Optic Flow Based Visual Guidance: From Flying Insects to Miniature Aerial Vehicles

International audienc

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

On the ecological approach to Information and control for roboticists

The ongoing and increasingly important trend in robotics to conceive designs that decentralize control is paralleled by currently active research paradigms in the study of perception and action. James Gibson’s ecological approach is one of these paradigms. Gibson’s approach emerged in part as a reaction to representationalist and computationalist approaches, which devote the bulk of their resources to the study of internal processes. The ecological approach instead focuses on constraints and ambient energy patterns in the animal‐environment coalition. The present article reviews how the emphasis on the environment by ecological psychologists has given rise to the concepts of direct perception, higher order information, active information pick up, informationbased control laws, prospective control, and direct learning. Examples are included to illustrate these concepts and to show how they can be applied to the construction of robots. Action is described as emergent and self‐organized. It is argued that knowledge about perception, action, and learning as it occurs in living organisms may facilitate the construction of robots, more obviously so if the aim is to construct (to some extent) biologically plausible robots.This material is based upon work supported by grant FFI2009‐13416‐C02‐02 of the Spanish Ministry of Science and Innovation

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

Honeybees' Speed Depends on Dorsal as Well as Lateral, Ventral and Frontal Optic Flows

Flying insects use the optic flow to navigate safely in unfamiliar environments, especially by adjusting their speed and their clearance from surrounding objects. It has not yet been established, however, which specific parts of the optical flow field insects use to control their speed. With a view to answering this question, freely flying honeybees were trained to fly along a specially designed tunnel including two successive tapering parts: the first part was tapered in the vertical plane and the second one, in the horizontal plane. The honeybees were found to adjust their speed on the basis of the optic flow they perceived not only in the lateral and ventral parts of their visual field, but also in the dorsal part. More specifically, the honeybees' speed varied monotonically, depending on the minimum cross-section of the tunnel, regardless of whether the narrowing occurred in the horizontal or vertical plane. The honeybees' speed decreased or increased whenever the minimum cross-section decreased or increased. In other words, the larger sum of the two opposite optic flows in the horizontal and vertical planes was kept practically constant thanks to the speed control performed by the honeybees upon encountering a narrowing of the tunnel. The previously described ALIS (“AutopiLot using an Insect-based vision System”) model nicely matches the present behavioral findings. The ALIS model is based on a feedback control scheme that explains how honeybees may keep their speed proportional to the minimum local cross-section of a tunnel, based solely on optic flow processing, without any need for speedometers or rangefinders. The present behavioral findings suggest how flying insects may succeed in adjusting their speed in their complex foraging environments, while at the same time adjusting their distance not only from lateral and ventral objects but also from those located in their dorsal visual field

