This paper proposes a practical approach for fastening the lengthy experimentational processes that may occur with iterative learning control (ILC) upto a certain level using simple low-order identified models. The traditional practice in ILC experiments is to update the ILC signal by directly using the experimental data after each run of the process which corresponds to one ILC update per one run. When considered from the point of experimental time, even conducting a moderate number of ILC updates can take quite long with this procedure. Since an accurate linear model can adequately represent the actual system upto a certain amplitude and/or frequency of the desired reference, we propose that the total experimental time can be reduced by updating the ILC signal via predicted system data until the limits of the linear model. This approach allows one to carry out large number of ILC updates while not needing to carry out the same amount of real experiments. Consequently, a significant number of experiments that would be needed for achieving the same results can be skipped with a simulation approach. The efficiency of the proposed method was tested through experimentation with three different UAV reference trajectories and the results demonstrated that it is possible to attain significant amount of tracking precision in several flight experiments.

This paper presents a new minimalist bio-inspired artificial eye of only 24 pixels, able to locate accurately a target placed in its small field of view (±10°). The eye is mounted on a very light custom-made gimbal system which makes the eye able to track faithfully a moving target. We have shown, that our gimbal eye can be embedded on a small quadrotor to achieve accurate hovering with respect to a target placed onto the ground. Our aiborne eye was enhanced with a bio-inspired reflex in charge of locking efficiently the robot's gaze onto a target and compensate for the robot's rotations and disturbances. The use of very few pixels allowed to implement a visual processing algorithm at a refresh rate of 400 Hz. This high refresh rate coupled to a very fast control of the eye's orientation allowed the robot to track a target moving at a speed up to 200° · s-1.

Hovering flies are capable of achieving outstanding performances when hovering above flowers for several minutes. A new insect-based hovering control strategy is presented here for accurately stabilizing the position of a sighted twin-rotor equipped with a decoupled eye with a narrow field-of-view of only a few degrees. The main aim of this paper is to describe how accurately hovering flight above a target can be achieved by means of this fundamental bio-inspired mechanical decoupling system between the eye and the body. The simulated gaze control system implemented on-board the aerial robot has several advantages : - it enables the robot's gaze to be stabilized on the basis of three bio-inspired oculomotor reflexes (ORs) : a visual fixation reflex (VFR), a translational reflex and a rotational vestibulo-ocular reflex (tVOR and rVOR), - it makes the eye compensate quickly and accurately for any sudden, untoward disturbances caused by the vagaries of the supporting head or body, - it provides a reference visual signal to compensate for the rate gyro drift used to implement the VORs and to stabilize the hovering robot, - it greatly improves the stability of the robot's roll during voluntary lateral displacements with respect to the target. Close comparisons were made between two simulated robots with and without a decoupled eye, which were both subjected to strong lateral and roll disturbances. The simulations show that the robot with a decoupled eye can reject disturbances twice as fast as that with a fixed eye. This innovative bio-inspired hovering control method stabilizes the robot's attitude without any need for accelerometers, magnetometers or classical inertial measurement units.