Safe Navigation for Indoor Mobile Robots. Part I: A Sensor-based Navigation Framework

International audienceThis paper presents a first part, Part-I of two, of a complete exploration and navigation methodology that enables a robot to safely navigate in an unknown environment. Reactive sensor-based navigation tasks and control laws are derived from the interaction between the robot and its workspace. The perception is performed by a 2-D laser nge finder mounted on the robot. Reactive navigation tasks are defined based on the task function framework in a such a way that the robot can explore an unknown indoor environment without any reference rajectory computation. Obstacle avoidance is ensured as a straight property implicit to the definition of the navigation tasks. The stability and obustness of the derived control laws with respect to the model errors are analyzed. The experimental results validate the proposed methodology

Safe Navigation for Indoor Mobile Robots - PartII: Exploration, Self Localization and Map Building

International audienceThis paper is the second part of the author's contribution on the topic of Safe Navigation for Indoor Mobile Robots. It presents a new solution to the exploration, self localization and map building problem taking advantage of the sensor-based navigation framework presented in the paper: Safe Navigation for Indoor Mobile Robots - Part I: A Sensor-based Navigation Framework. The model of the indoor environment is structured as an hybrid representation, both topological and geometrical, which is incrementally built during the exploration task. The topological aspect of the model captures the connectivity and accessibility of the different places in the environment, and the geometrical model holds up an accurate robot localization and map building method. To overpass the problem of drift inherited to the odometry when the robot navigates in large scale environments, a new dead-reckoning method is proposed combining laser readings and feedback control inputs. Embedding the self-localization and map building problem in a sensor-based navigation framework improves both the quality and the robustness of the representation built during the exploration phase and authorizes a further use to achieve safe navigation tasks successfully. Experiments are shown which confirm the interests of the proposed methodology

Vehicle recognition and tracking using a generic multi-sensor and multi-algorithm fusion approach

International audienceThis paper tackles the problem of improving the robustness of vehicle detection for Adaptive Cruise Control (ACC) applications. Our approach is based on a multisensor and a multialgorithms data fusion for vehicle detection and recognition. Our architecture combines two sensors: a frontal camera and a laser scanner. The improvement of the robustness stems from two aspects. First, we addressed the vision-based detection by developing an original approach based on fine gradient analysis, enhanced with a genetic AdaBoost-based algorithm for vehicle recognition. Then, we use the theory of evidence as a fusion framework to combine confidence levels delivered by the algorithms in order to improve the classification 'vehicle versus non-vehicle'. The final architecture of the system is very modular, generic and flexible in that it could be used for other detection applications or using other sensors or algorithms providing the same outputs. The system was successfully implemented on a prototype vehicle and was evaluated under real conditions and over various multisensor databases and various test scenarios, illustrating very good performances

Research on a semiautonomous mobile robot for loosely structured environments focused on transporting mail trolleys

In this thesis is presented a novel approach to model, control, and planning the motion of a nonholonomic wheeled mobile robot that applies stable pushes and pulls to a nonholonomic cart (York mail trolley) in a loosely structured environment. The method is based on grasping and ungrasping the nonholonomic cart, as a result, the robot changes its kinematics properties. In consequence, two robot configurations are produced by the task of grasping and ungrasping the load, they are: the single-robot configuration and the robot-trolley configuration. Furthermore, in order to comply with the general planar motion law of rigid bodies and the kinematic constraints imposed by the robot wheels for each configuration, the robot has been provided with two motorized steerable wheels in order to have a flexible platform able to adapt to these restrictions. [Continues.

Towards new sensing capabilities for legged locomotion using real-time state estimation with low-cost IMUs

L'estimation en robotique est un sujet important affecté par les compromis entre certains critères majeurs parmi lesquels nous pouvons citer le temps de calcul et la précision. L'importance de ces deux critères dépend de l'application. Si le temps de calcul n'est pas important pour les méthodes hors ligne, il devient critique lorsque l'application doit s'exécuter en temps réel. De même, les exigences de précision dépendent des applications. Les estimateurs EKF sont largement utilisés pour satisfaire les contraintes en temps réel tout en obtenant une estimation avec des précisions acceptables. Les centrales inertielles (Inertial Measurement Unit - IMU) demeurent des capteurs répandus dnas les problèmes d'estimation de trajectoire. Ces capteurs ont par ailleurs la particularité de fournir des données à une fréquence élevée. La principale contribution de cette thèses est une présentation claire de la méthode de préintégration donnant lieu à une meilleure utilisation des centrales inertielles. Nous appliquons cette méthode aux problèmes d'estimation dans les cas de la navigation piétonne et celle des robots humanoïdes. Nous souhaitons par ailleurs montrer que l'estimation en temps réel à l'aide d'une centrale inertielle à faible coût est possible avec des méthodes d'optimisation tout en formulant les problèmes à l'aide d'un modèle graphique bien que ces méthodes soient réputées pour leurs coûts élevés en terme de calculs. Nous étudions également la calibration des centrales inertielles, une étape qui demeure critique pour leurs utilisations. Les travaux réalisés au cours de cette thèse ont été pensés en gardant comme perspective à moyen terme le SLAM visuel-inertiel. De plus, ce travail aborde une autre question concernant les robots à jambes. Contrairement à leur architecture habituelle, pourrions-nous utiliser plusieurs centrales inertielles à faible coût sur le robot pour obtenir des informations précieuses sur le mouvement en cours d'exécution ?Estimation in robotics is an important subject affected by trade-offs between some major critera from which we can cite the computation time and the accuracy. The importance of these two criteria are application-dependent. If the computation time is not important for off-line methods, it becomes critical when the application has to run on real-time. Similarly, accuracy requirements are dependant on the applications. EKF estimators are widely used to satisfy real-time constraints while achieving acceptable accuracies. One sensor widely used in trajectory estimation problems remains the inertial measurement units (IMUs) providing data at a high rate. The main contribution of this thesis is a clear presentation of the preintegration theory yielding in a better use IMUs. We apply this method for estimation problems in both pedestrian and humanoid robots navigation to show that real-time estimation using a low- cost IMU is possible with smoothing methods while formulating the problems with a factor graph. We also investigate the calibration of the IMUs as it is a critical part of those sensors. All the development made during this thesis was thought with a visual-inertial SLAM background as a mid-term perspective. Firthermore, this work tries to rise another question when it comes to legged robots. In opposition to their usual architecture, could we use multiple low- cost IMUs on the robot to get valuable information about the motion being executed