A mobile robotic platform for Autonomous Site Selection and Preparation (ASSP) was developed for an analogue deployment to Mauna Kea, Hawai‘i. A team of rovers performed an autonomous Ground Penetrating Radar (GPR) survey and constructed a level landing pad. They used interchangeable payloads that allowed the GPR and blade to be easily exchanged. Autonomy was accomplished by integrating the individual hardware devices with software based on the ArgoSoft framework previously developed at UTIAS. The rovers were controlled by an on-board netbook. The successes and failures of the devices and software modules are evaluated within. Recommendations are presented to address problems discovered during the deployment and to guide future research on the platform.

Robust localisation is a key requirement for autonomous vehicles. However, in order to achieve widespread adoption of this technology, we also require this function to be performed using low-cost hardware. Cameras are appealing due to their information-rich image content and low cost; however, camera-based localisation is difficult because of the problem of appearance change. For example, in outdoor en- vironments the appearance of the world can change dramatically and unpredictably with variations in lighting, weather, season and scene structure. We require autonomous vehicles to be robust under these challenging environmental conditions. This thesis presents Dub4, a vision-only localisation system for autonomous vehicles. The system is founded on the concept of experiences, where an "experience" is a visual memory which models the world under particular conditions. By allowing the system to build up and curate a map of these experiences, we are able to handle cyclic appearance change (lighting, weather and season) as well as adapt to slow structural change. We present a probabilistic framework for predicting which experiences are most likely to match successfully with the live image at run-time, conditioned on the robot's prior use of the map. In addition, we describe an unsupervised algorithm for detecting and modelling higher-level visual features in the environment for localisation. These features are trained on a per-experience basis and are robust to extreme changes in appearance, for example between rain and sun, or day and night. The system is tested on over 1500km of data, from urban and off-road environments, through sun, rain, snow, harsh lighting, at different times of the day and night, and through all seasons. In addition to this extensive offline testing, Dub4 has served as the primary localisation source on a number of autonomous vehicles, including the Oxford University's RobotCar, the 2016 Shell Eco-Marathon, the LUTZ PathFinder Project in Milton Keynes, and the GATEway Project in Greenwich, London.

Orientador: Prof. Dr. Luis Alberto Martinez Riascos / According to the Instituto Brasileiro de Geografia e Estatística (IBGE) in the sense of 2010, motor disability was the second kind of deficiency that most affected people, where 13.265.599 people claimed to have limited mobility, representing 7,0% of brazilian people. Many of these people are wheelchair users and suffer constantly by needing help from others to go up and down stairs in environments that contain no ramps, as in many schools, universities, houses, hospitals, bus stations and transportation facilities. In this work, several kind of locomotion mechanisms in the mobile robotics that can be used in the assistive technology will be studied. Firstly, an analysis will be made, pointing out the pros and cons of each one, regarding the execution of the obstacles overcoming function, with the least energy consumption. The epicyclic mechanism, very used not only in the mobile robotics but in other areas, was identified to be the most suitable to the application. Its structure was projected, improved and adapted to the wheelchair. Then, through a multicorp analysis with the Euler-Lagrange equation and the virtual work principle, the development of a model to represent the dynamic behavior of the system was possible. Because of that, the estimation of energetic efficiency in comparison to other wheelchair already available in the market (as the tracked wheelchairs which executes the same function), and also the identification of a situation that could jeopardize the wheelchair user (as during downhills obstacles overcoming), was possible. Therefore, the need of a speed controller implementation to guarantee the wheelchair user stability in theses situations was shown. The control system has shown satisfactory results, meeting the performance specifications, with control signals always in the operation range of work of the actuator. The wheelchair with epicyclic locomotion system has been shown to be superior to the tracked wheelchair in many aspects as: terrain adaptability, vibration, energy consumption, etc, what makes it a promising competitor in the area of assistive technology devoted to the obstacles overcoming. / Tese ( doutorado)- Universidade Federal do ABC. Programa de Pós-Graduação em Energia, 2017. / Segundo o Instituto Brasileiro de Geografia e Estatística (IBGE) no Censo 2010, a deficiência motora foi o segundo tipo de deficiência que mais incidiu sobre a população, onde 13.265.599 pessoas declararam ter dificuldade de locomoção, representando 7,0% da