Outdoor view recognition based on landmark grouping and logistic regression

Vision-based robot localization outdoors has remained more elusive than its indoors counterpart. Drastic illumination changes and the scarceness of suitable landmarks are the main difficulties. This paper attempts to surmount them by deviating from the main trend of using local features. Instead, a global descriptor called landmark-view is defined, which aggregates the most visually-salient landmarks present in each scene. Thus, landmark co-occurrence and spatial and saliency relationships between them are added to the single landmark characterization, based on saliency and color distribution. A suitable framework to compare landmark-views is developed, and it is shown how this remarkably enhances the recognition performance, compared against single landmark recognition. A view-matching model is constructed using logistic regression. Experimentation using 45 views, acquired outdoors, containing 273 landmarks, yielded good recognition results. The overall percentage of correct view classification obtained was 80.6%, indicating the adequacy of the approach.Peer ReviewedPostprint (author’s final draft

Scouting algorithms for field robots using triangular mesh maps

Labor shortage has prompted researchers to develop robot platforms for agriculture field scouting tasks. Sensor-based automatic topographic mapping and scouting algorithms for rough and large unstructured environments were presented. It involves moving an image sensor to collect terrain and other information and concomitantly construct a terrain map in the working field. In this work, a triangular mesh map was first used to represent the rough field surface and plan exploring strategies. A 3D image sensor model was used to simulate collection of field elevation information.A two-stage exploring policy was used to plan the next best viewpoint by considering both the distance and elevation change in the cost function. A greedy exploration algorithm based on the energy cost function was developed; the energy cost function not only considers the traveling distance, but also includes energy required to change elevation and the rolling resistance of the terrain. An information-based exploration policy was developed to choose the next best viewpoint to maximise the information gain and minimize the energy consumption. In a partially known environment, the information gain was estimated by applying the ray tracing algorithm. The two-part scouting algorithm was developed to address the field sampling problem; the coverage algorithm identifies a reasonable coverage path to traverse sampling points, while the dynamic path planning algorithm determines an optimal path between two adjacent sampling points.The developed algorithms were validated in two agricultural fields and three virtual fields by simulation. Greedy exploration policy, based on energy consumption outperformed other pattern methods in energy, time, and travel distance in the first 80% of the exploration task. The exploration strategy, which incorporated the energy consumption and the information gain with a ray tracing algorithm using a coarse map, showed an advantage over other policies in terms of the total energy consumption and the path length by at least 6%. For scouting algorithms, line sweeping methods require less energy and a shorter distance than the potential function method

Avaliação de algoritmos de exploração de ambientes por robôs móveis

Trabalho de conclusão de curso (graduação)—Universidade de Brasília, Faculdade de Tecnologia, Curso de Graduação em Engenharia de Controle e Automação, 2018.Atividades como exploração e cobertura auxiliam robôs a descobrir o ambiente, maximizando a região coberta tanto fisicamente quanto sensorialmente. O foco desse trabalho é a avaliação de diferentes técnicas exploratórias com robôs móveis sem construção de mapa, tais técnicas são baseadas em direcionamento probabilístico. Para isso é utilizado um modelo de robô móvel Pioneer 3-DX, presente no LARA (Laboratório de Automação e Robótica), dotado de sensor visual Microsoft Kinect e utilizando o ambiente de desenvolvimento aberto ROS (Robot Operating System)The exploration and coverage problem help mobile robots to know their environment and maximize the total area which is covered by the body of robot or by their sensors. This work presents the evaluation of different exploration techniques of mobile robots without any map construction or representation, and these techniques are based in stochastic goals. For this purpose, is used a Pioneer 3-DX robot model, from the Automation and Robotics Laboratory (LARA), and is equipped with a Microsoft Kinect visual sensor and works with Robot Operating System (ROS) framework

Perception and Motion: use of Computer Vision to solve Geometry Processing problems

