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dc.contributor.authorSong, KTen_US
dc.contributor.authorChang, JMen_US
dc.date.accessioned2014-12-08T15:27:35Z-
dc.date.available2014-12-08T15:27:35Z-
dc.date.issued1996en_US
dc.identifier.isbn0-7803-2775-6en_US
dc.identifier.issn1553-572Xen_US
dc.identifier.urihttp://hdl.handle.net/11536/19833-
dc.description.abstractVisual tracking of a moving object has been an active research topic in the field of robotics and computer vision. In this paper, an experimental study is presented on a neural control design of a robotic manipulator to track a moving object using visual information. The proposed system integrates CCD visual data into an artificial neural network (ANN) for robot arm motion control. This design strategy features fast and efficient control approach where the computation load is reduced to fit the real-time requirement. Integrated experiments have been carried out using a Mitubishi RV-M2 industrial robot equipped with a CCD camera. After training the ANN controller with experimental data, the transformation from world coordinate to the robot coordinate can be eliminated. Robot motion control can be achieved without solving inverse kinematics of the manipulator. Furthermore, the proposed visual tracking system dose not require calibration data of the camera. The factors affecting tracking performance is analyzed and discussed.en_US
dc.language.isoen_USen_US
dc.titleExperimental study on robot visual tracking using a neural controlleren_US
dc.typeProceedings Paperen_US
dc.identifier.journalPROCEEDINGS OF THE 1996 IEEE IECON - 22ND INTERNATIONAL CONFERENCE ON INDUSTRIAL ELECTRONICS, CONTROL, AND INSTRUMENTATION, VOLS 1-3en_US
dc.citation.spage1850en_US
dc.citation.epage1855en_US
dc.contributor.department交大名義發表zh_TW
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentNational Chiao Tung Universityen_US
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:A1996BG90S00319-
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