população brasileira. Muitas destas pessoas são cadeirantes e sofrem por constantemente precisar de ajuda externa para subir ou descer escadas em ambientes que não contém rampas, como em muitas escolas, universidades, casas, hospitais, shoppings, estações rodoviárias e meios de transporte. Neste trabalho, serão estudados diversos mecanismos de locomoção da área da robótica móvel que podem ser utilizados na área de tecnologia assistiva. Primeiramente, haverá uma análise, indicando os prós e contras de cada um, no que se refere a executar a função de superar obstáculos através de uma cadeira de rodas, com o menor consumo de energia. O mecanismo epicíclico, muito utilizado não só no campo darobóticamóvel, mas em outras áreas, foi identificado como o mais adequado à aplicação. Sua estrutura foi projetada, melhorada e adaptada à cadeira de rodas. Através de uma análise multicorpos com as equações de Euler-Lagrange e o princípio do trabalho virtual, foi possível desenvolver um modelo que representasse o comportamento dinâmico do sistema. Com isso foi possível estimar sua eficiência energética frente a outras cadeiras já disponíveis no mercado (como as cadeiras do tipo esteira que executam a mesma função), e identificar situações que pudessem por em risco o cadeirante (como na superação de obstáculos durante descidas). Mostrou-se, portanto, a necessidade de implementação de um controlador de velocidade para garantia de estabilidade ao cadeirante nestas situações. O sistema de controle mostrou ser estável, atendendo as especificações de desempenho, com sinais de controle sempre dentro dos limites do atuador. As cadeiras com sistema epicíclico mostraram-se superiores às do tipo esteira, em muitos aspectos tais como: adaptabilidade ao terreno, vibração, consumo de energia, etc, o que a torna uma concorrente promissora na área de tecnologia assistiva dedicada à superação de obstáculos.

The population growth associated with natural resources shortage, food demand increasing and the lack of manpower for agricultural activities generate important challenges to agriculture and engineering. The challenges imply the improvement of productivity with fewer resources, This scenario is consisted parameters that generally are in opposite directions. This work presents the development of a rover to agriculture (R2A) to support agriculturescouting tasks, the tasks will be in the future important tools to improve the productivity and enable the use of less agricultural supplies. The research presents the development of a rover for agriculture (R2A) to support scouting tasks; tasks that in the future will improve productivity and allowed the use of less agricultural supplies. The study begins with a bibliographic review of Robots for agriculture, Rovers, and agricultural Rovers developed by different research institutions. After the review is presented the work methodology based on mechanic and mechatronic design methodologies; in the development of the methodology are presented the general crop characteristics, the proposed of scouting tasks, the benchmarking developing mathematical models, CAD (Computer Aided Design ) models, simulations and tests in order to know the different features of the Rovers and agricultural robots. Using the knowledge gained in the course of work is proposed the concept of a rover for agriculture R2A, the concept is compared in simulations, and developed the detailed design using CAE tools (Computer Aided Engineering) after it built a prototype and tested. As results are presented comparative simulations of R2A, their mathematical modeling, R2A simulations in ideally conditions highlighting their skills, and finally R2A tests and comparison are presented. / O crescimento populacional associado à escassez de recursos naturais, a crescente demanda alimentar e a falta de mão de obra para as actividades agrícolas geram importantes desafios para a agricultura e a engenharia. Os desafios implicam a melhoria da produtividade com menos recursos. O cenário é constituido por parâmetros que geralmente estão em direções opostas. O trabalho apresenta o desenvolvimento de um rover para agricultura (R2A) para suportar tarefas de Scouting, tarefas que no futuro melhorarão a produtividade e permitirão o uso de menos subministros agrícolas. O estudo começa pela revisão bibliográfica de Robôs para agricultura, Rovers e Rovers agrícolas desenvolvidos por diferentes instituições de pesquisa. Apos a revisão é apresentada a metodologia do trabalho baseada nas metodologias de projeto mecânico e mecatrônico; no desenvolvimento da metodologia são apresentadas as caraterísticas das culturas de maneira geral, a proposta de tarefas de Scouting, o benchmarking desenvolvendo modelos matemáticos, modelos CAD (Computer Aided Design) simulações e testes com o intuito de conhecer as diferentes caraterísticas dos Rovers e Robôs agrícolas. Usando o conhecimento no decorrer do trabalho é proposto o conceito do rover para agricultura R2A, o conceito é comparado em simulações, e feito o projeto detalhado usando ferramentas CAE (Computer Aided Enginnerring), após é construído o protótipo, e testado. Como resultados são apresentadas simulações comparativas do R2A, a sua modelagem matemática, simulações do R2A em condições ideais, destacando as suas capacidades, e finalmente são apresentados os testes e comparações do R2A.