Computer vision and geometry processing are often see as two different and, in a certain sense, distant fields: the first one works on two-dimensional data, while the other needs three dimensional information. But are 2D and 3D data really disconnected? Think about the human vision: each eye captures patterns of light, that are then used by the brain in order to reconstruct the perception of the observed scene. In a similar way, if the eye detects a variation in the patterns of light, we are able to understand that the scene is not static; therefore, we're able to perceive the motion of one or more object in the scene. In this work, we'll show how the perception of the 2D motion can be used in order to solve two significant problems, both dealing with three-dimensional data. In the first part, we'll show how the so-called optical flow, representing the observed motion, can be used to estimate the alignment error of a set of digital cameras looking to the same object. In the second part, we'll see how the detected 2D motion of an object can be used to better understand its underlying geometric structure by means of detecting its rigid parts and the way they are connected

Planification interactive de trajectoire en Réalité Virtuelle sur la base de données géométriques, topologiques et sémantiques

Pour limiter le temps et le coût de développement de nouveaux produits, l’industrie a besoin d’outils pour concevoir, tester et valider le produit avec des prototypes virtuels. Ces prototypes virtuels doivent permettre de tester le produit à toutes les étapes du Product Lifecycle Management (PLM). Beaucoup d’opérations du cycle de vie du produit impliquent la manipulation par un humain des composants du produit (montage, démontage ou maintenance du produit). Du fait de l’intégration croissante des produits industriels, ces manipulations sont réalisées dans un environnement encombré. La Réalité Virtuelle (RV) permet à des opérateurs réels d’exécuter ces opérations avec des prototypes virtuels. Ce travail de recherche introduit une nouvelle architecture de planification de trajectoire permettant la collaboration d’un utilisateur de RV et d’un système de planification de trajectoire automatique. Cette architecture s’appuie sur un modèle d’environnement original comprenant des informations sémantiques, topologiques et géométriques. Le processus de planification automatique de trajectoire est scindé en deux phases. Une planification grossière d’abord exploitant les données sémantiques et topologiques. Cette phase permet de définir un chemin topologique. Une planification fine ensuite exploitant les données sémantiques et géométriques détermine un trajectoire géométrique dans le chemin topologique défini lors de la planification grossière. La collaboration entre le système de planification automatique et l’utilisateur de RV s’articule autour de deux modes : en premier lieu, l’utilisateur est guidé sur une trajectoire pré-calculée à travers une interface haptique ; en second lieu, l’utilisateur peut quitter la solution proposée et déclencher ainsi une re-planification. L’efficacité et l’ergonomie des ces deux modes d’interaction est enrichie grâce à des méthodes de partage de contrôle : tout d’abord, l’autorité du système automatique est modulée afin de fournir à la fois un guidage prégnant lorsque l’utilisateur le suit, et plus de liberté à l’utilisateur (un guidage atténué) lorsque celui-ci explore des chemins alternatifs potentiellement meilleurs. Ensuite, lorsque l’utilisateur explore des chemins alternatifs, ses intentions sont prédites (grâce aux données géométriques associées aux éléments topologiques) et intégrées dans le processus de re-planification pour guider la planification grossière. Ce mémoire est organisé en cinq chapitres. Le premier expose le contexte industriel ayant motivé ces travaux. Après une description des outils de modélisation de l’environnement, le deuxième chapitre introduit le modèle multi-niveaux de l’environnement proposé. Le troisième chapitre présente les techniques de planification de trajectoire issues de la robotique et détaille le processus original de planification de trajectoire en deux phases développé. Le quatrième introduit les travaux précurseurs de planification interactive de trajectoire et les techniques de partage de contrôle existantes avant de décrire les modes d’interaction et les techniques de partage de contrôle mises en œuvre dans notre planificateur interactif de trajectoire. Enfin le dernier chapitre présente les expérimentations menées avec le planificateur de trajectoire et en analyse leurs résultats. ABSTRACT : To save time and money while designing new products, industry needs tools to design, test and validate the product using virtual prototypes. These virtual prototypes must enable to test the product at all Product Lifecycle Management (PLM) stages. Many operations in product’s lifecycle involve human manipulation of product components (product assembly, disassembly or maintenance). Cue to the increasing integration of industrial products, these manipulations are performed in cluttered environment. Virtual Reality (VR) enables real operators to perform these operations with virtual prototypes. This research work introduces a novel path planning architecture allowing collaboration between a VR user and an automatic path planning system. This architecture is based on an original environment model including semantic, topological and geometric information. The automatic path planning process split in two phases. First, coarse planning uses semantic and topological information. This phase defines a topological path. Then, fine planning uses semantic and geometric information to define a geometrical trajectory within the topological path defined by the coarse planning. The collaboration between VR user and automatic path planner is made of two modes: on one hand, the user is guided along a pre-computed path through a haptic device, on the other hand, the user can go away from the proposed solution and doing it, he starts a re-planning process. Efficiency and ergonomics of both interaction modes is improved thanks to control sharing methods. First, the authority of the automatic system is modulated to provide the user with a sensitive guidance while he follows it and to free the user (weakened guidance) when he explores possible better ways. Second, when the user explores possible better ways, his intents are predicted (thanks to geometrical data associated to topological elements) and integrated in the re-planning process to guide the coarse planning. This thesis is divided in five chapters. The first one exposes the industrial context that motivated this work. Following a description of environment modeling tools, the second chapter introduces the multi-layer environment model proposed. The third chapter presents the path planning techniques from robotics research and details the two phases path planning process developed. The fourth introduce previous work on interactive path planning and control sharing techniques before to describe the interaction modes and control sharing techniques involved in our interactive path planner. Finally, last chapter introduces the experimentations performed with our path planner and analyses their results

