Este trabalho apresenta o desenvolvimento dos algoritmos de controle de um robô móvel autônomo para coleta de lixo. O objetivo do robô é coletar latas de refrigerante espalhadas pelo chão. O sistema de navegação do robô foi implementado utilizando a arquitetura denominada \"Motor-Schema\". Essa arquitetura fornece um método para projetar comportamentos primitivos que atuam em forma paralela para realizar ações robóticas inteligentes em resposta aos estímulos do ambiente. O sistema de controle apresentado foi constituído por vários comportamentos primitivos que, coordenados, permitiram ao robô explorar de forma segura um ambiente desconhecido, detectar e coletar o lixo e levá-lo num depósito determinado. Os algoritmos desenvolvidos foram testados utilizando uma ferramenta de simulação 2D denominada Player/Stage. Os resultados obtidos mostraram que a solução apresentada é adequada para resolver a aplicação robótica de coleta de lixo. / This work presents the control system for an autonomous mobile robot for soda can collection. The navigation system is implemented using a reactive architecture called \"Motor-Schema\". This architecture provides a methodology to design primitive behaviors that can act in a distributed and parallel manner to yield intelligent robotic actions in response to environmental stimuli. The control system is composed of several primitive behaviors, which enable the robot explore an unknown environment, detect and collect the soda cans and navigate toward a soda can reservoir. The algorithms are tested using Player/Stage, a software for 2D simulation. The results show that the solution is suitable for soda can collection.

Este trabalho apresenta o desenvolvimento dos algoritmos de controle de um robô móvel autônomo para coleta de lixo. O objetivo do robô é coletar latas de refrigerante espalhadas pelo chão. O sistema de navegação do robô foi implementado utilizando a arquitetura denominada \"Motor-Schema\". Essa arquitetura fornece um método para projetar comportamentos primitivos que atuam em forma paralela para realizar ações robóticas inteligentes em resposta aos estímulos do ambiente. O sistema de controle apresentado foi constituído por vários comportamentos primitivos que, coordenados, permitiram ao robô explorar de forma segura um ambiente desconhecido, detectar e coletar o lixo e levá-lo num depósito determinado. Os algoritmos desenvolvidos foram testados utilizando uma ferramenta de simulação 2D denominada Player/Stage. Os resultados obtidos mostraram que a solução apresentada é adequada para resolver a aplicação robótica de coleta de lixo. / This work presents the control system for an autonomous mobile robot for soda can collection. The navigation system is implemented using a reactive architecture called \"Motor-Schema\". This architecture provides a methodology to design primitive behaviors that can act in a distributed and parallel manner to yield intelligent robotic actions in response to environmental stimuli. The control system is composed of several primitive behaviors, which enable the robot explore an unknown environment, detect and collect the soda cans and navigate toward a soda can reservoir. The algorithms are tested using Player/Stage, a software for 2D simulation. The results show that the solution is suitable for soda can collection.

Mobile robots are commonly used to achieve tasks involving tracking a desired trajectory and following a predefined path in different types of terrains that have different surface characteristics. A mobile robot can perform the same navigation task task over different surfaces if the tracking performance and accuracy are not essential. However, if the tracking performance is the main objective, due to changing the characteristics of wheel-ground interaction, a single set of controller parameters or an equation of motion might be easily failing to guarantee a desired performance and accuracy. The interaction occurring between the wheels and ground can be integrated into the system model so that the performance of the mobile robot can be enhanced on various surfaces. This modeling approach related to wheel-ground interaction can also be incorporated into the motion controller. In this thesis study, modeling studies for a two wheeled differential drive mobile robot and a steerable four-wheeled robot vehicle are carried out. A strategy to achieve better tracking performance for a differential drive mobile robot is developed by introducing a procedure including the effects of external wheel forces / i.e, traction, rolling and lateral. A new methodology to represent the effects of lateral wheel force is proposed. An estimation procedure to estimate the parameters of external wheel forces is also introduced. Moreover, a modeling study that is related to show the effects of surface inclination on tracking performance is performed and the system model of the differential drive mobile robot is updated accordingly. In order to accomplish better trajectory tracking performance and accuracy for a steerable four-wheeled mobile robot, a modeling work that includes a desired trajectory generator and trajectory tracking controller is implemented. The slippage is defined via the slip velocities of steerable front and motorized rear wheels of the mobile robot. These slip velocities are obtained by using the proposed slippage estimation procedure. The estimated slippage information is then comprised into the system model so as to increase the performance and accuracy of the trajectory tracking tasks. All the modeling studies proposed in this study are tested by using simulations and verified on experimental platforms.