Nesta pesquisa são estudados aspectos relacionados à problemática da localização robótica, e um sistema de localização robótica é construído. Para determinação da localização de um robô móvel em relação a um mapa topológico do ambiente, é proposta uma solução determinística. Esta solução é empregada a fim de prover localização para problemas de rastreamento de posição, embora seja de interesse também a observação da eficácia, do método proposto, frente a problemas de localização global. O sistema proposto baseia-se no uso de vetores de atributos, compostos de medições momentâneas extraídas do ambiente através de sensoriamentos pertencentes à percepção do robô. Estimativas feitas a partir da odometria e leitura de sensores de ultra-som são utilizadas em conjunto nestes vetores de atributos, de forma a caracterizar as observações feitas pelo robô. Uma bússola magnética também é empregada na solução. O problema de localização é então resolvido como um problema de reconhecimento de padrões. A topologia do ambiente é conhecida, e a correlação entre cada local neste ambiente e seus atributos são armazenados através do uso de redes neurais artificiais. O sistema de localização foi avaliado de maneira experimental, em campo, em uma plataforma robótica real, e resultados promissores foram obtidos e são apresentados. / In this research aspects related to the robot localization problem have been studied. In order to determine the localization of a mobile robot in relation to a topological map of its environment, a deterministic solution has been proposed. This solution is applied to provide localization for position tracking problems, although it is also of interest to observe the performance of the proposed method applied to global localization problems. The proposed system is based on feature vectors, which are composed of momentaneous measures extracted from sensory data of the robots perception. Estimative made from odometry, sonars and magnetic compass readings are used together in these feature vectors, in order to characterize observed scenes by the robot. Thus, the localization problem is solved as a pattern recognition problem. The topology of the environment is known, and the correlation between each place of this environment and its features is stored using an artificial neural network. The localization system was experimentally evaluated, in a real robotic platform. The results obtained allow validation of the methodology.

A detecção e reconhecimento de objetos é uma tarefa fundamental em aplicações relacionadas à navegação autônoma de robôs móveis e veículos inteligentes. Com a evolução tecnológica nos sistemas sensoriais, surgiram equipamentos capazes de detectar e representar os elementos presentes no ambiente de forma tridimensional, em estruturas chamadas nuvem de pontos. Os sensores 3D geralmente capturam um grande volume de pontos em curtos intervalos de tempo, o que demanda técnicas robustas para processamento dessa informação além de tolerância a eventuais ruídos nos dados. Uma abordagem frequentemente utilizada na área de Visão Computacional para redução de dimensionalidade é a extração de features robustas, armazenando um subconjunto de informações representativas e simplificadas do conjunto de dados. Esta tese apresenta uma metodologia de classificação de objetos em nuvens de pontos 3D através da extração de features 3D globais. Foi desenvolvido um novo descritor 3D invariante à escala, translação e rotação denominado 3D-CSD (3D-Contour Sample Distances) para representação da superfície dos objetos presentes no ambiente, e utilizado um método de aprendizado supervisionado para reconhecimento de padrões. Os experimentos realizados envolveram o uso de Redes Neurais Artificiais para o reconhecimento de diferentes classes de objetos, avaliando e validando a metodologia proposta. Os resultados obtidos demostraram a viabilidade da aplicação desta abordagem para o reconhecimento de objetos em sistemas de percepção 3D. / Objects detection and recognition is a critical task in applications for mobile robots and intelligent vehicles autonomous navigation. With the advent of many 3D sensors, environment elements can be detected and represented in three-dimensional mode, in structures known as point clouds. 3D sensors usually capture a large amount of points at high rates, requiring robust techniques to process this information and also deal with noise on input data. A common approach in the Computer Vision field for dimensionality reduction is the use of robust features extraction techniques. This way, only a subset with representative and simplified information from the dataset is processed. This thesis presents a methodology for objects recognition in 3D point clouds using global 3D features extraction. A novel 3D descriptor invariant to scale, translation and rotation named 3D-CSD (3D-Contour Sample Distances) was developed to represent the objects surface, and a supervised learning method used for pattern recognition. The experiments were performed using Artificial Neural Networks for the recognition of different classes of objects, evaluating and validating the proposed methodology. Obtained results demonstrated the feasibility of this approach application for object recognition in 3D perception systems.

