Control of a High Voltage Power Supply for a Traveling Tube Transmitter

The goal of the Master Thesis is to upgrade the control of a power supply for a radar system. A controller based on Kalman filtering and state feedback has been developed for this two inputs two outputs system

The Vertical Optic Flow: An Additional Cue for Stabilizing Beerotor Robot’s Flight Without IMU

International audienceBio-inspired guidance principles involving no reference frame are presented here and were implemented in a rotorcraft called Beerotor, which was equipped with a minimalistic panoramic optic flow sensor and no accelerometer, no inertial measurement unit (IMU) [9], as in flying insects (Dipterian only uses rotation rates). In the present paper, the vertical optic flow was used as an additional cue whereas the previously published Beerotor II's visuo-motor system only used translational op-tic flow cues [9]. To test these guidance principles, we built a tethered tandem rotorcraft called Beerotor (80g), which flies along a high-roofed tunnel. The aerial robot adjusts its pitch and hence its speed, hugs the ground and lands safely without any need for an inertial reference frame. The rotorcraft's altitude and forward speed are adjusted via several op-tic flow feedback loops piloting respectively the lift and the pitch angle on the basis of the common-mode and differential rotor speeds, respectively as well as an active system of reorientation of a quasi-panoramic eye which constantly realigns its gaze, keeping it parallel to the nearest surface followed. Safe automatic terrain following and landing were obtained with the active eye-reorientation system over rugged terrain, without any need for an inertial reference frame

Controlling docking, altitude and speed in a circular high-roofed tunnel thanks to the optic flow

International audienceThe new robot called BeeRotor we have developed is a tandem rotorcraft that mimicks optic flow-based behaviors previously observed in flies and bees. This tethered miniature robot (80g), which is autonomous in terms of its computational power requirements, is equipped with a 13.5-g quasi-panoramic visual system consisting of 4 individual visual motion sensors responding to the optic flow generated by photographs of natural scenes, thanks to the bio-inspired "time of travel" scheme. Based on recent findings on insects' sensing abilities and control strategies, the BeeRotor robot was designed to use optic flow to perform complex tasks such as ground and ceiling following while also automatically driving its forward speed on the basis of the ventral or dorsal optic flow. In addition, the BeeRotor robot can perform tricky manoeuvers such as automatic ceiling docking by simply regulating its dorsal or ventral optic flow in high-roofed tunnel depicting natural scenes. Although it was built as a proof of concept, the BeeRotor robot is one step further towards achieving a fully- autonomous micro-helicopter which is capable of navigating mainly on the basis of the optic flow

DE L'INSECTE AUX ROBOTS : OBSERVER, RECONSTRUIRE, INNOVER ET MIEUX COMPRENDRE

Les insectes ailés ont résolu des problèmes ardus tels que la stabilisation du vol, l’évitement d’obstacles en 3D, la poursuite de cibles, l’odométrie, l’atterrissage sans piste aménagée et l’atterrissage sur des cibles en mouvements, problèmes sur lesquels bute encore la robotique autonome contemporaine. Certains principes naturels, éprouvés depuis des millions d’années, peuvent aujourd’hui apporter à la Robotique des idées innovantes. Nous savons depuis 70 ans que les insectes ailés réagissent visuellement aux mouvements relatifs du sol causés par leur mouvement propre [Kennedy, 1939]. De façon surprenante, cet indice visuel naturel, plus récemment nommé “flux optique" [Gibson, 1950], n’a pas encore envahi le champ de l’aéronautique, alors même que les capteurs et les traitements mis en oeuvre par le système nerveux d’un insecte au service de son comportement visuo-moteur commencent à être clairement identifiés [Kennedy, 1951; Reichardt, 1969; Hausen, 1984; Pichon et al., 1989; Franceschini et al., 1989; Collett et al., 1993; Srinivasan et al., 1996, 2000;Serres et al., 2008b; Portelli et al., 2010a].Accorder une certaine autorité de vol à un micro-aéronef est une tâche particulièrement difficile, en particulier pendant le décollage, l’atterrissage, ou en présence de vent. Construire un aéronef de quelques grammes ou dizaines de grammes équipé d’un pilote automatique demande alors une démarche innovante. J’ai donc choisi une démarche bioinspirée résolument tournée vers les insectes ailés pour tenter de résoudre les problèmes inhérents au décollage, au contrôle de la vitesse, à l’évitement d’obstacles, à la réaction au vent, ou bien encore l’atterrissage grâce à lamesure du flux optique

A mouse sensor and a 2-pixel motion sensor exposed to continuous illuminance changes

International audienceConsiderable attention has been paid during the last decade to navigation systems based on the use of visual optic flow cues, especially for guiding autonomous robots designed to travel under specific lighting conditions. In the present study, the performances of two visual motion sensors used to measure a local 1-D angular speed, namely (i) a bio-inspired 2-pixel motion sensor and (ii) an off-the-shelf mouse sensor, were tested for the first time in a wide range of illuminance levels. The sensors' characteristics were determined here by recording their responses to a purely rotational optic flow generated by rotating the sensors mechanically and comparing their responses with an accurate rate gyro output signal. The refresh rate, a key parameter for future optic flow-based robotic applications, was also defined and tested in these two sensors. The bio-inspired 2-pixel motion sensor was found to be more accurate indoors whereas the mouse sensor was found to be more efficient outdoors

