Search

Accompanying the digital revolution in agriculture, agricultural robotics is experiencing a new boom, as evidenced by recent advances in robot autonomy, image recognition, visual perception of the environment and geolocation. These advances now offer new perspectives, particularly to support the practices advocated in the field of agro-ecology.; Accompagnant la révolution numérique de l'agriculture, la robotique agricole connaît un nouvel essor, comme en témoignent les récents progrès réalisés sur l'autonomie des robots, la reconnaissance d'images, la perception visuelle de l'environnement et la géolocalisation. Ces avancées offrent aujourd'hui de nouvelles perspectives, notamment pour accompagner les pratiques prônées dans le domaine de l'agroécologie.

National audience

International audience

International audience; Le renversement latéral apparaît comme étant la cause principale des accidents de véhicules légers tout-terrain (quads) dans le milieu agricole. Par conséquent, lestimation et la prédiction des situations potentielles de renversement sont deux étapes clés pour ensuite aborder le développement de systèmes de sécurité active appliqués aux véhicules tout-terrain. Si plusieurs travaux de recherche ont été réalisés dans le cadre des véhicules routiers, peu de ces développements peuvent être directement utilisés dans le cadre des véhicules rapides se déplaçant en milieu naturel, de part la spécificité et la forte variabilité des conditions de contact mises en jeu. Cet article a pour objet ledéveloppement d'un algorithme permettant l'estimation et la prédiction d'un critère de stabilité dynamique appelé Transfert de Charge Latéral (TCL), afin d'anticiper les situations de renversement latéral sur sol naturel. Cet algorithme repose sur un modèle dynamique du véhicule sur lequel est bâti un observateur par backstepping permettant d'estimer en ligne les conditions d'adhérence du véhicule qui impactent largement sa propension au renversement. La capacité de l'indicateur de risque à anticiper les situations de renversement a été testée à la fois au travers de simulations numériques mais aussi en grandeur réelle sur un quad Kymco Mxer 150.

International audience; This paper is aimed to present the development of an automatic guidance system dedicated to a four-wheel steering vehicle. The attractive feature is that, despite of sliding phenomena, both lateral and angular deviations can be explicitly controlled with respect to the path to be followed. This is particularly useful to compensate the crabway motion on sloping terrain and maintain the direction of the vehicle parallel to the slope. On the contrary, in order to reduce soil compaction generally caused by the load of several wheels in the same track, the path following can be carried out with a chosen crab angle. Relying on a kinematic model extended with sliding parameters, a backstepping control approach is considered. Actual experiments carried out with a four-wheel-steering vehicle on a low adherent sloping terrain demonstrate the capabilities of the proposed control law.

[Departement_IRSTEA]EA [TR1_IRSTEA]TESAD / MOST; International audience; The evolution of population needs, together with the necessity of environment preservation, rise important issues related to the way the human production have to progress. It is for instance the case in agriculture area, where the production have to increase in order to feed a growing population, while the environmental damage must decrease. Since current production processes favor one or the other of these objectives, new tools needs to be developed in order to address both of them. In this framework, mobile robotic can constitute a promising solution, since an accurate work can be achieved autonomously for long time range, offering new potentialitiesto increase production level while preserving environment. Nevertheless, to solve such a challenge, the considered devices must be accurate, fast and reliable despite of their motion in an off-road context, inducing rough dynamics and many risks for their integrity. The research leaded in the TIMS Research Federation aims at developing autonomous mobile robots in off-road environment able to meet such requirements. This paper presents a navigation algorithm, which contributes to tackle some of the problems rising in such a context. More precisely, a reliable and accurate path tracking algorithm is presented. Advances in localization, motion control and stability control are more particularly described. Above the agriculture area, the application of such automatic device can bring important help for intervention in hazardous areas in general.

[Departement_IRSTEA]EA [TR1_IRSTEA]TESAD / MOST; International audience; The growing popularity of quad bikes in the agricultural area is unfortunately accompanied by an increasing number of accidents and particularly lateral rollovers. Then, the estimation of hazardous situations, whatever the grip conditions and pilot behavior, is a preliminary step in the design of active security devices dedicated to All-Terrain vehicles (ATVs). This paper proposes a rollover metric dedicated to the lateral hazardous situations estimation. It is based on the computation of the Lateral Load Transfer (LLT) obtained, on one hand from a roll projection of the quad bike with its pilot and on the other hand from a backstepping observer dedicated to grip conditions estimation. Capabilities of the proposed observer and metric to estimate hazardous situations on natural ground are demonstrated via both advanced simulations and full scale experiments.

