Developing a PBL-based Rescue Robotics Course

  • Frank Hees
  • Sabina Jeschke
  • Nicole Natho
  • Olivier Pfeiffer
Conference paper


Problem-based learning (PBL) denotes self-determined learning and learning through discovery, activity-based education, interdisciplinary education, and self-assessment. The participants in problem based learning courses learn to analyze a subject or a problem with minimal guidance by their teacher or rather their facilitator of learning. Students find and use the suitable sources of information by themselves, and finally, compare, select and convert the results. The essential highlight of the PBL approach is the examination of authentic (real life) and complex subjects. The origin of the PBL lies in application-based technical engineering subjects and later in medical education.

Robotics education is perfectly suited for the application of PBL-scenarios as robotics combines a multitude of technological disciplines (ranging from computer sciences, software engineering, artificial intelligence, electrical engineering up to technology design) and its ubiquitous popularity with a variety soft skills (team skills, complex problem-solving strategies, etc.), required in the development process. The popularity of robots can be easily deduced from the large number of robotic heroes in literature and movies. Thus, robotics is ideally suited as a model project-oriented course of combining communication skills, development of strategies to solve complex interdisciplinary challenges, and different concepts of softand hardware engineering.

Among the wide range of robotics applications, one field of particular importance is the field of “Rescue Robots”. Here, robots are developed that operate in catastrophe-scenarios, e.g. earthquakes or fires. Based on the data obtained from their various sensors (video cameras, infrared sensors, laser scanner and gas sensors), these robots have to manage their tasks autonomously in catastrophe-based scenarios. This comprises detection, rescue, and aid for victims should the situation arise. In order to fulfill these complex tasks, development of basic skills such as exact movements on unstable bedrock, field mapping, positioning and communication in weakly structured environments is necessary. Besides the construction of preferably all-terrain and robust robots, the improvement of innovative analysis procedures for complex sensor data is another focus of development. In addition, conception and realization of novel man-machine-interfaces come to the fore in order to support the operators of robots with their exhausting control tasks.

Integrated in the “RoboCup”, the “Rescue-Robot League” clarifies the intensified orientation of the “RoboCup initiative” on real life applications. Another hint that rescue robotics represents a ideal playground for PBL scenarios in academic education.

Beyond that, robotics is increasing the number of female students in the natural sciences and engineering. It has the potential of attracting girls and young females at their respective levels education by illustrating their own potential in a playful experimental setting. Independent design and construction of robots demonstrates the importance of creativity and social relevance, giving young women more confidence in their technical and scientific skills, facts affecting young women’s choice of degree.


