Adaptive Coverage Control for Heterogeneous Mobile Sensor Networks in an Unknown Environment

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

View graph of relations

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publication2023 62nd IEEE Conference on Decision and Contro (CDC)
PublisherInstitute of Electrical and Electronics Engineers, Inc.
Pages3154-3159
ISBN (electronic)9798350301243
ISBN (print)9798350301250
Publication statusPublished - Dec 2023

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (electronic)2576-2370

Conference

Title62nd IEEE Conference on Decision and Control (CDC 2023)
LocationMarina Bay Sands
PlaceSingapore
Period13 - 15 December 2023

Abstract

This article addresses the coverage control problems for heterogeneous mobile sensor networks (MSNs) in an environment with unknown event density functions. In contrast to existing works, unknown heterogeneous sensing abilities of the mobile sensor network (MSN) are considered by leveraging a weighted Voronoi diagram, namely, the Power diagram. To guarantee that the time-varying Power diagram converges to that defined by the true sensing weights, an online weight learning law is designed. Moreover, to handle certain applications such as forest fire investigation or nuclear radiation leakage mapping where the density information for the events of interest is not known to the MSN, an adaptive law is presented so that the event density approximation of each sensor converges to the real one along its trajectory. In addition, a move-to-centroid control law is proposed to drive the MSN to a near-optimal coverage configuration as time goes to infinity. Finally, the effectiveness of the proposed approach is illustrated by an example. © 2023 IEEE.

Citation Format(s)

Adaptive Coverage Control for Heterogeneous Mobile Sensor Networks in an Unknown Environment. / Zheng, Boyin; Liu, Lu.
2023 62nd IEEE Conference on Decision and Contro (CDC). Institute of Electrical and Electronics Engineers, Inc., 2023. p. 3154-3159 (Proceedings of the IEEE Conference on Decision and Control).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review