1,518 research outputs found

    Image-based visual servo control of the translation kinematics of a quadrotor aerial vehicle

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    International audienceIn this paper, we investigate a range of image-based visual servo control algorithms for regulation of the position of a quadrotor aerial vehicle. The most promising control algorithms have been successfully implemented on an autonomous aerial vehicle and demonstrate excellent performance

    Kinematic Visual Servo Control of a Quadrotor aerial vehicle

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    Visual systems are key sensors for control of small scale unmanned aerial vehicles. In this paper we investigate a range of image based visual servo control algorithms for positioning of flying vehicles capable of hover. The image based outer control loop for translation kinematics is coupled to a high-gain inner control loop that regulates translational velocities and full attitude dynamics. Zero and first order image moments are used as visual features for the control design. Perspective projection moments with suitable scaling along with a classical image based visual servo control design lead to satisfactory transients and asymptotic stability of the closed-loop system when the image plane remains parallel to the target. However, the system response may lack robustness for aggressive manoeuvres. In order to overcome this problem, several control schemes, based on spherical image moments, are designed and their performance is analysed. All designed control laws have been tested on a kinematic robotic manipulator to demonstrate the relative strengths and weaknesses of thedifferent image based visual servo control designs. The three most promising control algorithms have been successfully implemented on an autonomous aerial vehicle showing excellent performances in all three cases

    Hierarchical task control for aerial inspection

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    This paper presents a task oriented control strategy for aerial vehicles equipped with a robotic arm and a camera attached to its end-effector. With this setting the camera can reach a new set of orientations previously not feasible for the quadrotor. The over-actuation of the whole system is exploited with a hierarchical control law to achieve a primary task consisting on a visual servoing control, whilst secondary tasks can also be attained to minimize gravitational effects or undesired arm configurations. Results are shown in a Robot Operating System (ROS) simulation.Peer ReviewedPostprint (author’s final draft

    Asymptotic Vision-Based Tracking Control of the Quadrotor Aerial Vehicle

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    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

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    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

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    AltURI: a thin middleware for simulated robot vision applications

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    Fast software performance is often the focus when developing real-time vision-based control applications for robot simulators. In this paper we have developed a thin, high performance middleware for USARSim and other simulators designed for real-time vision-based control applications. It includes a fast image server providing images in OpenCV, Matlab or web formats and a simple command/sensor processor. The interface has been tested in USARSim with an Unmanned Aerial Vehicle using two control applications; landing using a reinforcement learning algorithm and altitude control using elementary motion detection. The middleware has been found to be fast enough to control the flying robot as well as very easy to set up and use

    Real-Time Visual Servo Control of Two-Link and Three DOF Robot Manipulator

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    This project presents experimental results of position-based visual servoing control process of a 3R robot using 2 fixed cameras. Visual servoing concerns several field of research including vision systems, robotics and automatic control. This method deal with real time changes in the relative position of the target-object with respect to robot. It is have good accuracy with independency of Manipulator servo control structure from the target pose coordinates are the additional advantages of this method. The applications of visually guided systems are many: from intelligent homes to automotive industry. Visual servoing are also useful for a wide range of applications and it can be used to control many different systems (manipulator arms, mobile robots, aircraft, etc.). Visual servoing systems are generally divide depends on the number of camera, on the position of the camera with respect to the robot, on the design of the error function to robot. This project presents an approach for visual robot control. Existing approaches are increased in such a way that depth and position information of block or object is estimate during the motion of the robot. That is done by the visual tracking of an object throughout the trajectory. Vision designed robotics has been a major research area for more time. However, one of the open and commonly problems in the area is the requirement for exchange of the experiences and ideas. We also include a number of real–time examples from our own research. Forward and inverse kinematics of 3 DOF robot have been done then experiments on image processing, object shape recognition and pose estimation as well as target-block or object in Cartesian system and visual control of robot manipulator have been prescribed. Experimental results obtained from real-time system implementation of visual servo control and tests of 3DOF robot in lab
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