Roumeliotis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

In this paper, we consider the problem of multi-centralized Cooperative Localization (CL) under severe communication constraints, i.e., when each robot can communicate only a single bit per real-valued (analog) measurement. Existing approaches, such as those based on the Sign-of-Innovation Kalman filter (SOI-KF) and its variants, require each robot to process quantized versions of both its local (i.e., recorded by its own sensors) and remote (i.e., collected by other robots) measurements. This results in suboptimal performance since each robot has to discard information that is available in its own analog measurements. To address this limitation, we introduce a novel hybrid estimation scheme that enables each robot to process both quantized (from remote sensors) and analog (from its own sensors) measurements. Specifically, we first present the hybrid (H)-SOI-KF, a direct extension of the SOI-KF, for processing both types of measurements. Secondly, we introduce the modified (M)H-SOI-KF, that uses an asymmetric encoding/decoding scheme to incorporate additional information during quantization (based on the hybrid estimates locally available to each robot), resulting in substantial accuracy improvement. Lastly, we present extensive simulations which demonstrate that both hybrid estimators not only outperform the SOI-KF, but also achieve accuracy comparable to that of the standard (analog) centralized Kalman filter.

Original languageEnglish (US)
Title of host publicationIROS'11 - 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems
Subtitle of host publicationCelebrating 50 Years of Robotics
Pages502-509
Number of pages8
DOIs
StatePublished - Dec 29 2011
Event2011 IEEE/RSJ International Conference on Intelligent Robots and Systems: Celebrating 50 Years of Robotics, IROS'11 - San Francisco, CA, United States
Duration: Sep 25 2011Sep 30 2011

Publication series

NameIEEE International Conference on Intelligent Robots and Systems

Other

Other2011 IEEE/RSJ International Conference on Intelligent Robots and Systems: Celebrating 50 Years of Robotics, IROS'11
CountryUnited States
CitySan Francisco, CA
Period9/25/119/30/11

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    Nerurkar, E. D., Zhou, K. X., & Roumeliotis, S. I. (2011). A hybrid estimation framework for cooperative localization under communication constraints. In IROS'11 - 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems: Celebrating 50 Years of Robotics (pp. 502-509). [6048871] (IEEE International Conference on Intelligent Robots and Systems). https://doi.org/10.1109/IROS.2011.6048871