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The main objective of our ROS Summer School series is to introduce MA level students to program mobile robots with the Robot Operating System (ROS). ROS is a robot middleware that is used my many research institutions world-wide. Therefore, many state-of-the-art algorithms of mobile robotics are available in ROS and can be deployed very easily. As a basic robot platform we deploy a 1/10 RC cart that is wquipped with an Arduino micro-controller to control the servo motors, and an embedded PC that runs ROS. In two weeks, participants get to learn the basics of mobile robotics hands-on. We describe our teaching concepts and our curriculum and report on the learning success of our students.
The maintenance of wind turbines is of growing importance considering the transition to renewable energy. This paper presents a multi-robot-approach for automated wind turbine maintenance including a novel climbing robot. Currently, wind turbine maintenance remains a manual task, which is monotonous, dangerous, and also physically demanding due to the large scale of wind turbines. Technical climbers are required to work at significant heights, even in bad weather conditions. Furthermore, a skilled labor force with sufficient knowledge in repairing fiber composite material is rare. Autonomous mobile systems enable the digitization of the maintenance process. They can be designed for weather-independent operations. This work contributes to the development and experimental validation of a maintenance system consisting of multiple robotic platforms for a variety of tasks, such as wind turbine tower and rotor blade service. In this work, multicopters with vision and LiDAR sensors for global inspection are used to guide slower climbing robots. Light-weight magnetic climbers with surface contact were used to analyze structure parts with non-destructive inspection methods and to locally repair smaller defects. Localization was enabled by adapting odometry for conical-shaped surfaces considering additional navigation sensors. Magnets were suitable for steel towers to clamp onto the surface. A friction-based climbing ring robot (SMART— Scanning, Monitoring, Analyzing, Repair and Transportation) completed the set-up for higher payload. The maintenance period could be extended by using weather-proofed maintenance robots. The multi-robot-system was running the Robot Operating System (ROS). Additionally, first steps towards machine learning would enable maintenance staff to use pattern classification for fault diagnosis in order to operate safely from the ground in the future.
Pandaboard, TurtleBot, Kinect und Co. : Low-Cost Hardware im Lehreinsatz für die mobile Robotik.
(2012)
Mit freundlicher Genehmigung der Autoren und des Oldenbourg Industrieverlags https://www.oldenbourg-industrieverlag.de/de/9783835633223-33223 erschienen als Beitrag im Tagungsband zur AALE-Tagung 2012. 9. Fachkonferenz 4.-5. Mai 2012, Aachen, Fachhochschule. ISBN 9783835633223 S 8-1 S. 229-238 Original-Abstract des Autors: "Die mobile Robotik wird durch den Einsatz von Low-Cost Hardware einem breiten Publikum zugänglich. Bis vor kurzem basierte eine erschwingliche Hardware meist auf Mikrocontrollern mit den entsprechenden Leistungseinschränkungen z.B. im Bereich der Bildverarbeitung. Die Wahrnehmung einer 3D-Umgebung und somit die Möglichkeit zur autonomen Navigation wurde mit relativ kostenintensiver Hardware, z.B. Stereo-Vision-Systemen und Laserscannern gelöst. Die zur Auswertung der Sensorik notwendige Rechenleistung stand - entweder aufgrund des Stromverbrauchs oder der Performance meist für mobile Plattformen (lokal) - nicht zur Verfügung. Durch Einsatz von leistungsfähigen Prozessoren aus dem Bereich der Mobilgeräte (Smartphones, Tablets) und neuartigen Sensoren des Consumer-Bereichs, wie der Kinect, können mobile Roboter kostengünstig für den Einsatz in der Lehre aufgebaut werden.
Particle-Image-Velocimetry (PIV) in rotierenden Maschinen / Dues, M. ; Kallweit, S. ; Siekmann, H.
(1994)
The production and assembly of customized products increases the demand for flexible automation systems. One approach is to remove the safety fences that separate human and industrial robot to combine their skills. This collaboration possesses a certain risk for the human co-worker, leading to numerous safety concepts to protect him. The human needs to be monitored and tracked by a safety system using different sensors. The proposed system consists of a RGBD camera for surveillance of the common working area, an array of optical distance sensors to compensate shadowing effects of the RGBD camera and a laser range finder to detect the co-worker when approaching the work cell. The software for collision detection, path planning, robot control and predicting the behaviour of the co-worker is based on the Robot Operating System (ROS). A first prototype of the work cell shows that with advanced algorithms from the field of mobile robotics a very flexible safety concept can be realized: the robot not simply stops its movement when detecting a collision, but plans and executes an alternative path around the obstacle.