Control of robot-camera system with actuator's dynamics to track moving object
Keywords:Robot control, artificial neural network, visual servoing
This study presents a solution to the control of robot–camera system with actuator's dynamics to track a moving object where many uncertain parameters exist in the system’s dynamics.
After modeling and analyzing the system, this paper suggests a new control method using an on-line learning neural network in closed-loop to control the Pan-Tilt platform that moves the Camera to keep track an unknown moving object. The control structure based on the image feature error determines the necessary rotational velocities on the Pan joint and Tilt joint and computes the voltage controlling the DC motor in joints such that the object image should always be at the center point in the image plane. The global asymptotic stability of the closed-loop is proven by the Lyapunov direct stability theory. Simulation results on Matlab show the system tracking fast and stable.
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