The Experts below are selected from a list of 12255 Experts worldwide ranked by ideXlab platform

Tarek Hamel - One of the best experts on this subject based on the ideXlab platform.

  • A homography-based dynamic control approach applied to station keeping of autonomous underwater vehicles without linear velocity measurements
    2019
    Co-Authors: Lam-hung Nguyen, Guillaume Allibert, Minh-duc Hua, Tarek Hamel
    Abstract:

    A homography-based dynamic control approach applied to station keeping of Autonomous Underwater Vehicles (AUVs) without relying on linear velocity measurements is proposed. The homography estimated from images of a Planar Target scene captured by a downward-looking camera is directly used as feedback information. The full dynamics of the AUV are exploited in a hierarchical control design with inner-outer loop architecture. Enhanced by integral compensation actions and disturbance torque estimation, the proposed controller is robust with respect to model uncertainties and unknown currents. The performance of the proposed control approach is illustrated via both comparative simulation results conducted on a realistic AUV model and experimental validations on an in-house AUV.

  • A homography-based dynamic control approach of Autonomous Underwater Vehicles observing a (near) vertical Target without linear velocity measurements
    2019
    Co-Authors: Lam-hung Nguyen, Minh-duc Hua, Tarek Hamel
    Abstract:

    The paper addresses the challenging problem of image-based dynamic control of Autonomous Underwater Vehicles observing a (near) vertical Planar Target, without measuring the linear velocity. The proposed control approach exploits a minimum sensor suite consisting of a camera looking forward to provide images from which the homography matrix is extracted and an IMU providing angular velocity and gravity direction measurements. The dynamics of the AUV are exploited in a hierarchical control scheme with inner-outer control loop architecture. Rigourous stability analysis is established. The performance of the proposed approach is illustrated via simulation results conducted on a realistic AUV model.

  • homography estimation of a moving Planar scene from direct point correspondence
    Conference on Decision and Control, 2018
    Co-Authors: S Marco, Robert Mahony, Tarek Hamel
    Abstract:

    Homographies provide a robust and reliable cue for visual servo control of robots. Some nonlinear observers have been recently developed for the estimation of temporal sequences of homographies associated with rigid-body motion of a camera observing a stationary Planar scene. However, these algorithms do not model well time-varying changes in the homography velocity and tend to perform poorly when the camera or the scene moves fast. In this paper, an internal model-based observer posed on S L (3) for homography estimation is proposed allowing for dealing with complex camera-scene trajectories such as circular and sinusoidal motions of the camera and/or the scene. Rigorous proof of local asymptotic stability is established and excellent performance of the proposed observer is justified by experiments using an IMU-Camera prototype observing an oscillating Planar Target.

  • Attitude, Linear Velocity and Depth Estimation of a Camera observing a Planar Target using continuous homography and inertial data
    2018
    Co-Authors: Minh-duc Hua, Tarek Hamel, Ninad Manerikar, Claude Samson
    Abstract:

    This paper revisits the problem of estimating the attitude, linear velocity and depth of an IMU-Camera with respect to a Planar Target. The considered solution relies on the measurement of the optical flow (extracted from the continuous homography) complemented with gyrometer and accelerometer measurements. The proposed deterministic observer is accompanied with an observability analysis that points out camera's motion excitation conditions whose satisfaction grants stability of the observer and convergence of the estimation errors to zero. The performance of the observer is illustrated by performing experiments on a test-bed IMU-Camera system.

  • ICRA - Attitude, Linear Velocity and Depth Estimation of a Camera Observing a Planar Target Using Continuous Homography and Inertial Data
    2018 IEEE International Conference on Robotics and Automation (ICRA), 2018
    Co-Authors: Minh-duc Hua, Tarek Hamel, Ninad Manerikar, Claude Samson
    Abstract:

    This paper revisits the problem of estimating the attitude, linear velocity and depth of an IMU-Camera with respect to a Planar Target. The considered solution relies on the measurement of the optical flow (extracted from the continuous homography) complemented with gyrometer and accelerometer measurements. The proposed deterministic observer is accompanied with an observability analysis that points out camera's motion excitation conditions whose satisfaction grants stability of the observer and convergence of the estimation errors to zero. The performance of the observer is illustrated by performing experiments on a testbed IMU-Camera system.

Philippe Mouyon - One of the best experts on this subject based on the ideXlab platform.

