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Proceedings of the OAGM&ARW Joint Workshop - Vision, Automation and Robotics
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Fig. 2. Overall software architecture with links to the central refbox, the team server and the connectedn robots. of the paper. These skills are provided to the next higher layer, the mid-layer, via defined messages. The mid-layer, therefore, can use these skills to perform more complex tasks such as exploring a zone of the game- field, get a base from the base station or deliver the product holding in its gripper. Additionally, a first error detection and recovery behavior are implemented here, e.g. the system checks if there is a product in the gripper after the low-level hassuccessfullygrabbedsomething.Thesecomplex tasksare again provided via defined protobuf messages to our highest layer, the team server. Here a central knowledge-base is held and a game strategy is derived (see Section IV-B for further details). This central point enables the system to conclude a global optimal game strategy for the complete robotic fleet. The global strategy is derived using a simple planning system which uses a hi- erarchical task network [10] to properly create the products. Due to the centralized knowledge base one does not need to deal with synchronization of knowledge bases of the robot or distributed planning. Instead a “simpler” approach for planning can be applied. Fig. 3. Communication between the different layers for one robot using Google’s protocol buffers. IV. SELECTED SOFTWARE COMPONENTS To get an idea of the functional interaction of our robot system some selected components are presented. First of all, two low-level modules necessary to detect and identify a machine are presented in SectionIV-A. Additionally, the scheduling algorithm (located at the high-level component of our system) which manages the discovery of the unknown game-field is presented in Section IV-B. A. Machine Detection and Identification To be able to gather information about the unknown envi- ronment it is necessary for the robot to recognize elements surrounding it. One important type of these elements is a modular production system, i.e. the machines capable of producing the ordered products. To identify the machines AR-tags are used which are placed at two sides of these machines. 63
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Proceedings of the OAGM&ARW Joint Workshop Vision, Automation and Robotics
Titel
Proceedings of the OAGM&ARW Joint Workshop
Untertitel
Vision, Automation and Robotics
Autoren
Peter M. Roth
Markus Vincze
Wilfried Kubinger
Andreas Müller
Bernhard Blaschitz
Svorad Stolc
Verlag
Verlag der Technischen Universität Graz
Ort
Wien
Datum
2017
Sprache
englisch
Lizenz
CC BY 4.0
ISBN
978-3-85125-524-9
Abmessungen
21.0 x 29.7 cm
Seiten
188
Schlagwörter
Tagungsband
Kategorien
International
Tagungsbände

Inhaltsverzeichnis

  1. Preface v
  2. Workshop Organization vi
  3. Program Committee OAGM vii
  4. Program Committee ARW viii
  5. Awards 2016 ix
  6. Index of Authors x
  7. Keynote Talks
  8. Austrian Robotics Workshop 4
  9. OAGM Workshop 86
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Proceedings of the OAGM&ARW Joint Workshop