Basic Research of Visual Servo which Dynamically Combines Environment Recognition to Motion Control

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Visual servo system is a feedback control mechanism based on image information, which is essential in motion control of intelligent robots working in unstructured environments. In the conventional visual feedback system, environment recognition and motion control are performed sequentially in step by step manner. However, these conventional look and move schemes are deficient for fast and accurate manipulation.The purpose of this research project is to combine the environment recognition and the motion control dynamically so as to develop a new visual servo scheme in which the recognition and manipulation processes proceed complementing with each other. We have proposed a visual servo scheme called image-based dynamic visual servo, which is shown to be more accurate than the conventional scheme and to be robust against the measurement noises. The dynamics of this visual servo system is expressed by a state equation, based on which the optimal regulator can be used to stabilize the system.Realization of this visual servo system requires considerably powerful computing devices. Thus, we have developed a parallel processing system composed by ten 32-bits microprocessors--Transputers. Real-time image-based visual servo is implemented on this hardware system and PUMA 560. Though any Realistic manipulation can not be performed, some basic experiments verify the effectiveness of the proposed visual servo scheme.The visual servo scheme developed in this research project is derived by applying the available control theory to the image-based visual feedback system, which gives us no novel control theoretic framework of visual feedback. We found that, to build up new framework, robot dynamics must be included in the dynamics of visual servo system, and the inclusive mechanism must be treated as an augmented dynamic system. The results of this research project will become the bases of the future developments of visual feedback control theory.