This paper presents a robotic system designed for holding and placing objects based on their colour and shape. The presented robot is given a complete set of instructions of positions and orientation angles for each manipulation motion. The main feature in this paper is that the developed robot used a combination of vision and motion systems for holding and placing the work-objects, mounted on the flat work-plane, based on their shapes and colorus . This combination improves the flexibility of manipulation which may help eliminate the use of some expensive manipulation tasks in a variety of industrial applications. The robotic system presented in this paper is designed as an educational robot that possesses the ability for holding-and-placing operations with limited load. To process the various instructions for holding and placing the work objects, a main control unit -Manipulation Control Unit (MCU) is used as well as a slave unit that performed the actual instructions from the MCU.
This paper presents learning efficiency of a consciousness system for robot using artificial neural network. The proposed conscious system consists of reason system, feeling system and association system. The three systems are modeled using Module of Nerves for Advanced Dynamics (ModNAD). Artificial neural network of the type of supervised learning with the back propagation is used to train the ModNAD. The reason system imitates behaviour and represents self-condition and other-condition. The feeling system represents sensation and emotion. The association system represents behaviour of self and determines whether self is comfortable or not. A robot is asked to perform cognition and tasks using the consciousness system. Learning converges to about 0.01 within about 900 orders for imitation, pain, solitude and the association modules. It converges to about 0.01 within about 400 orders for the comfort and discomfort modules. It can be concluded that learning in the ModNAD completed after a relatively small number of times because the learning efficiency of the ModNAD artificial neural network is good. The results also show that each ModNAD has a function to imitate and cognize emotion. The consciousness system presented in this paper may be considered as a fundamental step for developing a robot having consciousness and feelings similar to humans.
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