Sensitive Skin for Robotics

This thesis explores two novel ways of reducing the data complexity of tactile sensing. The thesis begins by examining the state-of-the art in tactile sensing, not only examining the sensor construction and interpretation of data but also the motivation for these designs. The thesis then proposes two methods for reducing the complexity of data in tactile sensing. The first is a low-power tactile sensing array exploiting a novel application of a pressure-sensitive material called quantum tunnelling composite. The properties of this material in this array form are shown to be beneficial in robotics. The electrical characteristics of the material are also explored. A bit-based structure for representing tactile data called Bitworld is then defined and its computational performance is characterised. It is shown that this bit-based structure outperforms floating-point arrays by orders of magnitude. This structure is then shown to allow high-resolution images to be produced by combining low resolution sensor arrays with equivalent functional performance to a floating-point array, but with the advantages of computational efficiency. Finally, an investigation into making Bitworld robust in the presence of positional noise is described with simulations to verify that such robustness can be achieved. Overall, the sensor and data structure described in this thesis allow simple, but effective tactile systems to be deployed in robotics without requiring a significant commitment of computational or power resources on the part of a robot designer.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Des cartes combinatoires pour la construction automatique de modèles d'environnement par un robot mobile

Ce travail s'inscrit dans la problématique classique de localisation et de cartographie simultanées pour un robot mobile évoluant en milieu intérieur supposé inconnu. Son originalité réside dans la définition d'un modèle de carte très structuré fondé sur un outil algébrique appelé « carte combinatoire », qui combine plusieurs types de représentations géométriques (modèles surfaciques et cartes basées sur des primitives géométriques) et fournit des informations topologiques telles que les liens d'adjacence. Nous détaillons la chaîne algorithmique permettant de construire des cartes en ligne suivant ce modèle, avec un robot équipé d'un télémètre laser à balayage : il s'agit d'adapter les techniques habituelles basées sur le filtrage de Kalman afin de gérer les relations d'adjacence (appariement de chaînes polygonales, définition de points de cassure virtuels, mises à jour géométrique et topologique spécifiques). Des résultats expérimentaux illustrent et valident les divers mécanismes mis en oeuvre. ABSTRACT : This thesis focuses on the well-known Simultaneous Localization And Map-building (SLAM) problem for indoor mobile robots. The novelty of this work lies in the definition of a well-structured map model based on an algebraic tool called « combinatorial map » which combines different kinds of geometric representations (space-based, grid-based as well as feature-based formats) and provides topological information such as adjacency links between map elements. We describe the whole algorithm designed to build maps on line according to this model, using a robot equipped with a laser scanner. Classical techniques relying on Kalman filtering are adapted in order to deal with adjacency relationships (via polyline matching, the use of virtual break-points and specific geometric and topological update operations). Exeprimental results are presented to illustrate and validate the various mecanisms involved in this process