Multi-robot coverage planning with resource constraints for horticulture applications

Patten, T; Fitch, R; Sukkarieh, S

Multi-robot coverage planning with resource constraints for horticulture applications

Patten, T Fitch, R

Sukkarieh, S

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Publication Type:: Conference Proceeding
Citation:: Acta Horticulturae, 2016, 1130 pp. 655 - 661
Issue Date:: 2016-12-09

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Field	Value	Language
dc.contributor.author	Patten, T	en_US
dc.contributor.author	Fitch, R https://orcid.org/0000-0003-2215-5188	en_US
dc.contributor.author	Sukkarieh, S	en_US
dc.date.issued	2016-12-09	en_US
dc.identifier.citation	Acta Horticulturae, 2016, 1130 pp. 655 - 661	en_US
dc.identifier.isbn	9789462611443	en_US
dc.identifier.issn	0567-7572	en_US
dc.identifier.uri	http://hdl.handle.net/10453/99727
dc.description.abstract	A multi-robot system is a team of autonomous robots that work together to perform a given task. Multi-robot systems have great potential for use in horticulture applications. Robots have the potential to perform crop surveillance, efficiently apply fertiliser and chemical inputs, and perform weeding and harvesting. In all of these tasks, robots must visit many trees or plants over a large area in a time-sensitive manner. Multi-robot systems are appropriate because many robots can work efficiently in parallel. However, a fundamental challenge to be addressed is how to coordinate the motion of many robots while also respecting resource constraints such as limited energy storage, liquid payload, and harvested product storage. The algorithmic problem of multi-robot coverage planning with resource constraints is similar to the NP-hard vehicle routing problem, but the computational complexity of general resource-constrained coverage remains unknown. We show that one variant of this problem, coverage with fixed replenishment stations and zero queuing time, can be solved in polynomial time using area partitioning and graph search. We present algorithms and analysis for this variant, and demonstrate the behaviour of our algorithms in simulation experiments with up to 100 robots. The robots cover a large area organised as a collection of sub-areas with defined boundaries and row orientations. Robots plan to visit one of several possible replenishment stations in order to satisfy resource constraints. Each robot may replenish itself multiple times throughout its mission. This work is practically applicable to systems where refill time is short relative to working time.	en_US
dc.relation.ispartof	Acta Horticulturae	en_US
dc.relation.isbasedon	10.17660/ActaHortic.2016.1130.97	en_US
dc.subject.classification	Plant Biology & Botany	en_US
dc.title	Multi-robot coverage planning with resource constraints for horticulture applications	en_US
dc.type	Conference Proceeding
utslib.citation.volume	1130	en_US
utslib.for	0706 Horticultural Production	en_US
utslib.for	0607 Plant Biology	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	1130	en_US

Abstract:

A multi-robot system is a team of autonomous robots that work together to perform a given task. Multi-robot systems have great potential for use in horticulture applications. Robots have the potential to perform crop surveillance, efficiently apply fertiliser and chemical inputs, and perform weeding and harvesting. In all of these tasks, robots must visit many trees or plants over a large area in a time-sensitive manner. Multi-robot systems are appropriate because many robots can work efficiently in parallel. However, a fundamental challenge to be addressed is how to coordinate the motion of many robots while also respecting resource constraints such as limited energy storage, liquid payload, and harvested product storage. The algorithmic problem of multi-robot coverage planning with resource constraints is similar to the NP-hard vehicle routing problem, but the computational complexity of general resource-constrained coverage remains unknown. We show that one variant of this problem, coverage with fixed replenishment stations and zero queuing time, can be solved in polynomial time using area partitioning and graph search. We present algorithms and analysis for this variant, and demonstrate the behaviour of our algorithms in simulation experiments with up to 100 robots. The robots cover a large area organised as a collection of sub-areas with defined boundaries and row orientations. Robots plan to visit one of several possible replenishment stations in order to satisfy resource constraints. Each robot may replenish itself multiple times throughout its mission. This work is practically applicable to systems where refill time is short relative to working time.

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http://hdl.handle.net/10453/99727