This thesis deals with the design and implementation of autonomous robot with using of the platform ROS. Its goal is to get to know the ROS and use it to implement autonomous control of real robot Leela.

Afin de permettre une navigation autonome d'un robot dans un environnement, le robot doit être capable de percevoir son environnement. Dans la littérature, d'une manière générale, les robots perçoivent leur environnement en utilisant des capteurs de type sonars, cameras et lidar 2D. L'introduction de nouveaux capteurs, nommés lidar 3D, tels que le Velodyne HDL-64E S2, a permis aux robots d'acquérir plus rapidement des données 3D à partir de leur environnement. La première partie de cette thèse présente une technique pour la calibrage des capteurs lidar 3D. La technique est basée sur la comparaison des données lidar à un modèle de vérité de terrain afin d'estimer les valeurs optimales des paramètres de calibrage. La deuxième partie de la thèse présente une technique pour la localisation et la détection de fermeture de boucles pour les robots autonomes. La technique est basée sur l'extraction et l'indexation des signatures de petite-taille à partir de données lidar 3D. Les signatures sont basées sur les histogrammes de l'information de normales de surfaces locale extraite à partir des données lidar en exploitant la disposition des faisceaux laser dans le dispositif lidar / In order to autonomously navigate in an environment, a robot has to perceive its environment correctly. Rich perception information from the environment enables the robot to perform tasks like avoiding obstacles, building terrain maps, and localizing itself. Classically, outdoor robots have perceived their environment using vision or 2D lidar sensors. The introduction of novel 3D lidar sensors such as the Velodyne device has enabled the robots to rapidly acquire rich 3D data about their surroundings. These novel sensors call for the development of techniques that efficiently exploit their capabilities for autonomous navigation.The first part of this thesis presents a technique for the calibration of 3D lidar devices. The calibration technique is based on the comparison of acquired 3D lidar data to a ground truth model in order to estimate the optimal values of the calibration parameters. The second part of the thesis presents a technique for qualitative localization and loop closure detection for autonomous mobile robots, by extracting and indexing small-sized signatures from 3D lidar data. The signatures are based on histograms of local surface normal information that is efficiently extracted from the lidar data. Experimental results illustrate the developments throughout the manuscript

Since their introduction in the 1950s, industrial Automated Guided Vehicles (AGV) have gone from automatic machinery limited by hardware to complex robots limited by software, called Autonomous Mobile Robots. Small and medium businesses need to be able to utilize cutting-edge technology. Therefore, this research focuses on deploying mapless AMRs on cheap open source AMRs in dynamic industrial environments. The study implements Dijkstra’s and A-STAR algorithms on a simulated Turtlebot3 model deployed in a Gazebo rendering of an industrial warehouse with moving objects added. The Turtlebot3 model traverses the environment where time and distance results are observed. The results shown in the research indicate that Dijkstra’s algorithm is barely affected by the change of the initial map state, while the A-STAR algorithm performed worse on average. Future work should focus on minimizing the sensors needed and continue testing with more algorithms, but early tests show promising results.

No description available.

Tato práce se zabývá vytvořením lokalizačního a navigačního systému mobilního robota pro vnitřní prostředí pomocí frameworku ROS. Stručně je zde představen projekt, v rámci kterého diplomová práce vznikla, a jeho cíle. V rešeršní části je v krátkosti popsán ROS framework, simulační prostředí Gazebo a senzory, kterými robot disponuje. Následuje vytvoření modelu robota a simulačního prostředí, v němž jsou vyzkoušeny lokalizační, navigační a další rutiny. V experimentální části je provedeno testování senzorů a popsáno využití jejich výstupů. Následně jsou upraveny a otestovány algoritmy ze simulace na reálném robotovi. V závěru jsou popsány vytvořené vzdělávací minihry. Hlavním výstupem této práce je funkční stavový automat, který umožňuje manuální ovládání, zadávání cílů pro navigaci a v případě potřeby zajistí autonomní nabití robota.

This thesis deals with design of navigation system for autonomous mobile robots, which is based on the infrared light. The system is based on measuring the relavive angles using landmarks in the enviroment that make the robot can orient and recognize its absolute position in an environment in which it operates.

