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Article: A closed-loop bid adjustment approach to dynamic task allocation of robots

TitleA closed-loop bid adjustment approach to dynamic task allocation of robots
Authors
KeywordsAuction
Bid Adjustment
Dynamic Environments
Multi-Robot
Task Allocation
Issue Date2011
PublisherInternational Association of Engineers. The Journal's web site is located at http://www.engineeringletters.com/
Citation
Engineering Letters, 2011, v. 19 n. 4 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 aim to assemble robot team information at a single location to make practicable decisions on task allocation. However, a main deficiency of auction-based methods is that robots generally do not have sufficient information to estimate accurate and reliable bids to perform tasks, particularly in dynamic environments where there are operational uncertainties. 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 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 ssesses and records its performance to reflect the discrepancy between the submitted bid price and the corresponding actual cost of the task. A series of such performance records, with time-discounting factors, are taken into account to damp out fluctuations of bid adjustments. 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 bid adjustment mechanism.
Persistent Identifierhttp://hdl.handle.net/10722/155952
ISSN
2015 SCImago Journal Rankings: 0.241
References

 

DC FieldValueLanguage
dc.contributor.authorZhu, WKen_US
dc.contributor.authorChoi, SHen_US
dc.date.accessioned2012-08-08T08:38:35Z-
dc.date.available2012-08-08T08:38:35Z-
dc.date.issued2011en_US
dc.identifier.citationEngineering Letters, 2011, v. 19 n. 4en_US
dc.identifier.issn1816-093Xen_US
dc.identifier.urihttp://hdl.handle.net/10722/155952-
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 aim to assemble robot team information at a single location to make practicable decisions on task allocation. However, a main deficiency of auction-based methods is that robots generally do not have sufficient information to estimate accurate and reliable bids to perform tasks, particularly in dynamic environments where there are operational uncertainties. 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 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 ssesses and records its performance to reflect the discrepancy between the submitted bid price and the corresponding actual cost of the task. A series of such performance records, with time-discounting factors, are taken into account to damp out fluctuations of bid adjustments. 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 bid adjustment mechanism.en_US
dc.languageengen_US
dc.publisherInternational Association of Engineers. The Journal's web site is located at http://www.engineeringletters.com/en_US
dc.relation.ispartofEngineering Lettersen_US
dc.subjectAuctionen_US
dc.subjectBid Adjustmenten_US
dc.subjectDynamic Environmentsen_US
dc.subjectMulti-Roboten_US
dc.subjectTask Allocationen_US
dc.titleA closed-loop bid adjustment approach to dynamic task allocation of robotsen_US
dc.typeArticleen_US
dc.identifier.emailChoi, SH:shchoi@hkucc.hku.hken_US
dc.identifier.authorityChoi, SH=rp00109en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-81155153652en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-81155153652&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume19en_US
dc.identifier.issue4en_US
dc.publisher.placeHong Kongen_US
dc.identifier.scopusauthoridZhu, WK=7404232249en_US
dc.identifier.scopusauthoridChoi, SH=7408119615en_US

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