Optimal coordination of mobile sensor networks using Gaussian processes

Yunfei Xu; Jongeun Choi

doi:10.1115/DSCC2009-2677

Optimal coordination of mobile sensor networks using Gaussian processes

Yunfei Xu, Jongeun Choi

Department of Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we introduce a family of spatio-temporal Gaussian processes specified by a class of covariance functions. Nonparametric prediction based on truncated observations is proposed for mobile sensor networks with limited memory and computational power. We show that there is a trade-off between precision and efficiency when prediction based on trun-cated observations is used. Next, we propose both centralized and distributed navigation strategies for mobile sensor networks to move in order to reduce prediction error variances at positions of interest. Simulation results demonstrate the effectiveness of the proposed schemes.

Original language	English
Title of host publication	Proceedings of the ASME Dynamic Systems and Control Conference 2009, DSCC2009
Publisher	American Society of Mechanical Engineers (ASME)
Pages	1347-1354
Number of pages	8
Edition	PART B
ISBN (Print)	9780791848920
DOIs	https://doi.org/10.1115/DSCC2009-2677
Publication status	Published - 2010
Event	2009 ASME Dynamic Systems and Control Conference, DSCC2009 - Hollywood, CA, United States Duration: 2009 Oct 12 → 2009 Oct 14

Publication series

Name	Proceedings of the ASME Dynamic Systems and Control Conference 2009, DSCC2009
Number	PART B

Other

Other	2009 ASME Dynamic Systems and Control Conference, DSCC2009
Country/Territory	United States
City	Hollywood, CA
Period	09/10/12 → 09/10/14

All Science Journal Classification (ASJC) codes

Control and Systems Engineering

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10.1115/DSCC2009-2677

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Xu, Y., & Choi, J. (2010). Optimal coordination of mobile sensor networks using Gaussian processes. In Proceedings of the ASME Dynamic Systems and Control Conference 2009, DSCC2009 (PART B ed., pp. 1347-1354). (Proceedings of the ASME Dynamic Systems and Control Conference 2009, DSCC2009; No. PART B). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DSCC2009-2677

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title = "Optimal coordination of mobile sensor networks using Gaussian processes",

abstract = "In this paper, we introduce a family of spatio-temporal Gaussian processes specified by a class of covariance functions. Nonparametric prediction based on truncated observations is proposed for mobile sensor networks with limited memory and computational power. We show that there is a trade-off between precision and efficiency when prediction based on trun-cated observations is used. Next, we propose both centralized and distributed navigation strategies for mobile sensor networks to move in order to reduce prediction error variances at positions of interest. Simulation results demonstrate the effectiveness of the proposed schemes.",

author = "Yunfei Xu and Jongeun Choi",

year = "2010",

doi = "10.1115/DSCC2009-2677",

language = "English",

isbn = "9780791848920",

series = "Proceedings of the ASME Dynamic Systems and Control Conference 2009, DSCC2009",

publisher = "American Society of Mechanical Engineers (ASME)",

number = "PART B",

pages = "1347--1354",

booktitle = "Proceedings of the ASME Dynamic Systems and Control Conference 2009, DSCC2009",

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note = "2009 ASME Dynamic Systems and Control Conference, DSCC2009 ; Conference date: 12-10-2009 Through 14-10-2009",

}

Xu, Y & Choi, J 2010, Optimal coordination of mobile sensor networks using Gaussian processes. in Proceedings of the ASME Dynamic Systems and Control Conference 2009, DSCC2009. PART B edn, Proceedings of the ASME Dynamic Systems and Control Conference 2009, DSCC2009, no. PART B, American Society of Mechanical Engineers (ASME), pp. 1347-1354, 2009 ASME Dynamic Systems and Control Conference, DSCC2009, Hollywood, CA, United States, 09/10/12. https://doi.org/10.1115/DSCC2009-2677

Optimal coordination of mobile sensor networks using Gaussian processes. / Xu, Yunfei; Choi, Jongeun.

Proceedings of the ASME Dynamic Systems and Control Conference 2009, DSCC2009. PART B. ed. American Society of Mechanical Engineers (ASME), 2010. p. 1347-1354 (Proceedings of the ASME Dynamic Systems and Control Conference 2009, DSCC2009; No. PART B).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - In this paper, we introduce a family of spatio-temporal Gaussian processes specified by a class of covariance functions. Nonparametric prediction based on truncated observations is proposed for mobile sensor networks with limited memory and computational power. We show that there is a trade-off between precision and efficiency when prediction based on trun-cated observations is used. Next, we propose both centralized and distributed navigation strategies for mobile sensor networks to move in order to reduce prediction error variances at positions of interest. Simulation results demonstrate the effectiveness of the proposed schemes.

AB - In this paper, we introduce a family of spatio-temporal Gaussian processes specified by a class of covariance functions. Nonparametric prediction based on truncated observations is proposed for mobile sensor networks with limited memory and computational power. We show that there is a trade-off between precision and efficiency when prediction based on trun-cated observations is used. Next, we propose both centralized and distributed navigation strategies for mobile sensor networks to move in order to reduce prediction error variances at positions of interest. Simulation results demonstrate the effectiveness of the proposed schemes.

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Optimal coordination of mobile sensor networks using Gaussian processes

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