A new control method for stereo visual servoing system with Pan-tilt platform
Keywords:Target tracking, pan/tilt, stereo camera, neural network, Lyapunov stability.
This paper proposes a new control method for Pan-Tilt stereo camera system to track a moving object when there are many uncertainties in the parameters of both camera and Pan-Tilt platform. If a pair of cameras placed on the Pan-Tilt robot, it is unnecessary for its installation location to be determined accurately. Assuming that the optical parameters like focal length of two cameras in the simulation are the same. A two degree of freedom Pan-Tilt platform holding camera has many uncertain parameters such as inertial moment, Jacobian matrix, the friction and noise impact, etc. The proposed control algorithm is highly adaptive and robust due to the use of a compensating neural network with on-line learning rule. The asymptotic stability of overall control system is proved by Lyapunov's stability method.
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