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.

A nonlinear inertial-aided image-based visual servo control approach for the stabilization of (almost) fully actuated autonomous underwater vehicles (AUVs) is proposed. It makes use of the homography matrix between two images of a planar scene as feedback information while the system dynamics are exploited in a cascade manner in a control design: An outer-loop control defines a reference setpoint based on the homography matrix and an inner-loop control ensures the stabilization of the setpoint by assigning the thrust and torque controls. Unlike conventional solutions that only consider the system kinematics, the proposed control scheme is novel in considering the full system dynamics (incorporating all degrees of freedom, nonlinearities, and couplings, as well as interactions with the surrounding fluid) and in not requiring information of the relative depth and normal vector of the observed scene. Augmented with integral corrections, the proposed controller is robust with respect to model uncertainties and disturbances. The almost global asymptotic stability of the closed-loop system is demonstrated, which is the largest domain of attraction one can achieve by means of continuous feedback control. Simulation results illustrating these properties on a realistic AUV model subjected to a sea current are presented and finally experimental results on a real AUV are reported.

This paper presents an intuitive teleoperation scheme to safely operate a wide range of VTOL UAVs by an untrained user in a cluttered environment. This scheme includes a novel force-feedback algorithm that enables the user to feel the texture of the environment. In addition, a novel mapping function is introduced to teleoperate the UAV in an unlimited workspace in position control mode with a joystick which has a limited workspace. An obstacle avoidance strategy is designed to autonomously modify the position set point of the UAV independently of the pilot's commands. The stability analysis of the whole teleoperation loop is provided. Experiments demonstrate the successful teleoperation of a UAV using an haptic joystick and a hexacopter UAV equipped with a 2D laser-range scanner.

This paper presents the design and evaluation of a nonlinear control scheme for multirotor helicopters that takes first-order drag effects into account explicitly. A dynamic model including the blade flapping and induced drag forces is presented. Based on this model, a hierarchical nonlinear controller is designed to actively compensates for the nonlinear effects these drag forces. Reported simulation and experimental results indicate the significant performance improvement of the proposed drag-augmented control scheme with respect to a conventional nonlinear controller. For completeness, an offline procedure allowing for efficiently identifying the drag parameters is proposed.

A control approach for a class of underactuated vehicles with the objective of stabilizing reference trajectories either in velocity or position is proposed. The basic modeling assumption is that the vehicle is propulsed via a thrust force along a single body-fixed direction and that it has full torque actuation for attitude control (i.e. a typical actuation structure for aircrafts, vertical take-off and landing (VTOL) vehicles, submarines, etc.). Additional assumptions on the external forces applied to the vehicle are also introduced for the sake of control design and stability analyses. They are best satisfied for vehicles whose shape induces lift forces with limited amplitude and which are subjected to an external force field (e.g. gravity), as in the case of VTOL vehicles. The interactions of the vehicle with the surrounding fluid are often difficult to model precisely and they may significantly perturb its motion. Some novel nonlinear feedback control laws are proposed to compensate for modeling errors and perform robustly against such perturbations. Simulation results illustrating these properties on a realistic model of a VTOL vehicle are reported.