Manipulator-based grasping pose selection by means of task-objective optimisation

Richards, D; Paul, G; Webb, S; Kirchner, N

Manipulator-based grasping pose selection by means of task-objective optimisation

Richards, D Paul, G

Webb, S Kirchner, N

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the 2010 Australasian Conference on Robotics and Automation, ACRA 2010, 2010
Issue Date:: 2010-12-01

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Field	Value	Language
dc.contributor.author	Richards, D	en_US
dc.contributor.author	Paul, G https://orcid.org/0000-0002-3478-0020	en_US
dc.contributor.author	Webb, S	en_US
dc.contributor.author	Kirchner, N https://orcid.org/0000-0002-3018-992X	en_US
dc.date.issued	2010-12-01	en_US
dc.identifier.citation	Proceedings of the 2010 Australasian Conference on Robotics and Automation, ACRA 2010, 2010	en_US
dc.identifier.isbn	9780980740417	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16450
dc.description.abstract	This paper presents an alternative to inverse kinematics for mobile manipulator grasp pose selection which integrates obstacle avoidance and joint limit checking into the pose selection process. Given the Cartesian coordinates of an object in 3D space and its normal vector, end-effector pose objectives including collision checking and joint limit checks are used to create a series of cost functions based on sigmoid functions. These functions are optimised using Levenberg-Marquardt's algorithm to determine a valid pose for a given object. The proposed method has been shown to extend the workspace of the manipulator, eliminating the need for precomputed grasp sets and post pose selection collision checking and joint limit checks. This method has been successfully used on a 6 DOF manipulator both in simulation and in the real world environment.	en_US
dc.relation.ispartof	Proceedings of the 2010 Australasian Conference on Robotics and Automation, ACRA 2010	en_US
dc.title	Manipulator-based grasping pose selection by means of task-objective optimisation	en_US
dc.type	Conference Proceeding
utslib.for	090602 Control Systems, Robotics and Automation	en_US
dc.location.activity	Brisbane, Queensland, Australia	en_US
dc.location.activity	Sydney, Australia
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (Research)
pubs.organisational-group	/University of Technology Sydney/DVC (Research)/Institute For Sustainable Futures
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:

This paper presents an alternative to inverse kinematics for mobile manipulator grasp pose selection which integrates obstacle avoidance and joint limit checking into the pose selection process. Given the Cartesian coordinates of an object in 3D space and its normal vector, end-effector pose objectives including collision checking and joint limit checks are used to create a series of cost functions based on sigmoid functions. These functions are optimised using Levenberg-Marquardt's algorithm to determine a valid pose for a given object. The proposed method has been shown to extend the workspace of the manipulator, eliminating the need for precomputed grasp sets and post pose selection collision checking and joint limit checks. This method has been successfully used on a 6 DOF manipulator both in simulation and in the real world environment.

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http://hdl.handle.net/10453/16450