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Conference Paper: An auction-based approach with closed-loop bid adjustment to dynamic task allocation in robot teams

TitleAn auction-based approach with closed-loop bid adjustment to dynamic task allocation in robot teams
Authors
KeywordsAuction
Bid adjustment
Dynamic environments
Multi-robot
Task allocation
Issue Date2011
PublisherIAENG.
Citation
The World Congress on Engineering (WCE 2011), London, U.K., 6-8 July 2011. In Proceedings of WCE, 2011, v. 2, p. 1061-1066 How to Cite?
AbstractDynamic task allocation is among the most difficult issues in multi-robot coordination, although it is imperative for a multitude of applications. Auction-based approaches are popular methods that allocate tasks to robots by assembling team information at a single location to make practicable decisions. However, a main deficiency of auction-based methods is that robots generally do not have sufficient information to estimate reliable bids to perform tasks, particularly in dynamic environments. While some techniques have been developed to improve bidding, they are mostly open-looped without feed-back adjustments to tune the bid prices for subsequent tasks of the same type. Robots' bids, if not assessed and adjusted accordingly, may not be trustworthy and would indeed impede team performance. To address this issue, we propose a closed-loop bid adjustment mechanism for auction-based multi-robot task allocation, with an aim to evaluate and improve robots' bids, and hence enhance the overall team performance. Each robot in a team maintains and uses its own track record as closed-loop feedback information to adjust and improve its bid prices. After a robot has completed a task, it assesses and records its performance to reflect the discrepancy between the bid price and the actual cost of the task. Such performance records, with time-discounting factors, are taken into account to damp out fluctuations of bid prices. Adopting this adjustment mechanism, a task would be more likely allocated to a competent robot that submits a more accurate bid price, and hence improve the overall team performance. Simulation of task allocation of free-range automated guided vehicles serving at a container terminal is presented to demonstrate the effectiveness of the adjustment mechanism.
Persistent Identifierhttp://hdl.handle.net/10722/137737
ISBN
References

 

DC FieldValueLanguage
dc.contributor.authorZhu, WKen_HK
dc.contributor.authorChoi, SHen_HK
dc.date.accessioned2011-08-26T14:32:39Z-
dc.date.available2011-08-26T14:32:39Z-
dc.date.issued2011en_HK
dc.identifier.citationThe World Congress on Engineering (WCE 2011), London, U.K., 6-8 July 2011. In Proceedings of WCE, 2011, v. 2, p. 1061-1066en_HK
dc.identifier.isbn978-988-19251-4-5en_US
dc.identifier.urihttp://hdl.handle.net/10722/137737-
dc.description.abstractDynamic task allocation is among the most difficult issues in multi-robot coordination, although it is imperative for a multitude of applications. Auction-based approaches are popular methods that allocate tasks to robots by assembling team information at a single location to make practicable decisions. However, a main deficiency of auction-based methods is that robots generally do not have sufficient information to estimate reliable bids to perform tasks, particularly in dynamic environments. While some techniques have been developed to improve bidding, they are mostly open-looped without feed-back adjustments to tune the bid prices for subsequent tasks of the same type. Robots' bids, if not assessed and adjusted accordingly, may not be trustworthy and would indeed impede team performance. To address this issue, we propose a closed-loop bid adjustment mechanism for auction-based multi-robot task allocation, with an aim to evaluate and improve robots' bids, and hence enhance the overall team performance. Each robot in a team maintains and uses its own track record as closed-loop feedback information to adjust and improve its bid prices. After a robot has completed a task, it assesses and records its performance to reflect the discrepancy between the bid price and the actual cost of the task. Such performance records, with time-discounting factors, are taken into account to damp out fluctuations of bid prices. Adopting this adjustment mechanism, a task would be more likely allocated to a competent robot that submits a more accurate bid price, and hence improve the overall team performance. Simulation of task allocation of free-range automated guided vehicles serving at a container terminal is presented to demonstrate the effectiveness of the adjustment mechanism.en_HK
dc.languageengen_US
dc.publisherIAENG.en_US
dc.relation.ispartofProceedings of the World Congress on Engineeringen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectAuctionen_HK
dc.subjectBid adjustmenten_HK
dc.subjectDynamic environmentsen_HK
dc.subjectMulti-roboten_HK
dc.subjectTask allocationen_HK
dc.titleAn auction-based approach with closed-loop bid adjustment to dynamic task allocation in robot teamsen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=978-988-19251-4-5&volume=2&spage=1061&epage=1066&date=2011&atitle=An+auction-based+approach+with+closed-loop+bid+adjustment+to+dynamic+task+allocation+in+robot+teamsen_US
dc.identifier.emailChoi, SH:shchoi@hkucc.hku.hken_HK
dc.identifier.authorityChoi, SH=rp00109en_HK
dc.description.naturepostprint-
dc.identifier.scopuseid_2-s2.0-80755174464en_HK
dc.identifier.hkuros190923en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80755174464&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume2en_HK
dc.identifier.spage1061en_HK
dc.identifier.epage1066en_HK
dc.publisher.placeUnited Kingdom-
dc.description.otherThe World Congress on Engineering (WCE 2011), London, U.K., 6-8 July 2011. In Proceedings of WCE, 2011, v. 2, p. 1061-1066-
dc.identifier.scopusauthoridZhu, WK=7404232249en_HK
dc.identifier.scopusauthoridChoi, SH=7408119615en_HK

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