Modeling of robot inverse kinematics using two ANN paradigms

Yang, S.S. and Moghavvemi, M. and Tolman, J.D. (2000) Modeling of robot inverse kinematics using two ANN paradigms. In: IEEE Region 10 Annual International Conference, Proceedings/TENCON, 24 September 2000 through 27 September 2000, Kuala Lumpur, Malaysia..

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Abstract

The performance of two artificial neural networks, trained to learn data obtained from the kinematics model of a robotic arm, was compared. The trained artificial neural network (ANN) simulators were implemented to position the robotic manipulator demonstrating the feasibility of using ANN technology in actual implementations. Graphs were plotted to show relevant errors for robotic workspace and conclusions derived with reference to ANN's level of accuracy.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Artificial intelligence; Backpropagation; Inverse kinematics; Robot applications; Robotic arms; Robot inverse kinematics; Neural networks
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering
Depositing User: Ms. Norhamizah Tamizi
Date Deposited: 21 Mar 2014 03:17
Last Modified: 23 Nov 2017 01:47
URI: http://eprints.um.edu.my/id/eprint/9681

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