Abstract
In this paper, we propose distributed Gaussian process regression for resource-constrained mobile sensor networks under localization uncertainty. The proposed distributed algorithm, which combines Jacobi over-relaxation (JOR) and discrete-time average consensus (DAC), can effectively handle localization uncertainty as well as limited communication ranges and computation capabilities of mobile sensor networks. The performance of the proposed method is verified in numerical simulations against the centralized maximum a posteriori solution and the quick-and-dirty solution. We show that the proposed method outperforms the quick-and-dirty solution and achieves an accuracy comparable to the centralized solution.
| Original language | English |
|---|---|
| Title of host publication | 2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 4766-4771 |
| Number of pages | 6 |
| ISBN (Print) | 9781467357173 |
| DOIs | |
| Publication status | Published - 2013 Jan 1 |
| Event | 52nd IEEE Conference on Decision and Control, CDC 2013 - Florence, Italy Duration: 2013 Dec 10 → 2013 Dec 13 |
Publication series
| Name | Proceedings of the IEEE Conference on Decision and Control |
|---|---|
| ISSN (Print) | 0191-2216 |
Other
| Other | 52nd IEEE Conference on Decision and Control, CDC 2013 |
|---|---|
| Country | Italy |
| City | Florence |
| Period | 13/12/10 → 13/12/13 |
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All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Modelling and Simulation
- Control and Optimization
Cite this
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Distributed gaussian process regression for mobile sensor networks under localization uncertainty. / Choi, Sungjoon; Jadaliha, Mahdi; Choi, Jongeun; Oh, Songhwai.
2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013. Institute of Electrical and Electronics Engineers Inc., 2013. p. 4766-4771 6760636 (Proceedings of the IEEE Conference on Decision and Control).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Distributed gaussian process regression for mobile sensor networks under localization uncertainty
AU - Choi, Sungjoon
AU - Jadaliha, Mahdi
AU - Choi, Jongeun
AU - Oh, Songhwai
PY - 2013/1/1
Y1 - 2013/1/1
N2 - In this paper, we propose distributed Gaussian process regression for resource-constrained mobile sensor networks under localization uncertainty. The proposed distributed algorithm, which combines Jacobi over-relaxation (JOR) and discrete-time average consensus (DAC), can effectively handle localization uncertainty as well as limited communication ranges and computation capabilities of mobile sensor networks. The performance of the proposed method is verified in numerical simulations against the centralized maximum a posteriori solution and the quick-and-dirty solution. We show that the proposed method outperforms the quick-and-dirty solution and achieves an accuracy comparable to the centralized solution.
AB - In this paper, we propose distributed Gaussian process regression for resource-constrained mobile sensor networks under localization uncertainty. The proposed distributed algorithm, which combines Jacobi over-relaxation (JOR) and discrete-time average consensus (DAC), can effectively handle localization uncertainty as well as limited communication ranges and computation capabilities of mobile sensor networks. The performance of the proposed method is verified in numerical simulations against the centralized maximum a posteriori solution and the quick-and-dirty solution. We show that the proposed method outperforms the quick-and-dirty solution and achieves an accuracy comparable to the centralized solution.
UR - http://www.scopus.com/inward/record.url?scp=84902318747&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84902318747&partnerID=8YFLogxK
U2 - 10.1109/CDC.2013.6760636
DO - 10.1109/CDC.2013.6760636
M3 - Conference contribution
AN - SCOPUS:84902318747
SN - 9781467357173
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 4766
EP - 4771
BT - 2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013
PB - Institute of Electrical and Electronics Engineers Inc.
ER -