Angle-Encoded Swarm Optimization for UAV Formation Path Planning

Hoang, VT; Phung, MD; Dinh, TH; Ha, QP

Angle-Encoded Swarm Optimization for UAV Formation Path Planning

Hoang, VT

Phung, MD

Dinh, TH Ha, QP

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Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Intelligent Robots and Systems, 2018, pp. 5239 - 5244
Issue Date:: 2018-12-27

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Field	Value	Language
dc.contributor.author	Hoang, VT https://orcid.org/0000-0001-5557-5571	en_US
dc.contributor.author	Phung, MD https://orcid.org/0000-0002-8870-5114	en_US
dc.contributor.author	Dinh, TH	en_US
dc.contributor.author	Ha, QP https://orcid.org/0000-0003-0978-1758	en_US
dc.date.available	2020-10-01T19:05:55Z
dc.date.issued	2018-12-27	en_US
dc.identifier.citation	IEEE International Conference on Intelligent Robots and Systems, 2018, pp. 5239 - 5244	en_US
dc.identifier.isbn	9781538680940	en_US
dc.identifier.issn	2153-0858	en_US
dc.identifier.uri	http://hdl.handle.net/10453/128038
dc.description.abstract	© 2018 IEEE. This paper presents a novel and feasible path planning technique for a group of unmanned aerial vehicles (DAVs) conducting surface inspection of infrastructure. The ultimate goal is to minimise the travel distance of DAVs while simultaneously avoid obstacles, and maintain altitude constraints as well as the shape of the UAV formation. A multiple-objective optimisation algorithm, called the Angle-encoded Particle Swarm Optimization (θ- PSO) algorithm, is proposed to accelerate the swarm convergence with angular velocity and position being used for the location of particles. The whole formation is modelled as a virtual rigid body and controlled to maintain a desired geometric shape among the paths created while the centroid of the group follows a pre-determined trajectory. Based on the testbed of 3DR Solo drones equipped with a proprietary Mission Planner, and the Internet-of- Things (loT) for multi-directional transmission and reception of data between the DAV s, extensive experiments have been conducted for triangular formation maintenance along a monorail bridge. The results obtained confirm the feasibility and effectiveness of the proposed approach.	en_US
dc.relation.ispartof	IEEE International Conference on Intelligent Robots and Systems	en_US
dc.relation.isbasedon	10.1109/IROS.2018.8593930	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Angle-Encoded Swarm Optimization for UAV Formation Path Planning	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	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/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CBI - Centre for Built Infrastructure
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access	*
pubs.publication-status	Published	en_US

Abstract:

© 2018 IEEE. This paper presents a novel and feasible path planning technique for a group of unmanned aerial vehicles (DAVs) conducting surface inspection of infrastructure. The ultimate goal is to minimise the travel distance of DAVs while simultaneously avoid obstacles, and maintain altitude constraints as well as the shape of the UAV formation. A multiple-objective optimisation algorithm, called the Angle-encoded Particle Swarm Optimization (θ- PSO) algorithm, is proposed to accelerate the swarm convergence with angular velocity and position being used for the location of particles. The whole formation is modelled as a virtual rigid body and controlled to maintain a desired geometric shape among the paths created while the centroid of the group follows a pre-determined trajectory. Based on the testbed of 3DR Solo drones equipped with a proprietary Mission Planner, and the Internet-of- Things (loT) for multi-directional transmission and reception of data between the DAV s, extensive experiments have been conducted for triangular formation maintenance along a monorail bridge. The results obtained confirm the feasibility and effectiveness of the proposed approach.

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http://hdl.handle.net/10453/128038