Navegação de um robô móvel em ambiente semi-estruturado

Este trabalho aborda a implementação de um sistema de navegação autônoma para um robô móvel a partir das ferramentas propostas pelo ROS. Primeiramente, o modelo do robô estudado foi obtido e adaptado para a tarefa proposta, incluindo a adição de sensores. Em seguida, trabalhou-se com a planta de um prédio existente nas dependências UFRGS para obter um mapa para a navegação. O sistema de navegação proposto no ROS foi estudado e configurado para ser então integrado ao projeto. Foram executadas simulações para avaliar o desempenho do sistema e ajustar os parâmetros necessários para garantir seu funcionamento. Ao final, obteve-se um sistema capaz de planejar e executar trajetórias para que o robô desloque-se de forma autônoma para posições arbitrárias dentro do ambiente utilizado.This project approaches the implementation of an autonomous navigation system for a mobile robot using tools proposed by ROS. Firsty, the model of the robot that was studied in this project was obtained and adapted for the proposed task, including the addition of sensors. Then, the floorplan of one of the building from UFRGS was used to obtain a map for the navigation to be based on. The navigation system proposed by ROS was studied and configured in order to be integrated to the project. Simulations were executed to evaluate the performance of the system and to adjust the parameters needed to ensure its correct operation. In the end, the designed system was capable of planning and executing trajectories allowing the robot to move autonomously to arbitrary positions in its environment

Semantische dreidimensionale Karten für autonome mobile Roboter

Intelligentes autonomes Roboterhandeln in Alltagsumgebungen erfordert den Einsatz von 3D-Karten, in denen Objekte klassifiziert sind. 3D-Karten sind u.a. zur Steuerung notwendig, damit der Roboter komplexen Hindernissen ausweichen und sich mit 6 Freiheitsgraden (x-, y-, z-Position, Nick-, Gier-, und Rollwinkel) lokalisieren kann. Soll der Roboter mit seiner Umgebung interagieren, wird Interpretation unumgänglich. Über erkannte Objekte kann der Roboter Schlussfolgerungen ziehen, sein Wissen wird inspizier- und kommunizierbar. Aus diesen Gründen ist die automatische und schnelle semantische 3D-Modellierung der Umgebung eine wichtige Fragestellung in der Robotik. 3D-Laserscanner sind eine junge Technologie, die die Erfassung räumlicher Daten revolutioniert und Robotern das dreidimensionale Abtasten von Objekten möglich macht. Die vorliegende Arbeit untersucht und evaluiert mit Hilfe eines 3D-Laserscanners und des mobilen Roboters Kurt3D die zur automatischen semantischen 3D-Kartenerstellung notwendigen Algorithmen. Der erste Teil der Arbeit beschäftigt sich mit der Aufgabe, 3D-Scans in einem globalen Koordinatensystem zu registrieren. Korrekte, global konsistente Modelle entstehen durch einen 6D-SLAM Algorithmus. Hierbei werden 6 Freiheitsgrade in der Roboterpose berücksichtigt, geschlossene Kreise erkannt und der globale Fehler minimiert. Die Basis des 6D-SLAM ist ein sehr schneller ICP-Algorithmus. Im zweiten Teil geht es darum, die Punktmodelle mit Semantik zu versehen. Dazu werden 3D-Flächen in einer digitalisierten 3D-Szene detektiert und interpretiert. Anschließend sucht ein effizienter Algorithmus nach Objekten und bestimmt deren Pose, ebenfalls mit 6 Freiheitsgraden. Schließlich wird der in den zahlreichen Experimenten verwendete, mobile Roboter Kurt3D vorgestellt.Semantic three dimensional maps for autonomous mobile robots Intelligent autonomous acting in unstructured environments requires 3D maps with labelled 3D objects. 3D maps are necessary to avoid collisions with complex obstacles and to self localize in six degrees of freedom (x-, y-, z-position, roll, yaw and pitch angle). Meaning becomes inevitable, if the robot has to interact with its environment. The robot is then able to reason about the objects; its knowledge becomes inspectable and communicable. These arguments lead to requiring automatic and fast semantic environment modelling in robotics. A revolutionary method for gaging environments are 3D scanners, which enable robots to scan objects in a non-contact way in three dimensions. The presented work examines and evaluates the algorithms needed for automatic semantic 3D map building using a 3D laser range finder and the mobile robot Kurt3D. The first part deals with the task to register 3D scans in a common coordinate system. Correct, globally consistent models result from a 6D SLAM algorithm. Hereby 6 degrees of freedom of the robot pose are considered, closed-loops are detected and the global error is minimized. 6D SLAM is based on a very fast ICP algorithm. In the second part semantic descriptions are derived from the point model. For that purpose 3D planes are detected and interpreted in the digitalized 3D scene. After that an efficient algorithm detects objects and estimates their pose with 6 degrees of freedom, too. Finally, the mobile robot Kurt3D, that was used in numerous experiments is presented

Biomimetic Navigation Models and Strategies in Animats

This paper describes a hierarchy of four navigation strategies --- guidance, place recognition-triggered response, topological navigation and metric navigation. Such a hierarchy can be used to categorize models that are inspired by current knowledge about the way animals navigate in their environments. The main mechanisms implemented in each model are described, together with the basic adaptive capacities that the corresponding strategy affords. Because biomimetic models have seldom been implemented in real robots, it is premature to compare their merits with those of traditional engineering solutions to the navigation problem. Nevertheless, the methodological options that such implementations would entail are discussed in the text