Vision-based assistance for wheelchair navigation along corridors

International audienceIn case of motor impairments, steering a wheelchair can become a hazardous task. Typically, along corridors, joystick jerks induced by uncontrolled motions are source of wall collisions. This paper describes a vision based assistance solution for safe indoor semi-autonomous navigation purposes. To this aim, the control process is based on a visual servoing process designed for wall avoidance purposes. As the patient manually drives the wheelchair, a virtual guide is defined to progressively activate an automatic trajectory cor- rection. The proposed solution does not require any knowledge of the environment. Experiments have been conducted over corridors that present different configurations and illumination conditions. Results demonstrate the ability of the system to smoothly and adaptively assist people during their motions

Design and calibration of a specialized polydioptric camera rig

The development of advanced computational machines does not necessarily provide solutions to all the scientific problems in the research. It has been observed in the nature that all creatures have evolved highly exclusive sensory organs depending on their habitat and the form of availability of the resources they utilize for their survival. In this project, a novel omnidirectional camera rig is proposed that is exclusively designed to operate for highly specified operations and tasks in the field of mobile robots. Navigation problems on uneven terrains and detection of the moving objects while the robot is itself in motion are the core problems that omnidirectional systems tackle. The proposed omnidirectional system is a compact and a rigid vision system with dioptric cameras that provide a 360° field-of-view in horizontal and vertical, with no blind spot in their site plus a high resolution stereo camera is mounted to monitor anterior field-of-view for precise results with depth information of the scene. Structure from motion algorithm is adapted and implemented to prove the validity of the design of the proposed camera rig and a toolbox is developed to calibrate similar systems

Using human-inspired models for guiding robot locomotion

Cette thèse a été effectuée dans le cadre du projet européen Koroibot dont l'objectif est le développement d'algorithmes de marche avancés pour les robots humanoïdes. Dans le but de contrôler les robots d'une manière sûre et efficace chez les humains, il est nécessaire de comprendre les règles, les principes et les stratégies de l'homme lors de la locomotion et de les transférer à des robots. L'objectif de cette thèse est d'étudier et d'identifier les stratégies de locomotion humaine et créer des algorithmes qui pourraient être utilisés pour améliorer les capacités du robot. La contribution principale est l'analyse sur les principes de piétons qui guident les stratégies d'évitement des collisions. En particulier, nous observons comment les humains adapter une tâche de locomotion objectif direct quand ils ont à interférer avec un obstacle en mouvement traversant leur chemin. Nous montrons les différences entre la stratégie définie par les humains pour éviter un obstacle non-collaboratif et la stratégie pour éviter un autre être humain, et la façon dont les humains interagissent avec un objet si se déplaçant en manier simil à l'humaine. Deuxièmement, nous présentons un travail effectué en collaboration avec les neuroscientifiques de calcul. Nous proposons une nouvelle approche pour synthétiser réalistes complexes mouvements du robot humanoïde avec des primitives de mouvement. Trajectoires humaines walking-to-grasp ont été enregistrés. L'ensemble des mouvements du corps sont reciblées et proportionnée afin de correspondre à la cinématique de robots humanoïdes. Sur la base de cette base de données des mouvements, nous extrayons les primitives de mouvement. Nous montrons que ces signaux sources peuvent être exprimées sous forme de solutions stables d'un système dynamique autonome, qui peut être considéré comme un système de central pattern generators (CPGs). Sur la base de cette approche, les stratégies réactives walking-to-grasp ont été développés et expérimenté avec succès sur le robot humanoïde HRP-2 au LAAS-CNRS. Dans la troisième partie de la thèse, nous présentons une nouvelle approche du problème de pilotage d'un robot soumis à des contraintes non holonomes par une porte en utilisant l'asservissement visuel. La porte est représentée par deux points de repère situés sur ses supports verticaux. La plan géométric qui a été construit autour de la porte est constituée de faisceaux de hyperboles, des ellipses et des cercles orthogonaux. Nous montrons que cette géométrie peut être mesurée directement dans le plan d'image de la caméra et que la stratégie basée sur la vision présentée peut également être lié à l'homme. Simulation et expériences réalistes sont présentés pour montrer l'efficacité de nos solutions.This thesis has been done within the framework of the European Project Koroibot which aims at developing advanced algorithms to improve the humanoid robots locomotion. It is organized in three parts. With the aim of steering robots in a safe and efficient manner among humans it is required to understand the rules, principles and strategies of human during locomotion and transfer them to robots. The goal of this thesis is to investigate and identify the human locomotion strategies and create algorithms that could be used to improve robot capabilities. A first contribution is the analysis on pedestrian principles which guide collision avoidance strategies. In particular, we observe how humans adapt a goal-direct locomotion task when they have to interfere with a moving obstacle crossing their way. We show differences both in the strategy set by humans to avoid a non-collaborative obstacle with respect to avoid another human, and the way humans interact with an object moving in human-like way. Secondly, we present a work done in collaboration with computational neuroscientists. We propose a new approach to synthetize realistic complex humanoid robot movements with motion primitives. Human walking-to-grasp trajectories have been recorded. The whole body movements are retargeted and scaled in order to match the humanoid robot kinematics. Based on this database of movements, we extract the motion primitives. We prove that these sources signals can be expressed as stable solutions of an autonomous dynamical system, which can be regarded as a system of coupled central pattern generators (CPGs). Based on this approach, reactive walking-to-grasp strategies have been developed and successfully experimented on the humanoid robot HRP at LAAS-CNRS. In the third part of the thesis, we present a new approach to the problem of vision-based steering of robot subject to non-holonomic constrained to pass through a door. The door is represented by two landmarks located on its vertical supports. The planar geometry that has been built around the door consists of bundles of hyperbolae, ellipses, and orthogonal circles. We prove that this geometry can be directly measured in the camera image plane and that the proposed vision-based control strategy can also be related to human. Realistic simulation and experiments are reported to show the effectiveness of our solutions

