Modeling of robot inverse kinematics using two ANN paradigms
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 technolog...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
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Elsevier Science
2000
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| _version_ | 1825719746399567872 |
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| author | Yang, S.S. Moghavvemi, M. Tolman, J.D. |
| author_facet | Yang, S.S. Moghavvemi, M. Tolman, J.D. |
| author_sort | Yang, S.S. |
| collection | UM |
| description | 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. |
| first_indexed | 2024-03-06T05:24:28Z |
| format | Conference or Workshop Item |
| id | um.eprints-9681 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:24:28Z |
| publishDate | 2000 |
| publisher | Elsevier Science |
| record_format | dspace |
| spelling | um.eprints-96812017-11-23T01:47:10Z http://eprints.um.edu.my/9681/ Modeling of robot inverse kinematics using two ANN paradigms Yang, S.S. Moghavvemi, M. Tolman, J.D. TA Engineering (General). Civil engineering (General) 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. Elsevier Science 2000 Conference or Workshop Item PeerReviewed 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.. |
| spellingShingle | TA Engineering (General). Civil engineering (General) Yang, S.S. Moghavvemi, M. Tolman, J.D. Modeling of robot inverse kinematics using two ANN paradigms |
| title | Modeling of robot inverse kinematics using two ANN paradigms |
| title_full | Modeling of robot inverse kinematics using two ANN paradigms |
| title_fullStr | Modeling of robot inverse kinematics using two ANN paradigms |
| title_full_unstemmed | Modeling of robot inverse kinematics using two ANN paradigms |
| title_short | Modeling of robot inverse kinematics using two ANN paradigms |
| title_sort | modeling of robot inverse kinematics using two ann paradigms |
| topic | TA Engineering (General). Civil engineering (General) |
| work_keys_str_mv | AT yangss modelingofrobotinversekinematicsusingtwoannparadigms AT moghavvemim modelingofrobotinversekinematicsusingtwoannparadigms AT tolmanjd modelingofrobotinversekinematicsusingtwoannparadigms |