De acordo com a Organização Mundial da Saúde,cerca de 1,2milhões de pessoas no mundo morrem em acidentes de trânsito. Sistemas de assistência ao motorista e veículos autônomos podem diminuir o número de acidentes. Dentre as várias demandas existentes para viabilizar essa tecnologia, sistemas computacionais de percepção ainda permanecem sem uma solução definitiva. Dois deles, detecção de obstáculos e de via navegável, normalmente fazem uso de algoritmos sofisticados como técnicas de aprendizado supervisionado, que mostram resultados impressionantes quando treinados com bases de dados bem definidas e diversificadas.Entretanto, construir, manter e atualizar uma base de dados com exemplos de vários lugares do mundo e em diversas situações é trabalhoso e complexo. Assim, métodos adaptativos e auto-supervisionados mostram-se como boas alternativas para sistemas de detecção do futuro próximo. Neste contexto, esta tese apresenta um método para estimar obstáculose via navegável através de sensores de baixo custo (câmeras estereoscópicas), sem o uso de técnicas de aprendizado de máquina e de diversas suposições normalmente utilizadas por trabalhos já disponíveis na literatura. Esses métodos utilizando sensor estereoscópico foram comparados fazendo uso de sensores do tipo 3D-LIDAR e mostraram resultados semelhantes. Este sistema poderá ser usado como uma fase pré-processamento de dados para melhorar ou viabilizar métodos adaptativos de aprendizado. / World wide, an estimated 1.2million lives are lostin road crashes each year and Advanced Driver Assistance Systems (ADAS) and Self-driving cars promise to reduce this number. Among the various issues to complete this technology, perception systems are still an unsolved issues. Normally two of them, obstacle detection and road detection, make use of sophisticated algorithms such as supervised machine learning methods which can perform with impressive results if it was trained with good data sets. Since it is a complex and an expensive job to create and maintain data bases of scenarios from the entire world, adaptive and/or self-supervised methods are good candidates for detection systems in the near future. Due that, this thesis present a method to estimate obsta- cles and estimate the road terrain using low cost sensors (stereo camera), avoiding supervised machine learning techniques and the most common assumptions used by works presented in literature. These methods were compared with 3D-LIDAR approaches achieving similar results and thus it can be used as a pre-processing step to improve or allow adaptive methods with machine learning systems.