Autonomous lawn mowers have been available to consumers for more than 20 years. During this period, advancements in embedded device computations and sensor performance have led to improvements in the reliability of these robots. Despite recent improvements, the opportunity for further innovation of such systems remains significant. Currently, many autonomous robots rely on electric wires installed underground to delimit the boundaries of the lawn. Such a configuration is simple, but more effective autonomous solutions are available. This thesis focuses on the analysis and related implementation of both localisation and mapping features for autonomous lawn mowers. Heterogeneous sensors and their different configurations are investigated and an Adaptive Extended Kalman Filter is proposed to fuse their measurements. This technique improves the pose estimation of the autonomous lawn mower, which is then exploited by the mapping module. Based on Bayesian’s inference, the mapping module updates the knowledge of the map based on direct interactions with the environment. The final results highlight the importance of precise localisation as the bottleneck for the development of new features. The improved pose estimation enables the employment of a virtual boundary, but it is not accurate enough to precisely map the presence of objects in the environment. Advanced features which could be developed from the proposed configuration are related to deterministic coverage algorithms and the interaction with lawn objects. / Autonoma gräsklippare har varit tillgängliga för konsumenter i mer än 20 år. Under denna period har framsteg inom beräkningar av inbyggda enheter och sensorprestanda lett till förbättringar av tillförlitligheten hos dessa robotar. Trots de senaste förbättringarna är möjligheten till innovation av sådana system fortfarande betydande. Autonoma robotar har fortfarande begränsade funktioner. De förlitar sig på elektriska ledningar installerade under jord för att avgränsa gräsmattans gränser, som de reagerar på utan resonemang. En sådan konfiguration anses nu vara föråldrad och mer effektiva autonoma lösningar finns tillgängliga. Den här avhandlingen fokuserar på att använda för närvarande tillgängliga tekniker för att designa de kärnmoduler som behövs för att förbättra kapaciteten hos dessa system. Analysen och relaterad implementering av både lokaliserings och kartläggningsfunktioner för autonoma gräsklippare presenteras. Heterogena sensorer och deras olika konfigurationer undersöks och ett Adaptive Extended Kalman Filter föreslås för att smälta samman deras mätningar. Denna teknik förbättrar poseuppskattningen av den autonoma gräsklipparen, som sedan utnyttjas av kartläggningsmodulen. Det valda tillvägagångssättet för den senare, baserat på Bayesians slutledning, lyckas uppdatera kunskapen om kartan baserat på direkta interaktioner med omgivningen. De slutliga resultaten belyser vikten av exakt lokalisering som den verkliga flaskhalsen för utvecklingen av nya funktioner. Den förbättrade positionsuppskattningen gör det möjligt att definiera en virtuell gräns. Definitionen inte tillräckligt korrekt för att korrekt kartlägga förekomsten av objekt i miljön Exempel på avancerade funktioner från den föreslagna konfigurationen är implementeringen av deterministiska täckningsalgoritmer och interaktionen med gräsmattaobjekt. / I tosaerba autonomi sono disponibili per i consumatori da oltre 20 anni. Durante questo periodo, i progressi nei calcoli dei dispositivi integrati e nelle prestazioni dei sensori hanno portato a miglioramenti nell’affidabilità di questi robot. Nonostante i recenti miglioramenti, l’opportunità di innovazione di tali sistemi rimane significativa. I robot autonomi hanno ancora funzionalità limitate. Si affidano a fili elettrici installati sottoterra per delimitare i confini del prato, a cui reagiscono senza ragionamento. Tale configurazione è ormai considerata obsoleta e sono disponibili soluzioni autonome più efficaci. Questa tesi si concentra sull’utilizzo delle tecniche attualmente disponibili per progettare i moduli principali necessari per far avanzare le capacità di questi sistemi. Vengono presentate l’analisi e la relativa implementazione delle funzionalità di localizzazione e mappatura per i tosaerba autonomi. Vengono studiati sensori eterogenei e le loro diverse configurazioni e viene proposto un filtro di Kalman adattivo esteso per fondere le loro misurazioni. Questa tecnica migliora la stima della posa del rasaerba autonomo, che viene poi sfruttata dal modulo di mappatura. L’approccio scelto per quest’ultimo, basato sull’inferenza bayesiana, riesce ad aggiornare la conoscenza della mappa basata su interazioni dirette con l’ambiente. I risultati finali evidenziano l’importanza di una localizzazione precisa come vero collo di bottiglia per lo sviluppo di nuove funzionalità. La stima della posa migliorata consente la definizione di un confine virtuale. La definizione non è sufficientemente precisa per mappare correttamente la presenza di oggetti nell’ambiente Esempi di funzionalità avanzate a partire dalla configurazione proposta sono l’implementazione di algoritmi di copertura deterministici e l’interazione con gli oggetti del prato.