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FSR, the International Conference on Field and Service Robotics, is a robotics Symposium which has established over the past ten years the latest research and practical results towards the use of field and service robotics in the community with particular focus on proven technology. The first meeting was held in Canberra, Australia, in 1997. Since then the meeting has been held every two years in the pattern Asia, America, Europe. Field robots are non-factory robots, typically mobile, that operate in complex, and dynamic environments: on the ground (of Earth or planets), under the ground, underwater, in the air or in space. Service robots are those that work closely with humans to help them with their lives. This book presents the results of the sixth edition of Field and Service Robotics, FSR07, held in Chamonix, France, on 9th - 12th July 2007. The conference provided a forum for researchers, professionals and robot manufacturers to exchange up-to-date technical knowledge and experience. This book offers a collection of a broad range of topics including: Underwater Robots and Systems, Autonomous Navigation for Unmanned Aerial Vehicles, Simultaneous Localization and Mapping, Climbing Robotics, Sensor Fusion.

Les premiers documents attestant l’utilisation d’une chaise à roues utilisèe pour transporter une personne avec un handicap datent du 6ème siècle en Chine. À l’exception des fauteuils roulants pliables X-frame inventés en 1933, 1400 ans d’évolution de la science humaine n’ont pas changé radicalement la conception initiale des fauteuils roulants. Pendant ce temps, les progrès de l’informatique et le développement de l’intelligence artificielle depuis le milieu des années 1980 ont conduit inévitablement à la conduite de recherches sur des fauteuils roulants intelligents.Plutôt que de se concentrer sur l’amélioration de la conception sous-jacente, l’objectif principal de faire un fauteuil roulant intelligent est de le rendre le plus accessible. Même si l’invention des fauteuils roulants motorisés ont partiellement atténué la dépendance d’un utilisateur à d’autres personnes pour la réalisation de leurs actes quotidiens, certains handicaps qui affectent les mouvements des membres, le moteur ou la coordination visuelle, rendent impossible l’utilisationd?un fauteuil roulant électrique classique. L’accessibilité peut donc être interprétée comme l’idéed’un fauteuil roulant adaptée à la pathologie de l’utilisateur de telle sorte que il / elle soit capabled’utiliser les outils d’assistance.S’il est certain que les robots intelligents sont prêts à répondre à un nombre croissant deproblèmes dans les industries de services et de santé, il est important de comprendre la façon dont les humains et les utilisateurs interagissent avec des robots afin d’atteindre des objectifs communs. En particulier dans le domaine des fauteuils roulants intelligents d’assistance, la préservation du sentiment d’autonomie de l’utilisateur est nécessaire, dans la mesure où la lib-erté individuelle est essentielle pour le bien-être physique et social. De façon globale, ce travail vise donc à caractériser l’idée d’une assistance par contrôle partagé, et se concentre tout particulièrement sur deux problématiques relatives au domaine de la robotique d’assistance appliquée au fauteuil roulant intelligent, à savoir une assistance basée sur la vision et la navigation en présence d’humains.En ciblant les tâches fondamentales qu’un utilisateur de fauteuil roulant peut avoir à exécuter lors d’une navigation en intérieur, une solution d’assistance à bas coût, basée vision, est conçue pour la navigation dans un couloir. Le système fournit une assistance progressive pour les tâches de suivi de couloir et de passage de porte en toute sécurité. L’évaluation du système est réalisée à partir d’un fauteuil roulant électrique de série et robotisé. A partir de la solutionplug and play imaginée, une formulation adaptative pour le contrôle partagé entre l’utilisateur et le robot est déduite. De plus, dans la mesure où les fauteuils roulants sont des dispositifs fonctionnels qui opèrent en présence d’humains, il est important de considérer la question des environnements peuplés d’humains pour répondre de façon complète à la problématique de la mobilité en fauteuil roulant. En s’appuyant sur les concepts issus de l’anthropologie, et notam-ment sur les conventions sociales spatiales, une modélisation de la navigation en fauteuil roulant en présence d’humains est donc proposée. De plus, une stratégie de navigation, qui peut être intégrée sur un robot social (comme un fauteuil roulant intelligent), permet d’aborder un groupe d’humains en interaction de façon équitable et de se joindre à eux de façon socialement acceptable.Enfin, à partir des enseignements tirés des solutions proposées d’aide à la mobilité en fauteuil roulant, nous pouvons formaliser mathèmatiquement un contrôle adaptatif partagé pour la planification de mouvement relatif à l’assistance à la navigation. La validation de ce formalismepermet de proposer une structure générale pour les solutions de navigation assistée en fauteuil roulant et en présence d’humains. Earliest records of a wheeled chair used to transport a person with disability dates back to the 6th century in China. With the exception of the collapsible X-frame wheelchairs invented in 1933, 1400 years of human scientific evolution has not radically changed the initial wheelchair design. Meanwhile, advancements in computing, and the development of artificial intelligence since the mid 1980s, has inevitably led to research on Intelligent Wheelchairs. Rather than focusing on improving the underlying design, the core objective of making a wheelchair intelligent is to make it more accessible. Even though the invention of the powered wheelchairs have partially mitigated a user's dependence on other people for their daily routines, some disabilities that affect limb movements, motor or visual coordination, make it impossible for a user to operate a common electrically powered wheelchair. Accessibility can also thus be thought of as the idea, where the wheelchair adapts to the user malady such that he/she is able to utilize its assistive capabilities to the fullest.While it is certain that intelligent robots are poised to address a growing number of issues in the service and medical care industries, it is important to resolve how humans and users interact with robots in order to accomplish common objectives. Particularly in the assistive intelligent wheelchair domain, preserving a sense of autonomy with the user is required, as individual agency is essential for his/her physical and social well being. This work thus aims to globally characterize the idea of assistive shared control while particularly devoting the attention to two issues within the intelligent assistive wheelchair domain viz. vision-based assistance and human-aware navigation. Recognizing the fundamental tasks that a wheelchair user may have to execute in indoor environments, we design low-cost vision-based assistance framework for corridor navigation. The framework provides progressive assistance for the tasks of safe corridor following and doorway passing. Evaluation of the framework is carried out on a robotised off-the-shelf wheelchair. From the proposed plug and play design, we infer an adaptive formulation for sharing control between user and robot. Furthermore, keeping in mind that wheelchairs are assistive devices that operate in human environments, it is important to consider the issue of human-awareness within wheelchair mobility. We leverage spatial social conventions from anthropology to surmise wheelchair navigation in human environments. Moreover, we propose a motion strategy that can be embedded on a social robot (such as an intelligent wheelchair) that allows it to equitably approach and join a group of humans in interaction. Based on the lessons learnt from the proposed designs for wheelchair mobility assistance, we can finally mathematically formalize adaptive shared control for assistive motion planning. In closing, we demonstrate this formalism in order to design a general framework for assistive wheelchair navigation in human environments.