Orientadores: Paulo Augusto Valente Ferreira, Samuel Siqueira Bueno / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-23T20:27:15Z (GMT). No. of bitstreams: 1 Martins_RenatoJose_M.pdf: 2887206 bytes, checksum: cfdb6978d48e6f68b3ae81fad838d7ed (MD5) Previous issue date: 2013 / Resumo: Esta dissertação tem como escopo o tema de localização de um veículo terrestre que evolui em ambiente externo. O trabalho consiste no desenvolvimento de técnicas de percepção sensorial capazes de fornecer estimativas de pose (posição e orientação), aspecto fundamental para toda tarefa de navegação robótica. Sucintamente, os enfoques abordados utilizam-se de diferentes classes de sensores como encoders, lasers, GPS e suas combinações, de maneira a minimizar as incertezas intrínsecas de cada sensor. A principal contribuição do trabalho está em uma nova formulação de odometria por otimização, bem como suas extensões para a estimação concomitante de polarizações. É apresentado também um esquema de estimação determinística de poses em batelada no contexto da fusão odometria-GPS, além da definição de mapeamentos por funções suaves que viabilizam o uso de medidas de orientação descontínuas. As metodologias são formuladas, avaliadas em simulação e validadas experimentalmente com a plataforma robótica do projeto VERO (Veículo Robótico de Exterior) do CTI Renato Archer / Abstract: This dissertation addresses the problem of localizing a ground vehicle that navigates in an outdoor environment. The work consists in the development of sensorial perception and odometry techniques capable of furnishing pose estimates (position and attitude), a fundamental aspect of any robotic navigation task. In short, we focus on exploring different sensor classes, such as encoders, lasers, GPSs, and their combinations, in order to minimize the intrinsic uncertainties of each sensor. The main contribution of the work is a new odometry formulation and its extension for simultaneous bias estimation. We also present a deterministic batch estimation framework for the odometry-GPS fusion, as well as the definition of mappings by smooth functions of the orientation state component that allow the use of discontinuous heading measures. Methodologies are formulated, analysed in simulation and experimentaly validated using the VERO ("VEículo RObótico de Exterior", in Portuguese) robotic platform / Mestrado / Automação / Mestre em Engenharia Elétrica

La dégradation des terres dans le monde affecte directement plus d’un milliard d’hectares. Elle menace près de 35% des terres de la planète ainsi que les moyens de subsistance de deux milliards d’individus. Les estimations des pertes financières sont considérables chaque année. La dégradation des terres arides et semi-arides est une entrave au développement des pays concernés. Ce problème demeure insoluble et la communauté internationale organisée au sein de plusieurs instances n’ayant pas trouvé de solution pérenne, assiste impuissante à la progression du fléau malgré les efforts et expérimentations menées à travers le monde. L’urgence est de mise pour trouver des solutions qui soient à la fois techniques, sociales, économiques et culturelles.Ce constat appelle des réponses et la nécessité d’exploiter des approches basées sur les avancées des nouvelles techniques. La robotique mobile est une piste qui peut contribuer dans un avenir proche à freiner ce phénomène. Cette technologie recèle d’immenses possibilités dans plusieurs domaines : médical, aide à la personne, militaire, agricole et bien entendu dans la restauration des écosystèmes. La thèse s’inscrit dans le projet R-Stepps pour évaluer les capacités de résilience d’une solution basée sur les techniques robotiques. Elle expérimente une flotte de robots pour lutter contre la dégradation des terres et l’avancée de la désertification. Nous avons étudié et exploré les moyens de mettre au point une flotte de robots nomades pour remplir des missions de restauration des écosystèmes dégradés. Pour construire des systèmes mécatroniques simples et robustes nous avons mis au point des robots limités à une seule tâche.Nous avons développé une plateforme expérimentale composée de cinq robots capables de se coordonner et d’accomplir chacun une tâche spécifique (forage, plantage, arrosage, surveillance, guidage). Le démonstrateur sert à valider les modèles de navigation, de localisation, de planification ainsi que les procédures de plantation et de surveillance de l’environnement / Land degradation directly affects over a billion hectares throughout the world. It is a threat to almost 35% of the planet’s land as well as to the means of subsistence of two billion people. Estimations of heavy financial losses are increasing year after year. The degradation of arid and semi-arid lands is a serious drawback to the development of the countries concerned. This problem is today unsolved and since a number of organizations within the international community have not found an