Task oriented area partitioning and allocation for optimal operation of multiple industrial robots in unstructured environments

Hassan, M; Liu, D; Huang, S; Dissanayake, G

Task oriented area partitioning and allocation for optimal operation of multiple industrial robots in unstructured environments

Hassan, M

Liu, D

Huang, S

Dissanayake, G

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Publication Type:: Conference Proceeding
Citation:: 2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014, 2014, pp. 1184 - 1189
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Hassan, M https://orcid.org/0000-0002-0824-3272	en_US
dc.contributor.author	Liu, D https://orcid.org/0000-0002-1581-5582	en_US
dc.contributor.author	Huang, S https://orcid.org/0000-0002-6124-4178	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014, 2014, pp. 1184 - 1189	en_US
dc.identifier.isbn	9781479951994	en_US
dc.identifier.uri	http://hdl.handle.net/10453/33422
dc.description.abstract	© 2014 IEEE. When multiple industrial robots are deployed in field applications such as grit blasting and spray painting of steel bridges, the environments are unstructured for robot operation and the robot positions may not be arranged accurately. Coordination of these multiple robots to maximize productivity through area partitioning and allocation is crucial. This paper presents a novel approach to area partitioning and allocation by utilizing multiobjective optimization and voronoi partitioning. Multiobjective optimization is used to minimize: (1) completion time, (2) proximity of the allocated area to the robot, and (3) the torque experienced by each joint of the robot during task execution. Seed points of the voronoi graph for voronoi partitioning are designed to be the design variables of the multiobjective optimization algorithm. Results of three different simulation scenarios are presented to demonstrate the effectiveness of the proposed approach and the advantage of incorporating robots' torque capacity.	en_US
dc.relation.ispartof	2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014	en_US
dc.relation.isbasedon	10.1109/ICARCV.2014.7064473	en_US
dc.title	Task oriented area partitioning and allocation for optimal operation of multiple industrial robots in unstructured environments	en_US
dc.type	Conference Proceeding
utslib.for	0913 Mechanical Engineering	en_US
dc.location.activity	Marina Bay Sands, Singapore
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 Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

© 2014 IEEE. When multiple industrial robots are deployed in field applications such as grit blasting and spray painting of steel bridges, the environments are unstructured for robot operation and the robot positions may not be arranged accurately. Coordination of these multiple robots to maximize productivity through area partitioning and allocation is crucial. This paper presents a novel approach to area partitioning and allocation by utilizing multiobjective optimization and voronoi partitioning. Multiobjective optimization is used to minimize: (1) completion time, (2) proximity of the allocated area to the robot, and (3) the torque experienced by each joint of the robot during task execution. Seed points of the voronoi graph for voronoi partitioning are designed to be the design variables of the multiobjective optimization algorithm. Results of three different simulation scenarios are presented to demonstrate the effectiveness of the proposed approach and the advantage of incorporating robots' torque capacity.

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http://hdl.handle.net/10453/33422