  • Stabilization of a class of underactuated vehicles with uncertain position measurements and application to visual servoing
    Automatica, 2017
    Co-Authors: Henry De Plinval, Pascal Morin, Philippe Mouyon
    Abstract:

    Stabilization of a class of underactuated vehicles with uncertain measurements of the position tracking error is addressed. Nonlinear feedback laws ensuring semi-global stability for a large class of uncertainties on these measurements are derived based on properties of saturated controls. Practical relevance of the proposed results is illustrated by two application examples for Vertical TakeOff and Landing aerial vehicles equipped with a mono-camera sensor: point stabilization in front of a Planar Target and visual way-points navigation based on interpolation of homography measures.

  • Visual servoing for underactuated VTOL UAVs: A linear, Homography-Based Approach
    2011
    Co-Authors: Henry De Plinval, Pascal Morin, Philippe Mouyon, Tarek Hamel
    Abstract:

    The paper addresses the control of Vertical Take Off and Landing (VTOL) Underactuated Autonomous Vehicles (UAVs) in hover flight, based on measurements provided by an on-board video camera and rate gyros. The objective is to stabilize the vehicle to the pose associated with a visual image of a Planar Target. By using the homography matrix computed from the camera measurements of the Target, stabilizing feedback laws are derived. Explicit stability conditions on the control parameters are provided. It is shown that very good robustness and performance can be achieved without any apriori information on the visual Target (like geometry, or orientation), by a proper tuning of the control parameters. Simulation results confirm the effectiveness of the approach

Guangjun Zhang - One of the best experts on this subject based on the ideXlab platform.

  • a vision measurement model of laser displacement sensor and its calibration method
    Optics and Lasers in Engineering, 2013
    Co-Authors: Jie Zhang, Guangjun Zhang
    Abstract:

    Abstract Laser displacement sensors (LDSs) use a triangulation measurement model in general. However, the non-linearity of the triangulation measurement model influences the measurement accuracy of the LDS, and the geometric parameters calibration process of the components of the LDS is tedious. In this paper, we present a vision measurement model of the LDS based on the perspective projection principle. Furthermore, a corresponding calibration method is proposed. A Planar Target with featured lines is moved by a 2D moving platform to some preset known positions. At each position, the world coordinates of calibration points are obtained by the cross ratio invariance principle and the linear array camera of the LDS is used for collecting Target images. The simulations verify the effectiveness of the proposed model and the feasibility of the calibration method. The experimental results indicate that the calibration method achieves a calibration accuracy of 0.026 mm. Compared with the traditional measurement model, the vision measurement model of the LDS is more comprehensive and avoids a linear approximation procedure, and the corresponding calibration method is easily complemented.

  • High-dynamic angle measurement based on laser displacement sensors
    Applied Optics, 2013
    Co-Authors: Jie Zhang, Guangjun Zhang
    Abstract:

    It is currently difficult to achieve good real-time dynamic angle measurements with high accuracy and large ranges. In this paper, a photoelectric measurement method for dynamic angles based on three laser displacement sensors (LDSs) is proposed. Offline, a dynamic angle vision measurement model is established, and the system is calibrated by using a Planar Target moved by a 2D moving platform. In the course of measurement, three laser beams emitted from three LDSs are projected onto a rotating plane, and three noncollinear points are acquired synchronously; then the rotation angle is calculated in real time. Simulations verify the feasibility of the method theoretically. Experimental results demonstrate that the method achieves measurement accuracies of 0.008° and 0.046° under quasi-static condition of 80°/s and highly dynamic condition of 1000°/s within the measurement range of about ±40°, respectively.

  • A camera calibration method based on iterated extended Kalman filter using Planar Target
    Sixth International Symposium on Instrumentation and Control Technology: Sensors Automatic Measurement Control and Computer Simulation, 2006
    Co-Authors: Fuqiang Zhou, Jin Zhai, Guangjun Zhang
    Abstract:

    ABSTRACT It is proposed a method for camera calibration that could be used in stereo systems as well as in stereo head navigation in this paper. A pinhole camera model and two-dimensional Planar Target are considered. An Iterated Extended Kalman Filter (IEKF) is used to estimate camera parameters. The met hod takes the observed feature points of images as the filter input and the estimated value of the intrinsic and extrinsic camera parameters as the filter output. Both computer simulation and real data experiments have been used to test the proposed method, and good results have been obtained. The RMS error of absolute distance between reprojection feature points is about 0.09 pixels in real experiments. The experimental results show IEKF is also a feasible optimization algorithm for on-line camera calibration. Key words: Camera Calibration, Iterated Extended Kalman Filter, Planar Target 1. INTRODUCTION Camera calibration is a crucial phase in most vision systems and a first step in 3D reconstruction. It has been broadly applied in machine vision, virtual reality, and three-dimensional reconstruction and so on. Generally, in order to obtain higher calibration precision, in trinsic and extrinsic camera para meters are estimated through nonlinear optimization methods with information acquired from images. Starting from the simplest method we could mention the Least Square Error (LSE)