International audience; In this paper, automatic path tracking of a four-wheel-steering vehicle in presence of sliding is adressed. The attractive feature of such a steering system is that, despite of sliding phenomena, both lateral and angular deviations can be explicitly controlled. Indeed, previous research has demonstrated that high-precision path tracking on a low grip terrain can be achieved with two-wheel-steering vehicles. However, in that case, only the lateral deviation is satisfactorily close to zero, the angular deviation is non null in order to compensate for sliding effects. In this paper, previous adaptive control laws are extended to the case of four-wheel-steering mobile robots with the aim to servo both lateral and angular deviations. Relying on an extended kinematic model, a backstepping control approach, considering successively front and rear steering control, has been designed. Actual experiments have been carried out on a low adherent sloping terrain with a four-wheel-steering vehicle equipped with a single RTK-GPS. They demonstrate the capabilities of the proposed control law and its robustness in actual all-terrain conditions.

International audience; The use of centrifugal spreaders for application of granular fertilizers raises concern about application accuracy. These spreaders enable to distribute almost uniform deposits with regularly spaced parallel tramlines but lead over and under fertilizer application when distances separating the successive tractor trajectories are not constant or if paths are not parallel between them. The aim of this study is to propose an optimization-based method to compute optimal variables for uniform fertilizer application. Mechanical constraints are also introduced so that the calculated parameters can be afterwards used as reference variables for the control of the spreader. The resulting improvements are illustrated by numerical examples for a field with geometrical singularities.

International audience

[Departement_IRSTEA]EA [TR1_IRSTEA]TESAD / TECHPROPRE; We study an approach for the optimization of spreading performed by centrifugal spreaders in order to minimize environmental effects due to application errors. Faced with a large scale problem, we divide the domain of study into subdomains so that each tramline is individually dealt with. In order to take into account the mechanical limits of the device, some inequality constraints are introduced. After cost function discretization, we use an augmented lagrangian algorithm associated with a L-BFGS technique to solve the problem. Results are presented for parallel and non parallel paths.

International audience

[Departement_IRSTEA]EA [TR1_IRSTEA]TESAD / MOST; If the development of algorithms dedicated for path tracking control of mobile robots is a well-known problem under the rolling without sliding condition (for vehicles moving on road for example), transfer of such control techniques are not always relevant for the case of mobile robots moving off road. Indeed, the application of control techniques developed under this assumption for off road vehicles demonstrates some unexpected behaviour, which depreciated considerably precision of a trajectory tracking (especially when vehicle executes a curve on a low adherent surface or when moving on a slope). Moreover, actuators used in natural environment are often more powerful and consequently less reactive, what introduces delays in vehicle dynamics. Such delays are emphasized by inertial effects, as the stability of off road vehicles requires the use of more important mass (and then inertia). An algorithm, taking into account for such phenomena and preserves the precision of path tracking for mobile robots, is presented. Capabilities of this approach are investigated through full-scale experiments, on farm tractor. Assistance of agricultural works indeed constitutes the application field of theoretical developments presented. If localization problem is often an important topic for those robots, it is not considered here. Indeed, the approach here proposed is focused on single exteroceptive sensor (a Real Time Kinematic GPS), which supplies an accuracy of 2cm on coordinates signal at a sampling frequency of 10Hz. In addition, an angular sensor, based on steering wheel is present to ensure servoing of low-level actuator. Steering angle is here the unique control variable to be calculated, and velocity of robots is tuned manually and viewed, in control law, as a measured parameter, which can be variable. Considering this measurement system and the numerous parameters required by a wheel-soil interaction model in a dynamical approach, the use of complex dynamical models (such as Pacejka or LuGree) is rejected. Instead, an extended kinematical model, adapted to describe sliding effects is designed. It takes account for vehicle behaviour (including sliding, which inevitably occurs on low adherent terrain) by the integration of two sliding parameters homogeneous to sideslip angles. However, it is necessary to estimate these parameters in order to feed the model and access to an accurate description of vehicle dynamics, with respect to the unique sensor approach. As considered parameters cannot be measured directly, an observer-based approach is then proposed, turned into a suitable way, in accordance with the duality between control and observation problems. As an accurate model is then available, and considering this non-linear model can be turned into a linear one using a chained system form, a control law can so be designed. This law is able, on one part to compensate sliding phenomena in slow varying conditions, with respect to observer performances, but, on the other part, delays presents on actual vehicle (due to actuator properties and inertial effects) are neglected. As a result, accuracy of path tracking is preserved when sliding phenomenon can be considered as slow varying, but overshoots are present during transient phases. It is mainly the case during curve transition, appearing at begin or end of a curve. Considering, that in path tracking case the entire trajectory to be followed is known and assuming on that it is possible to extract a model of the actuator response to a step of steering consign, a Model Predictive Control is introduced in the algorithm. Predictive action is here applied only on a part of control law, dedicated to the curvature servoing. An horizon of prediction is defined, allowing extraction of a future consign relevant with respect to reference path future configuration. Using the low level model, the actual steering angle can be predicted and error in the future between desired response and actual one can be computed. Then, the prediction algorithm consists in finding the set of control on the horizon of prediction, which minimizes this error. The first value of this set is then applied on the part of control dedicated to curvature servoing. As a result, overshoots are considerably limited. Moreover, even if only a low level model is considered, this predictive action is able to compensate implicitly delays induced by inertial effects. The accuracy is then also preserved during transient phases of curvature. Finally, the global algorithm allows to achieve a high accurate tracking for off road mobile robots, whatever the path to be followed is, whatever the conditions of adherence are, and whatever configuration of terrain is (flat or sloppy ground). Accuracy reached by this control techniques (including adaptive and predictive actions), is close to sensor precision (considering the noise introduced by the roll effects of vehicle) during actual path following. Full scale experiments show that the vehicle is able to stay inside an acceptation interval of ±15cm. With respect to the application field, such accuracy meets the farmer expectation for agricultural tasks.

