International audience

International audience

In this paper, the problem associated with accurate control of a two-wheel steering mobile robot following a path is addressed thanks to a backstepping control strategy. This approach involves an observer to estimate the grip conditions, based on previous work, and the proposed control algorithm for the front axle. Since the significant parameters of the grip conditions are available from the observer, namely the sideslip angles and the cornering stiffnesses, it is then suitable to include them into an algorithm to control mobile robots and obtain a more accurate path tracking. This is made possible by gathering into a single backstepping approach both kinematic and dynamic models. This new point of view permits to take account of both kinematic and dynamic behaviors and grip parameters in the control law. The proposed approach is experimentally evaluated at different speeds and compared with two other state-of-the-art path tracking algorithms and evaluated for several values of lateral deviations.

Many agricultural tasks are known to be dangerous for human operators, the environment, and human health in general. The increasing pressure both on safety and on production levels motivates the development of new methodologies and technologies. The rising of off-road mobile robots for agricultural application appears to be a promising contribution to required innovations. It both permits to limit the exposure of people to hazardous products and to achieve difficult and repetitive tasks. Nevertheless, to be fully efficient, autonomous robots have to ensure a high level of accuracy, while carrying potentially heavy tools, possibly in harsh conditions. It is especially the case of spraying, for which accuracy is a key challenge for reducing environmental impacts. The use of huge robots for spraying might seem to be a straightforward solution, by simply automating existing machines. Nevertheless, a simple automation does not reduce directly the environmental impact of human activities (soil compaction, energy, reduction of the use of chemical products). Moreover, huge machines are not necessarily an advantage when considering safety aspects (rollover risk and maneuverability). As a result, a solution based on the cooperation of at least two mobile robots, moving from either side of a vine row, is investigated in this paper thanks to Ultra Wide Band (UWB) technology.

In this paper, the problems associated with accurate path tracking control in off-road conditions is addressed with model-based adaptive control. In particular, the estimation of grip conditions is investigated through the derivation of a new observer and by gathering kinematic and dynamic models into a single framework. This new reference point employs a unique observer regardless of the velocity of the robots. Previous approaches necessitated the switching of models depending upon the phenomena encountered as well as robot dynamics. The observer proposed here allows an accurate and reactive estimation of sliding. This permits to feed relevantly a control law based on an extended kinematic model, enabling accurate path tracking, even in harsh conditions and when facing significant dynamic effects such as spin around.