  • Complete calibration of a structured light stripe vision sensor through Planar Target of unknown orientations
    Image and Vision Computing, 2004
    Co-Authors: Fuqiang Zhou, Guangjun Zhang
    Abstract:

    Abstract Structured light 3D vision inspection is a commonly used method for various 3D surface profiling techniques. In this paper, the mathematical model of the structured light stripe vision sensor is established. We propose a flexible new approach to easily determine all primitive parameters of a structured light stripe vision sensor. It is well suited for use without specialized knowledge of 3D geometry. The technique only requires the sensor to observe a Planar Target shown at a few (at least two) different orientations. Either the sensor or the Planar Target can be freely moved. The motion need not be known. A novel approach is proposed to generate sufficient non-collinear control points for structured light stripe vision sensor calibration. Real data has been used to test the proposed technique, and very good result has been obtained. Compared with classical techniques, which use expensive equipment such as two or three orthogonal planes, the proposed technique is easy to use and flexible. It advances structured light vision one step from laboratory environments to real engineering 3D metrology applications.

Carme Torras - One of the best experts on this subject based on the ideXlab platform.

  • depth from the visual motion of a Planar Target induced by zooming
    International Conference on Robotics and Automation, 2007
    Co-Authors: Guillem Alenya, M Alberich, Carme Torras
    Abstract:

    Robot egomotion can be estimated from an acquired video stream up to the scale of the scene. To remove this uncertainty (and obtain true egomotion), a distance within the scene needs to be known. If no a priori knowledge on the scene is assumed, the usual solution is to derive "in some way" the initial distance from the camera to a Target object. This paper proposes a new, very simple way to obtain such a distance, when a zooming camera is available and there is a Planar Target in the scene. Similarly to "two-grid calibration" algorithms, no estimation of the camera parameters is required, and no assumption on the optical axis stability between the different focal lengths is needed. Quite the reverse, the non stability of the optical axis between the different focal lengths is the key ingredient that enables to derive our depth estimate, by applying a result in projective geometry. Experiments carried out on a mobile robot platform show the promise of the approach.

  • ICRA - Depth from the visual motion of a Planar Target induced by zooming
    Proceedings 2007 IEEE International Conference on Robotics and Automation, 2007
    Co-Authors: Guillem Alenya, M Alberich, Carme Torras
    Abstract:

    Robot egomotion can be estimated from an acquired video stream up to the scale of the scene. To remove this uncertainty (and obtain true egomotion), a distance within the scene needs to be known. If no a priori knowledge on the scene is assumed, the usual solution is to derive "in some way" the initial distance from the camera to a Target object. This paper proposes a new, very simple way to obtain such a distance, when a zooming camera is available and there is a Planar Target in the scene. Similarly to "two-grid calibration" algorithms, no estimation of the camera parameters is required, and no assumption on the optical axis stability between the different focal lengths is needed. Quite the reverse, the non stability of the optical axis between the different focal lengths is the key ingredient that enables to derive our depth estimate, by applying a result in projective geometry. Experiments carried out on a mobile robot platform show the promise of the approach.

Henry De Plinval - One of the best experts on this subject based on the ideXlab platform.

  • Stabilization of a class of underactuated vehicles with uncertain position measurements and application to visual servoing
    Automatica, 2017
    Co-Authors: Henry De Plinval, Pascal Morin, Philippe Mouyon
    Abstract:

    Stabilization of a class of underactuated vehicles with uncertain measurements of the position tracking error is addressed. Nonlinear feedback laws ensuring semi-global stability for a large class of uncertainties on these measurements are derived based on properties of saturated controls. Practical relevance of the proposed results is illustrated by two application examples for Vertical TakeOff and Landing aerial vehicles equipped with a mono-camera sensor: point stabilization in front of a Planar Target and visual way-points navigation based on interpolation of homography measures.

  • Visual servoing for underactuated VTOL UAVs: A linear, Homography-Based Approach
    2011
    Co-Authors: Henry De Plinval, Pascal Morin, Philippe Mouyon, Tarek Hamel
    Abstract:

    The paper addresses the control of Vertical Take Off and Landing (VTOL) Underactuated Autonomous Vehicles (UAVs) in hover flight, based on measurements provided by an on-board video camera and rate gyros. The objective is to stabilize the vehicle to the pose associated with a visual image of a Planar Target. By using the homography matrix computed from the camera measurements of the Target, stabilizing feedback laws are derived. Explicit stability conditions on the control parameters are provided. It is shown that very good robustness and performance can be achieved without any apriori information on the visual Target (like geometry, or orientation), by a proper tuning of the control parameters. Simulation results confirm the effectiveness of the approach