Manipulator adaptive control by neural networks in an orange picking robot.
The paper focuses on the use of neural networks for process identification in an orange-picking robot adaptive control system. The results that will be shown in the paper refer to a study carried out under the European Community ESPRIT project "CONNY", dealing with the application of neural networks to robotics. The aim of the research is to verify the possibility of integrating a neural identification module in a traditional system to control the movement of the manipulators of the robot. The paper illustrates integration of neural identification in the existing orange-picking robot control system, highlighting the improvement of performance obtainable. Although the proposal refers to a specific robot, it can be applied to any system with the same dynamic features.
Cavalieri
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S
Istituto di Informatica e Telecomunicazioni, Facolta' di Ingegneria, Universita' di Catania, Italy. cavalieri@iit.unict.it
Plebe
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D000223:Adaptation, Psychological; D001185:Artificial Intelligence; D003198:Computer Simulation; D008959:Models, Neurological; D016571:Neural Networks, Computer; D011597:Psychomotor Performance; D012371:Robotics / Q000295:instrumentation*