This paper considers the problem of sensor self-calibration in mobile robotics by only using a single point feature (e.g. a source of light). In particular, the problem of determining the extrinsic parameters of a bearing sensor mounted on a mobile platform (e.g. a camera) and simultaneously estimating the parameters describing the systematic error in the odometry system is discussed. Special attention is devoted to investigate the dependence of the observability properties of these parameters on the chosen robot trajectory. The main contribution provided by this paper is the introduction of a new method to deal with estimation problems in the framework of mobile robotics. Specifically, a calibration problem has been considered. However, the same method can be adopted to solve other fundamental estimation problems. The method is based on the theory of distributions which exploits all the system Lie symmetries. Regarding the considered calibration problem this method allows analytically detecting the combinations of the calibration parameters which are observable for a given robot trajectory. Experiments are provided to validate the results. International audience

Robots and Humans have to share the same environment more and more often. In the aim of steering robots in a safe and convenient manner among humans it is required to understand how humans interact with them. This work focuses on collision avoidance between a human and a robot during locomotion. Having in mind previous results on human obstacle avoidance, as well as the description of the main principles which guide collision avoidance strategies, we observe how humans adapt a goal-directed locomotion task when they have to interfere with a mobile robot. Our results show differences in the strategy set by humans to avoid a robot in comparison with avoiding another human. Humans prefer to give the way to the robot even when they are likely to pass first at the beginning of the interaction.

