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Visual motor control of a 7DOF redundant manipulator using redundancy preserving learning network

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Kumar, Swagat, Patcaikani, Premkumar, Dutta, Ashish and Behera, Laxmidhar (2009) Visual motor control of a 7DOF redundant manipulator using redundancy preserving learning network. Robotica, 28 . pp. 795-810. [Journal article]

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URL: http://journals.cambridge.org/action/displayFulltext?type=1&fid=7881955&jid=ROB&volumeId=28&issueId=06&aid=7881953

DOI: 10.1017/S026357470999049X

Abstract

This paper deals with the design and implementation of avisual kinematic control scheme for a redundant manipulator.The inverse kinematic map for a redundant manipulatoris a one-to-many relation problem; i.e. for each Cartesianposition, multiple joint angle vectors are associated. Whenthis inverse kinematic relation is learnt using existinglearning schemes, a single inverse kinematic solution isachieved, although the manipulator is redundant. Thus anew redundancy preserving network based on the selforganizingmap (SOM) has been proposed to learn theone-to-many relation using sub-clustering in joint anglespace. The SOM network resolves redundancy using threecriteria, namely lazy arm movement, minimum angle normand minimum condition number of image Jacobian matrix.The proposed scheme is able to guide the manipulator endeffectortowards the desired target within 1-mm positioningaccuracy without exceeding physical joint angle limits. Anew concept of neighbourhood has been introduced toenable the manipulator to follow any continuous trajectory.The proposed scheme has been implemented on a sevendegree-of-freedom (7DOF) PowerCube robot manipulatorsuccessfully with visual position feedback only. Thepositioning accuracy of the redundant manipulator usingthe proposed scheme outperforms existing SOM-basedalgorithms

Item Type:Journal article
Keywords:Visual motor control; Self-organizing map; Sub-clustering; Redundancy resolution; Inverse kinematics.
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:21056
Deposited By:Dr Laxmidhar Behera
Deposited On:14 Feb 2012 16:04
Last Modified:14 Feb 2012 16:04

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