Asymptotic Vision-Based Tracking Control of the Quadrotor Aerial Vehicle

This paper proposes an image-based visual servo (IBVS) controller for the 3D translational motion of the quadrotor unmanned aerial vehicle (UAV). The main purpose of this paper is to provide asymptotic stability for vision-based tracking control of the quadrotor in the presence of uncertainty in the dynamic model of the system. The aim of the paper also includes the use of ow of image features as the velocity information to compensate for the unreliable linear velocity data measured by accelerometers. For this purpose, the mathematical model of the quadrotor is presented based on the optic ow of image features which provides the possibility of designing a velocity-free IBVS controller with considering the dynamics of the robot. The image features are de ned from a suitable combination of perspective image moments without using the model of the object. This property allows the application of the proposed controller in unknown places. The controller is robust with respect to the uncertainties in the transla- tional dynamics of the system associated with the target motion, image depth and external disturbances. Simulation results and a comparison study are presented which demonstrate the e ectiveness of the proposed approach

Asymptotic Vision-Based Tracking Control of the Quadrotor Aerial Vehicle

This paper proposes an image-based visual servo (IBVS) controller for the 3D translational motion of the quadrotor unmanned aerial vehicle (UAV). The main purpose of this paper is to provide asymptotic stability for vision-based tracking control of the quadrotor in the presence of uncertainty in the dynamic model of the system. The aim of the paper also includes the use of ow of image features as the velocity information to compensate for the unreliable linear velocity data measured by accelerometers. For this purpose, the mathematical model of the quadrotor is presented based on the optic ow of image features which provides the possibility of designing a velocity-free IBVS controller with considering the dynamics of the robot. The image features are de ned from a suitable combination of perspective image moments without using the model of the object. This property allows the application of the proposed controller in unknown places. The controller is robust with respect to the uncertainties in the transla- tional dynamics of the system associated with the target motion, image depth and external disturbances. Simulation results and a comparison study are presented which demonstrate the e ectiveness of the proposed approach

An Analytical Approach for Fast Recovery of the LSI Properties in Magnetic Particle Imaging

Linearity and shift invariance (LSI) characteristics of magnetic particle imaging (MPI) are important properties for quantitative medical diagnosis applications. The MPI image equations have been theoretically shown to exhibit LSI; however, in practice, the necessary filtering action removes the first harmonic information, which destroys the LSI characteristics. This lost information can be constant in the x-space reconstruction method. Available recovery algorithms, which are based on signal matching of multiple partial field of views (pFOVs), require much processing time and a priori information at the start of imaging. In this paper, a fast analytical recovery algorithm is proposed to restore the LSI properties of the x-space MPI images, representable as an image of discrete concentrations of magnetic material. The method utilizes the one-dimensional (1D) x-space imaging kernel and properties of the image and lost image equations. The approach does not require overlapping of pFOVs, and its complexity depends only on a small-sized system of linear equations; therefore, it can reduce the processing time. Moreover, the algorithm only needs a priori information which can be obtained at one imaging process. Considering different particle distributions, several simulations are conducted, and results of 1D and 2D imaging demonstrate the effectiveness of the proposed approach

Dynamic IBVS control of an underactuated UAV

In this paper image based visual servo approach for 3D translational motion and yaw rotation of an under-actuated flying robot is considered. Taking into account the complexity of dynamics of flying robots, main objective of this paper is to consider the dynamics of these robots in designing an image based control strategy. Inertial information of the robot orientation is combined with image information in order to have overall system dynamics in a fashion to apply full dynamic image based controller. Suitable perspective image moments are used in order to have satisfactory trajectories in image space and Cartesian coordinates. A nonlinear controller for the full dynamics of the system is designed. Simulation results are presented to validate the designed controller. © 2012 IEEE