National audience

National audience

International audience; Working on new equipments to increase agricultural productivity and safety, reducing human action hardness , Cemagref and Lasmea have developed an help guidance system for agricultural vehicles. The aim of this system is to help the operator to guide the machine in order to give more attention to the order task. To r each this goal, we use a visual perception of the environment because this sensor gives a solution well adapted to lots of situations. This project began with researches on a visual guidance system for a lawn mower in 1990 and has been adaptated to the development of the same system for a combine harvester in 1995. We model the lawn mower with a virtual axle, use trajectory generation to guide it, and localize the vehicle at each iteration to insure the servoing task. For the combine harvester, we decide to use the task function approach 23] and then to control the combine harvester directly in the sensor space.

National audience; Depuis le debut des annees 90, nous travaillons sur un systeme de contrôle temps reel applique au guidage d'engins agricoles par vision monoculaire. Il s'agit d'alleger les tâches de pilotage confiees aux conducteurs d'engins en proposant un co-pilotage par un systeme entierement automatique. Ces tâches concernent particulierement les travaux de recolte (moisson), de fenaison, et de labour. Dans cet article, nous nous interessons a l'aspect contrôle du vehicule par vision monoculaire a partir de la detection de l'interface fauche/non-fauche dans l'image. Le vehicule considere est une moissonneuse-batteuse. L'approche fonction de tâche introduite par Samson et Espiau a la n des annees 80 est utilisee. Un premier contrôleur est elabore pour les recoltes sur terrains plats. Un second est propose pour tenir compte des effets de la pente.

International audience

We present experimental results of a visual servoing approach to control an agricultural mobile machine. To detect the limit between mowed and unmowed natural zones, we use an original region segmentation algorithm based on a Markovian modeling of a set of sites. With the 2D informations extracted by the image processing algorithm, a visual servoing unit allows the machine to follow the detected limit. All these algorithms are implanted on a parallel architecture., Nous présentons une approche commande référencée vision (CRV) pour asservir une machine agricole. Pour détecter la limite entre une zone fauchée et une zone non fauchée, nous utilisons un algorithme original de segmentation en régions basée sur un modèle Markovien d'un ensemble de sites. A partir des informations 2D issues de l'algorithme de traitement d'images, un module basé sur la CRV permet à la machine de suivre la limite détectée. Tous ces algorithmes sont implantés sur une architecture parallèle.