appropriate, perennial solution, we are powerlessly witnessing the progression of this plague despite the efforts and experiments carried out all over the world. It has become extremely urgent to find solutions that are not only technical, but also social, economic and cultural.This assessment calls for action and the need to exploit different approaches based on the most recent advanced technology. Mobile robotics are a lead to explore and may well contribute to slowing down this phenomenon in the near future. This technology offers endless possibilities in many fields: healthcare, personal assistance, military, agriculture and of course the restoring of ecosystems. It will therefore be necessary to follow the evolution of this sector and observe its effects on the environment and society in general in those regions affected by the phenomenon. Our findings aim to propose a technical solution, and the more general questions regarding societal consequences are not examined; our main concern is to demonstrate and evaluate the resilience capacity of a solution based on robotic techniques. This document is part of the R-Stepps project to experiment a fleet of robots to combat land degradation and reverse the progress of desertification. Its main mission is reforestation, maintenance and surveillance of such zones. The fleet of robots is composed of various platforms, each with a specific function. By limiting each robot to one task, this will ensure their solidity and simple design

Abstract The Earth’s magnetic field (MF) has been used for navigation for centuries. Man-made metallic structures, such as steel reinforcements in buildings, cause local distortions to the Earth’s magnetic field. Up until the recent decade, these distortions have been mostly considered as a source of error in indoor localization, as they interfere with the compass direction. However, as the distortions are temporally stable and spatially distinctive, they provide a unique magnetic landscape that can be used for constructing a map for indoor localization purposes, as noted by recent research in the field. Most approaches rely on manually collecting the magnetic field map, a process that can be both tedious and error-prone. In this thesis, the map is collected by a robotic platform with minimal sensor equipment. It is shown that a mere magnetometer along with odometric information suffices to construct the map via a simultaneous localization and mapping (SLAM) procedure that builds on the Rao-Blackwellized particle filter as means for recursive Bayesian estimation. Furthermore, the maps are shown to achieve decimeter level localization accuracy that combined with the extremely low-cost hardware requirements makes the presented methods very lucrative for domestic robots. In addition, general auxiliary methods for effective sampling and dealing with uncertainties are presented. Although the methods presented here are devised in mobile robotics context, most of them are also applicable to mobile device-based localization, for example, with little modifications. Magnetic field localization offers a promising alternative to WiFi-based methods for achieving GPS-level localization indoors. This is motivated by the rapidly growing indoor location market. / Tiivistelmä Maan magneettikenttään perustuvat kompassit ovat ohjanneet merenkäyntiä vuosisatojen ajan. Rakennusten metallirakenteet aiheuttavat paikallisia häiriöitä tähän magneettikenttään, minkä vuoksi kompasseja on pidetty epäluotettavina sisätiloissa. Vasta viimeisen vuosikymmenen aikana on huomattu, että koska nämä häiriöt ovat ajallisesti pysyviä ja paikallisesti hyvin erottelevia, niistä voidaan muodostaa jokaiselle rakennukselle yksilöllinen häiriöihin perustuva magneettinen kartta, jota voidaan käyttää sisätiloissa paikantamiseen. Suurin osa tämänhetkisistä magneettikarttojen sovelluksista perustuu kartan käsin keräämiseen, mikä on sekä työlästä että tarjoaa mahdollisuuden inhimillisiin virheisiin. Tämä väitöstutkimus tarttuu ongelmaan laittamalla robotin hoitamaan kartoitustyön ja näyttää, että robotti pystyy itsenäisesti keräämään magneettisen kartan hyödyntäen pelkästään magnetometriä ja renkaiden antamia matkalukemia. Ratkaisu perustuu faktoroituun partikkelisuodattimeen (RBPF), joka approksimoi täsmällistä rekursiivista bayesilaista ratkaisua. Robotin keräämien karttojen tarkkuus mahdollistaa paikannuksen n. 10 senttimetrin tarkkuudella. Vähäisten sensori- ja muiden vaatimusten takia menetelmä soveltuu erityisen hyvin koti- ja parvirobotiikkaan, joissa hinta on usein ratkaiseva tekijä. Tutkimuksessa esitellään lisäksi uusia apumenetelmiä tehokkaaseen näytteistykseen ja epävarmuuden hallintaan. Näiden käyttöala ei rajoitu pelkästään magneettipaikannukseen- ja kartoitukseen. Robotiikan sovellusten lisäksi tutkimusta motivoi voimakkaasti kasvava tarve älylaitteissa toimivalle sisätilapaikannukselle. Tämä avaa uusia mahdollisuuksia paikannukselle ympäristöissä, joissa GPS ei perinteisesti toimi.