Adaptive Source Localization Based Station Keeping of Autonomous Vehicles

Handle URI:
http://hdl.handle.net/10754/623707
Title:
Adaptive Source Localization Based Station Keeping of Autonomous Vehicles
Authors:
Guler, Samet; Fidan, Baris; Dasgupta, Soura; Anderson, Brian D.O.; Shames, Iman ( 0000-0001-7308-3546 )
Abstract:
We study the problem of driving a mobile sensory agent to a target whose location is specied only in terms of the distances to a set of sensor stations or beacons. The beacon positions are unknown, but the agent can continuously measure its distances to them as well as its own position. This problem has two particular applications: (1) capturing a target signal source whose distances to the beacons are measured by these beacons and broadcasted to a surveillance agent, (2) merging a single agent to an autonomous multi-agent system so that the new agent is positioned at desired distances from the existing agents. The problem is solved using an adaptive control framework integrating a parameter estimator producing beacon location estimates, and an adaptive motion control law fed by these estimates to steer the agent toward the target. For location estimation, a least-squares adaptive law is used. The motion control law aims to minimize a convex cost function with unique minimizer at the target location, and is further augmented for persistence of excitation. Stability and convergence analysis is provided, as well as simulation results demonstrating performance and transient behavior.
KAUST Department:
Electrical Engineering Program
Citation:
Guler S, Fidan B, Dasgupta S, Anderson BDO, Shames I (2016) Adaptive Source Localization Based Station Keeping of Autonomous Vehicles. IEEE Transactions on Automatic Control: 1–1. Available: http://dx.doi.org/10.1109/tac.2016.2621764.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Transactions on Automatic Control
Issue Date:
26-Oct-2016
DOI:
10.1109/tac.2016.2621764
Type:
Article
ISSN:
0018-9286; 1558-2523
Sponsors:
This work is supported by the Canadian NSERC Discovery Grant 116806. This work is supported in part by US NSF grants EPS-1101284, CNS-1329657, CCF-1302456, ONR grant N00014-13-1-0202 and under the Thousand Talents Program of the State and Shandong Province, administered by the Shandong Academy of Sciences, China.
Additional Links:
http://ieeexplore.ieee.org/document/7707439/
Appears in Collections:
Articles; Electrical Engineering Program

Full metadata record

DC FieldValue Language
dc.contributor.authorGuler, Sameten
dc.contributor.authorFidan, Barisen
dc.contributor.authorDasgupta, Souraen
dc.contributor.authorAnderson, Brian D.O.en
dc.contributor.authorShames, Imanen
dc.date.accessioned2017-05-25T10:55:13Z-
dc.date.available2017-05-25T10:55:13Z-
dc.date.issued2016-10-26en
dc.identifier.citationGuler S, Fidan B, Dasgupta S, Anderson BDO, Shames I (2016) Adaptive Source Localization Based Station Keeping of Autonomous Vehicles. IEEE Transactions on Automatic Control: 1–1. Available: http://dx.doi.org/10.1109/tac.2016.2621764.en
dc.identifier.issn0018-9286en
dc.identifier.issn1558-2523en
dc.identifier.doi10.1109/tac.2016.2621764en
dc.identifier.urihttp://hdl.handle.net/10754/623707-
dc.description.abstractWe study the problem of driving a mobile sensory agent to a target whose location is specied only in terms of the distances to a set of sensor stations or beacons. The beacon positions are unknown, but the agent can continuously measure its distances to them as well as its own position. This problem has two particular applications: (1) capturing a target signal source whose distances to the beacons are measured by these beacons and broadcasted to a surveillance agent, (2) merging a single agent to an autonomous multi-agent system so that the new agent is positioned at desired distances from the existing agents. The problem is solved using an adaptive control framework integrating a parameter estimator producing beacon location estimates, and an adaptive motion control law fed by these estimates to steer the agent toward the target. For location estimation, a least-squares adaptive law is used. The motion control law aims to minimize a convex cost function with unique minimizer at the target location, and is further augmented for persistence of excitation. Stability and convergence analysis is provided, as well as simulation results demonstrating performance and transient behavior.en
dc.description.sponsorshipThis work is supported by the Canadian NSERC Discovery Grant 116806. This work is supported in part by US NSF grants EPS-1101284, CNS-1329657, CCF-1302456, ONR grant N00014-13-1-0202 and under the Thousand Talents Program of the State and Shandong Province, administered by the Shandong Academy of Sciences, China.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/document/7707439/en
dc.rights(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.subjectOptimizationen
dc.subjectAdaptive Controlen
dc.subjectAutonomous Robotsen
dc.subjectCooperative Controlen
dc.subjectSensor Networksen
dc.titleAdaptive Source Localization Based Station Keeping of Autonomous Vehiclesen
dc.typeArticleen
dc.contributor.departmentElectrical Engineering Programen
dc.identifier.journalIEEE Transactions on Automatic Controlen
dc.eprint.versionPost-printen
dc.contributor.institutionDepartment of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON, N2L 3G1 Canadaen
dc.contributor.institutionDepartment of Electrical and Computer Engineering, University of Iowa, Iowa City, IA, 52242 USAen
dc.contributor.institutionShandong Computer Science Center (National Supercomputer Center in Jinan), Shandong Provincial Key Laboratory of Computer Networksen
dc.contributor.institutionResearch School of Information Sciences and Engineering, Australian National University, Canberra, ACT, 0200 Australiaen
dc.contributor.institutionNational ICT Australia (NICTA), NSW 2601, Canberra, Australiaen
dc.contributor.institutionDepartment of Electrical and Electronic Engineering, University of Melbourne, Melbourne, VIC 3010, Australiaen
kaust.authorGuler, Sameten
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