Purpose of review. In recent years, legged robots locomotion has been transitioning from mostly flat ground in controlled settings to generic indoor and outdoor environments, approaching now real industrial scenarios. This paper aims at documenting some of the key progress made in legged locomotion control that enabled this transition. Recent findings. Legged locomotion control makes extensive use of numerical trajectory optimization and its online implementation, Model Predictive Control. A key progress has been how this optimization is handled, with refined models and refined numerical methods. This led the legged locomotion research community to heavily invest in and contribute to the development of new optimization methods and efficient numerical software. International audience

Perception of and reasoning about dynamic environments is pertinent for mobile robotics and still constitutes one of the major challenges. To work in these environments, the mobile robot must perceive the environment with sensors; measurements are uncertain and normally treated within the estimation framework. Such an approach enables the mobile robot to model the dynamic environment and follow the evolution of its environment. With an internal representation of the environment, the robot is thus able to perform reasoning and make predictions to accomplish its tasks successfully. Systems for tracking the evolution of the environment have traditionally been a major component in robotics. Industries are now beginning to express interest in such technologies. One particular example is the application within the automotive industry for adaptive cruise control [Coué et al., 2002], where the challenge is to reduce road accidents by using better collision detection sys- tems. The major requirement of such a system is a robust tracking system. Most of the existing target-tracking algorithms use an object-based represen- tation of the environment. However, these existing techniques must explicitly consider data association and occlusion. In view of these problems, a grid- based framework, the Bayesian occupancy filter (BOF) [Coué et al., 2002, 2003], has been proposed.

This paper introduces a simple and very efficient strategy to extrinsically calibrate a bearing sensor (e.g. a camera) mounted on a mobile robot and simultaneously estimate the parameters describing the systematic error of the robot odometry system. The paper provides two contributions. The first one is the analytical computation to derive the part of the system which is observable when the robot accomplishes circular trejectories. This computation consists in performing a local decomposition of the system, based on the theory of distributions. In this respect, this paper represents the first application of the distribution theory in the frame-work of mobile robotics. Then, starting from this decomposition, a method to efficiently estimate the parameters describing both the extrinsic bearing sensor calibration and the odometry calibration is derived (second contribution). Simulations and experiments with the robot e-Puck equipped with encoder sensors and a camera validate the approach. International audience

Visual servoing (see [1] for an introduction to basic approaches) consists in controlling the motionof a robot by using computer vision data. Visual servoing schemes aim to minimize an error definedbetween a vector s of visual features derived from image measurements, and the vector s∗ of thedesired values of the features (which correspond to the reference position). A first classical visualservoing scheme is the image-based visual servoing (IBVS), that employs for s a set of features thatare directly available in the image data. Another is position-based visual servoing, where s is a setof robot position parameters that have to be estimated from image data.The classical IBVS approach is considered in the sequel. It consists in using the image coordinatesof a set of points to define the feature vector s. They are compared to their coordinates in a referenceimage taken at the desired camera position to control the robot motion. Stability and convergenceof IBVS has been studied but remains challenging [2]. Visual servoing will be done in the so-calledeye-in-hand configuration, in which the camera is mounted on the robot.An holonomic 3 degrees-of-freedom robot is considered. Its configuration is given by its coordinates(x, y) in the plane and its heading θ. The robot is equipped with a line-scan camera (a camerathat captures a single row of pixels, i.e an image line). For the sake of simplicity, the camera andthe robot pose are assumed to be the same.This work aims to compute the set of camera poses from which IBVS will converge to the referencepose (that corresponds to the reference image). Since classical IBVS is done by matching featurepoints between the current image and the reference image, we also need to check that the featurepoints always stay in the camera field of view. International audience