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Proceedings Paper

Integrated self-tuning control accelerator and computer vision system for robot arms
Author(s): Eliana P. L. Aude; Julio S. Aude; Mario F. Martins; Henrique Serdeira; Emerson Prado Lopes
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Paper Abstract

Systems for high-precision control of the trajectory to be followed by a robot arm grip need to properly model the interaction among the robot arm joints and to cope with the high-speed and nonlinearities of the arm dynamics. To solve this problem the use of a hardware accelerator, which is able to explore parallelism within multivariable self-tuning control algorithms, is proposed. The accelerator works as part of an integrated system which incorporates facilities of computer vision and robot arm trajectory definition. The computer vision sub-system recognizes the position of an object selected to be picked by the robot arm and the trajectory definition sub-system uses a neural network to define the angular position of the joints along the trajectory to be followed by the arm.

Paper Details

Date Published: 11 March 1993
PDF: 7 pages
Proc. SPIE 1964, Applications of Artificial Intelligence 1993: Machine Vision and Robotics, (11 March 1993); doi: 10.1117/12.141773
Show Author Affiliations
Eliana P. L. Aude, Univ. Federal do Rio de Janeiro (Brazil)
Julio S. Aude, Univ. Federal do Rio de Janeiro (Brazil)
Mario F. Martins, Univ. Federal do Rio de Janeiro (Brazil)
Henrique Serdeira, Univ. Federal do Rio de Janeiro (Brazil)
Emerson Prado Lopes, Univ. Federal do Rio de Janeiro (Brazil)


Published in SPIE Proceedings Vol. 1964:
Applications of Artificial Intelligence 1993: Machine Vision and Robotics
Kim L. Boyer; Louise Stark, Editor(s)

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