A Doorway Detection and Direction (3Ds) System for Social Robots via a Monocular Camera

In this paper, we propose a novel algorithm to detect a door and its orientation in indoor settings from the view of a social robot equipped with only a monocular camera. The challenge is to achieve this goal with only a 2D image from a monocular camera. The proposed system is designed through the integration of several modules, each of which serves a special purpose. The detection of the door is addressed by training a convolutional neural network (CNN) model on a new dataset for Social Robot Indoor Navigation (SRIN). The direction of the door (from the robot’s observation) is achieved by three other modules: Depth module, Pixel-Selection module, and Pixel2Angle module, respectively. We include simulation results and real-time experiments to demonstrate the performance of the algorithm. The outcome of this study could be beneficial in any robotic navigation system for indoor environments

Metodología de Navegación de robots móviles para detección de vanos y discontinuidades en su trayectoria

En la presente tesis de maestría, se pretende plantear el estudio e implementación de 2 estrategias de navegación autónoma que permitan a una plataforma robótica llegar al cumplimiento de la tarea asignada en entornos interiores estáticos, incluyendo trabajar con algunas discontinuidades, tales como puertas y/o pasillos. La primera estrategia que se evaluara será un sistema hibrido, teniendo en cuenta un sistema neuro-difuso, donde la parte de redes neuronales en combinación con comportamientos reactivos estimaran una decisión en cuanto a la orientación, y la parte difusa entregara mediante el uso de reglas, la velocidad a seguir por la plataforma, teniendo en cuenta las restricciones físicas y mecánicas del robot, el segundo método a analizar estará basado en estrategias estadísticas y/o probabilísticas, donde se enfocara en redes bayesianas. Se elaboraran pruebas en diversos entornos y cada una con diversos niveles de complejidad, donde datos representativos podrán ser comparados con métricas de desempeño y así poder establecer en alguna medida la mejor opciónIn this master thesis, intends to present the study and implementation of 2 autonomous navigation strategies that lead to a robotic platform to fulfilling the task assigned in normal indoor environments, including work with some discontinuities, such as Corridor or hallways. The first strategy to be evaluated will be a hybrid system, taking into account a neuronal-fuzzy system, where the part of neuronal networks in combination with reactive behaviors estimate a decision on orientation, and the fuzzy logic part delivered through the use of rules , The speed to be followed by the platform, taking into account the physical and mechanical constraints of the robot, the second method to analyze will be based on statistical and / or probabilistic strategies, where it will focus on Bayesian networks. Tests will be developed in different environments and each with different levels of complexity, where representative data can be compared with performance metrics and thus be able to establish to some extent the best optionMagister en Automatización y Contro

Ground robotics in tunnels: Keys and lessons learned after 10 years of research and experiments

The work reported in this article describes the research advances and the lessons learned by the Robotics, Perception and Real-Time group over a decade of research in the field of ground robotics in confined environments. This study has primarily focused on localization, navigation, and communications in tunnel-like environments. As will be discussed, this type of environment presents several special characteristics that often make well-established techniques fail. The aim is to share, in an open way, the experience, errors, and successes of this group with the robotics community so that those that work in such environments can avoid (some of) the errors made. At the very least, these findings can be readily taken into account when designing a solution, without needing to sift through the technical details found in the papers cited within this text

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications

Recent Advances in Multi Robot Systems

To design a team of robots which is able to perform given tasks is a great concern of many members of robotics community. There are many problems left to be solved in order to have the fully functional robot team. Robotics community is trying hard to solve such problems (navigation, task allocation, communication, adaptation, control, ...). This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. It is focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. The book consists of 16 chapters introducing both basic research and advanced developments. Topics covered include kinematics, dynamic analysis, accuracy, optimization design, modelling, simulation and control of multi robot systems