Image-based visual servo control of the translation kinematics of a quadrotor aerial vehicle
IEEE Transactions on Robotics - Special issue on rehabilitation robotics
Neural Network Control of Unknown Nonlinear Systems with Efficient Transient Performance
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
IEEE Transactions on Neural Networks
H∞ stability conditions for fuzzy neural networks
Advances in Fuzzy Systems
Visual tracking control for an uncalibrated robot system with unknown camera parameters
Robotics and Computer-Integrated Manufacturing
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An image-based strategy for visual servo control of a class of dynamic systems is proposed. The class of systems considered includes dynamic models of unmanned aerial vehicles capable of quasi-stationary flight (hover and near hover flight). The control strategy exploits passivity-like properties of the dynamic model to derive a Lyapunov control algorithm using backstepping techniques. The paper extends earlier work (Hamel, T., & Mahony, R. (2002). Visual servoing of an under-actuated dynamic rigid-body system: An image based approach. IEEE Transactions on Robotics and Automation, 18(2), 187-198) where partial pose information was used in the construction of the visual error. In this paper the visual error is defined purely in terms of the image features derived from the camera input. Local exponential stability of the system is proved. An estimate of the basin of attraction for the closed-loop system is provided.