DocumentCode :
663830
Title :
Sustainable robot foraging: Adaptive fine-grained multi-robot task allocation for maximum sustainable yield of biological resources
Author :
Zhao Song ; Vaughan, Richard T.
Author_Institution :
Sch. of Comput. Sci., Simon Fraser Univ., Burnaby, BC, Canada
fYear :
2013
fDate :
3-7 Nov. 2013
Firstpage :
3309
Lastpage :
3316
Abstract :
We introduce the concept of Maximum Sustainable Yield (MSY) to the context of autonomous robot foraging. MSY is an optimal approach to the problem of maximizing sustainable foraging where the resources harvested are replenished by logistic growth, e.g. living things. Over-harvesting reduces both the instantaneous resource availability and growth rate, and above some threshold will permanently deplete resources. Under-harvesting is sustainable, but fails to maximally exploit the resources. We describe a system model and use it to determine the optimal allocation of robot work to resource-producing `patches´. We give a practical illustration of a troublesome feature of MSY: it is too sensitive for a fixed allocation to be sustainable in practice. We show how to centrally allocate a number of robots to each patch, and then locally adapt the work rate of each robot to achieve sustainable and near-optimal foraging. This is the first study of robot foraging where the robots´ activity modifies the productivity and sustainability of the environment.
Keywords :
agricultural machinery; mobile robots; multi-robot systems; telerobotics; adaptive fine-grained multirobot task allocation; autonomous robot foraging; biological resources; logistic growth; maximum sustainable yield; near-optimal foraging; sustainable robot foraging; Logistics; Resource management; Robot sensing systems; Sociology; Statistics; Switching circuits;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on
Conference_Location :
Tokyo
ISSN :
2153-0858
Type :
conf
DOI :
10.1109/IROS.2013.6696827
Filename :
6696827
Link To Document :
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