Le pilotage visuel chez l'abeille : expériences et modèle

Quand un insecte vole, l'image des objets à l'entour défile sur sa rétine. De nombreuses expériences ont montré que ce défilement angulaire (flux optique) joue un rôle majeur dans le contrôle du vol. Les insectes semblent maintenir le flux optique perçu à une valeur préférée, les conduisant à adopter une position et une vitesse "de sécurité". Nous avons élaboré un modèle basé sur le principe de "régulation du flux optique" proposé précédemment par notre laboratoire, et capable de rendre compte d'observations et de résultats d'expériences réalisées auparavant chez les insectes. Nous avons ensuite réalisé des expériences comportementales sur des abeilles en vol libre, en environnement contrôlé, visant à mettre en défaut le modèle proposé. Nos résultats révèlent un lien étroit entre flux optique ventral et hauteur de vol. Ils montrent aussi que l'abeille est sensible au flux optique dorsal et enfin que l'abeille adapte sa vitesse à l'encombrement de l'environnement dans les plans vertical et horizontal. Tous ces résultats étayent le modèle proposé. Cependant une expérience finale suggère qu'au delà de l'aspect "réflexe" du contrôle du vol, l'apprentissage joue un rôle et module le comportement de vol. Ceci impose d'inclure un élément "cognitif" au schéma proposé. Cette thèse décrit, pour la première fois sous la forme d'un schéma fonctionnel, les principes mis en œuvre dans le contrôle 3D du vol d'un insecte par le flux optique. Le caractère explicite du modèle proposé, d'une part ouvre la voie à de nouvelles expériences comportementales susceptibles de le mettre en défaut ou d'en préciser les limites, d'autre part le rend directement applicable à la robotique mobile, aérienne ou spatiale.When an insect flies in its environment, the image of the surrounding objects moves on its retina. Several studies have shown that this angular movement, called "optic flow", plays a major role in the insect flight control. Flying insects seem to maintain the perceived optic flow at a prefered value, which makes them choose a "safe" position and a "safe" speed. We first designed a model based on the "optic flow regulation principle" recently proposed at our laboratory, which can account for observations and results previously shown on insects. We then performed behavioral experiments using free flying bees in controlled environments, which aimed at refuting the proposed model. Our results show a direct link between the ventral optic flow and the flight height. They also show that the honeybee is sensitive to the dorsal optic flow and that the honeybee can adjust its speed according to the cluttering of the environment in both the vertical and horizontal planes. All these results support the proposed model. The results of a last experiment suggest, however, that beyond the "reflex" part of the flight control system, a learning process may play a role and modulate the flight behavior. This last point requires that a learning process be incorporated into the model. This thesis for the first time proposes an explicit and functional scheme based on optic flow, describing the principles involved in the 3D flight control system of an insect. This model suggests new behavioral experiments liable to fault it. Because this model is explicit, it may be directly implemented onboard aerial or spatial robots

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Unmanned Vehicle Systems & Operations on Air, Sea, Land

Unmanned Vehicle Systems & Operations On Air, Sea, Land is our fourth textbook in a series covering the world of Unmanned Aircraft Systems (UAS) and Counter Unmanned Aircraft Systems (CUAS). (Nichols R. K., 2018) (Nichols R. K., et al., 2019) (Nichols R. , et al., 2020)The authors have expanded their purview beyond UAS / CUAS systems. Our title shows our concern for growth and unique cyber security unmanned vehicle technology and operations for unmanned vehicles in all theaters: Air, Sea and Land – especially maritime cybersecurity and China proliferation issues. Topics include: Information Advances, Remote ID, and Extreme Persistence ISR; Unmanned Aerial Vehicles & How They Can Augment Mesonet Weather Tower Data Collection; Tour de Drones for the Discerning Palate; Underwater Autonomous Navigation & other UUV Advances; Autonomous Maritime Asymmetric Systems; UUV Integrated Autonomous Missions & Drone Management; Principles of Naval Architecture Applied to UUV’s; Unmanned Logistics Operating Safely and Efficiently Across Multiple Domains; Chinese Advances in Stealth UAV Penetration Path Planning in Combat Environment; UAS, the Fourth Amendment and Privacy; UV & Disinformation / Misinformation Channels; Chinese UAS Proliferation along New Silk Road Sea / Land Routes; Automaton, AI, Law, Ethics, Crossing the Machine – Human Barrier and Maritime Cybersecurity.Unmanned Vehicle Systems are an integral part of the US national critical infrastructure The authors have endeavored to bring a breadth and quality of information to the reader that is unparalleled in the unclassified sphere. Unmanned Vehicle (UV) Systems & Operations On Air, Sea, Land discusses state-of-the-art technology / issues facing U.S. UV system researchers / designers / manufacturers / testers. We trust our newest look at Unmanned Vehicles in Air, Sea, and Land will enrich our students and readers understanding of the purview of this wonderful technology we call UV.https://newprairiepress.org/ebooks/1035/thumbnail.jp

Unmanned Systems Sentinel / 11 January 2016

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