Optic Flow Based Autopilots: Speed Control and Obstacle Avoidance

International audienceThe explicit control schemes presented here explain how insects may navigate on the sole basis of optic flow (OF) cues without requiring any distance or speed measurements: how they take off and land, follow the terrain, avoid the lateral walls in a corridor and control their forward speed automatically. The optic flow regulator, a feedback system controlling either the lift, the forward thrust or the lateral thrust, is described. Three OF regulators account for various insect flight patterns observed over the ground and over still water, under calm and windy conditions and in straight and tapered corridors. These control schemes were simulated experimentally and/or implemented onboard two types of aerial robots, a micro helicopter (MH) and a hovercraft (HO), which behaved much like insects when placed in similar environments. These robots were equipped with opto-electronic OF sensors inspired by our electrophysiological findings on houseflies' motion sensitive visual neurons. The simple, parsimonious control schemes described here require no conventional avionic devices such as range finders, groundspeed sensors or GPS receivers. They are consistent with the the neural repertoire of flying insects and meet the low avionic payload requirements of autonomous micro aerial and space vehicles

Towards an Automatic Parking System using Bio-Inspired 1-D Optical Flow Sensors

International audienceAlthough several (semi-) automatic parking systems have been presented throughout the years [1]–[12], car manufacturers are still looking for low-cost sensors providing redundant information about the obstacles around the vehicle, as well as efficient methods of processing this information, in the hope of achieving a very high level of robustness. We therefore investigated how Local Motion Sensors (LMSs) [13], [14], comprising only of a few pixels giving 1-D optical flow (OF) measurements could be used to improve automatic parking maneuvers. For this purpose, we developed a low computational-cost method of detecting and tracking a parking spot in real time using 1-D OF measurements around the vehicle as well as the vehicle's longitudinal velocity and steering angle. The algorithm used was composed of 5 processing steps, which will be described here in detail. In this initial report, we will first present some results obtained in a highly simplified 2-D parking simulation performed using Matlab/Simulink software, before giving some preliminary experimental results obtained with the first step in the algorithm in the case of a vehicle equipped with two 6-pixel LMSs. The results of the closed-loop simulation show that up to a certain noise level, the simulated vehicle detected and tracked the parking-spot assessment in real time. The preliminary experimental results show that the average refresh frequency obtained with the LMSs was about 2-3 times higher than that obtained with standard ultrasonic sensors and cameras, and that these LMSs therefore constitute a promising alternative basis for designing new automatic parking systems

Evidence for ventral optic flow regulation in honeybees

To better grasp the visuomotor control system underlying insects' height and speed control, we attempted to interfere with this system by producing a major perturbation on the free flying insect and obsering the effect of this perturbation. Honeybees were trained to fly along a high-roofed tunnel, part of which was equipped with a moving floor. The bees followed the stationary part of the floor at a given height. On encountering the moving part of the floor, which moved in the same direction as their flight, honeybees descended and flew at a lower height. In so doing, bees gradually restored their ventral optic flow (OF) to a similar value to that they had perceived when flying over the stationary part of the floor. OF restoration therefore relied on lowering the groundheight rather than increasing the groundspeed. This result can be accounted for by the control system called an optic flow regulator that we proposed in previous studies. This visuo-motor control scheme explains how honeybees can navigate safely along tunnels on the sole basis of OF measurements, without any need to measure either their speed or the clearance from the ground, the roof or the surrounding walls

Biomimetic visual navigation in a corridor: to centre or not to centre?

International audienceAs a first step toward an Automatic Flight Control System (AFCS) for Micro-Air Vehicle (MAV) obstacle avoidance, we introduce a vision based autopilot (LORA: Lateral Optic flow Regulation Autopilot), which is able to make a hovercraft automatically follow a wall or centre between the two walls of a corridor. A hovercraft is endowed with natural stabilization in pitch and roll while keeping two translational degrees of freedom (X and Y) and one rotational degree of freedom (yaw Ψ). We show the feasibility of an OF regulator that maintains the lateral Optic Flow (OF) on one wall equal to an OF set-point. The OF sensors used are Elementary Motion Detectors (EMDs), whose working was directly inspired by the housefly motion detecting neurons. The properties of these neurons were previously analysed at our laboratory by performing electrophysiological recordings while applying optical microstimuli to single photoreceptor cells of the compound eye. The simulation results show that depending on the OF set-point, the hovercraft either centres along the midline of the corridor or follows one of the two walls, even with local lack of optical texture on one wall, such as caused, for instance, by an open door or a T-junction. All these navigational tasks are performed with one and the same feedback loop, which consists of a lateral OF regulation loop that permits relatively high-speed navigation (1m/s, i.e 3 body-lengths per second). The passive visual sensors and the simple processing system are suitable for use with MAVs with an avionic payload of only a few grams. The goal is to achieve MAV automatic guidance or to relieve a remote operator from guiding it in challenging environments such as urban canyons or indoor environments