PBL Robotics Academic Education 


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  1. [Bar96]
    H.S. Barrows. Problem-based learning in medicine and beyond: a brief overview. In Luann Wilkerson and Wim H. Gijselaers, editors, Bringing Problem-Based Learning to Higher Education: Theory and Practice: New Directions for Teaching and Learning. Jossey-Bass, San Francisco, 1996.Google Scholar
  2. [Bar00]
    H.S. Barrows. Problem-based learning applied to medical education. UniversitySchool of Medicine, Springfield, Southern Illinois, 2000. Rev. 1994 Ed.Google Scholar
  3. [BD06]
    T Bailey and H Durrant-Whyte. Simultaneous localization and mapping (SLAM):part II. IEEE Robotics & Automation Magazine, 13(3):117, 108, 2006.Google Scholar
  4. [BDM95]
    J.A. Barbera, C. DeAtley, and A.G. Macintyre. Medical aspects of urban search andrescue. Fire Engineering, 148:88–92, November 1995.Google Scholar
  5. [BF98]
    David Boud, Grahame Feletti, and Feletti Boud. The Challenge of Problem Based Learning. Routledge, 2nd edition, 1998.Google Scholar
  6. [BT80]
    Howard S. Barrows and Robyn M. Tamblyn. Problem-Based Learning: An Approach to Medical Education. Springer Publishing Company, 1980.Google Scholar
  7. [Dav02]
    A. Davids. Urban search and rescue robots: from tragedy to technology. Intelligent Systems, IEEE, 17(2):81–83, 2002.Google Scholar
  8. [DB06]
    H. Durrant-Whyte and T. Bailey. Simultaneous localization and mapping: part I. IEEE Robotics & Automation Magazine, 13(2):99–110, 2006.CrossRefGoogle Scholar
  9. [Dew16]
    John Dewey. Democracy And Education. Free Press, Original from The Macmillan Company, 1916.Google Scholar
  10. [dWSB96]
    Carlos Canudas de Wit, Bruno Siciliano, and Georges Bastin. Theory of Robot Control. Springer, London, 1996.MATHGoogle Scholar
  11. [fAiSAP06]
    St. Augustin Fraunhofer-Institut für Autonome intelligente Systeme AIS andGabriele Theidig Josef Börding Ulrike Petersen. Roberta - Anleitung zur Schulung von Kursleiterinnen und Kursleitern, volume 5. IRB Verlag, 2006.Google Scholar
  12. [GHL06]
    H.H. Gonzalez-Banos, D. Hsu, and J.C. Latombe. Motion Planning: Recent Developments.In Shuzhi Sam Ge and F.L. Lewis, editors, Autonomous Mobile Robots: Sensing, Control, Decision Making and Applications. CRC Press, Bota Racon, 2006.Google Scholar
  13. [HBDH94]
    G. Hirzinger, B. Brunner, J. Dietrich, and J. Heindl. ROTEX-the first remotely controlledrobot in space. In Robotics and Automation, 1994. Proceedings., 1994 IEEE International Conference on, pages 2604–2611, San Diego, 1994. 3.Google Scholar
  14. [JKN+09]
    Sabina Jeschke, Lars Knipping, Nicole Natho, Ursula Vollmer, and Marc Wilke. The“Robinson” Programme: Interdisciplinary Education based on Robotics Curricula. InXiangyun Du, Erik de Graaff, and Anette Kolmos, editors, Research on PBL Practice in Engineering Education, pages 185–198. Sense Publishers, P.O. Box 21858, 3001AWRotterdam, The Netherlands, May 2009. ISBN 978-90-8790-930-7 (paperback),ISBN 978-90-8790-931-4 (hardback), ISBN 978-90-8790-932-1 (e-book).Google Scholar
  15. [KZ93]
    Ronald Kube and Hong Zhang. Collective Robotics: From Social Insects to Robots. Adaptive Behavior, 2(2):189–218, 1993.CrossRefGoogle Scholar
  16. [Mer02]
    M. David Merrill. A pebble-in-the-pond model for instructional design. Performance Improvement, 41(7):41–46, 2002.CrossRefGoogle Scholar
  17. [Mer07]
    M. DavidMerrill. A task centered instructional strategy. Journal of Research on Technology in Education, 40(1):33–50, 2007.Google Scholar
  18. [MS93]
    M.J. Massimo and T.B. Sheridan. Sensory substitution for force feedback in teleoperation. Presence: Teleoperators and Virtual Environments, 2(4):344–352, 1993.Google Scholar
  19. [MSPG06]
    R. Murphy, S. Stover, K. Pratt, and C. Griffin. Cooperative Damage Inspection withUnmanned Surface Vehicle and Micro Unmanned Aerial Vehicle at HurricaneWilma.In Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on, page 9, Beijing, 2006. IEEE Press.CrossRefGoogle Scholar
  20. [MTN+08]
    R.R. Murphy, S. Tadokoro, D. Nardi, A. Jacoff, P. Fiorini, H. Choset, and A.M. Erkmen. Search and rescue robotics. In Springer handbook of robotics. Springer Berlin /Heidelberg, 2008.Google Scholar
  21. [Mur00]
    R.R. Murphy. Marsupial robots for urban search and rescue. IEEE Intell. Systems, 15(2):14–19, 2000.CrossRefGoogle Scholar
  22. [Mur04]
    R.R. Murphy. Trial by fire [rescue robots]. Robotics & Automation Magazine, IEEE, 11(3):50–61, 2004.CrossRefGoogle Scholar
  23. [oCC07]
    Intergovernmental Panel on Climate Change. 4th Assessment Report. Technical report,2007.Google Scholar
  24. [Sim06]
    Dan Simon. Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches. Wiley-Interscience, New York, 2006.Google Scholar
  25. [SS96]
    Lorenzo Sciavicco and Bruno Siciliano. Modelling and Control of Robot Manipulators. McGraw-Hill, New York, 1996.Google Scholar
  26. [vA06]
    Maarten K. van Aalst. The impacts of climate change on the risk of natural disasters. Disasters, 30(1):5–18, 2006.CrossRefGoogle Scholar
  27. [vMBH04]
    J.J.G. van Merriënboer, Th. Bastiaens, and B. Hoogveld. Instructional design forintegrated e-learning. In Wim Jochems, Rob Koper, and Jeroen Van Merrienboer,editors, Integrated E-Learning: Implications for Pedagogy, Technology and Organization, page 15. Kogan Page, London, UK, 2004.Google Scholar
  28. [Web04]
    Agnes Weber. Problem-Based Learning: Ein Handbuch für die Ausbildung auf der Sekundarstufe II und auf der Tertiärstufe. hep verlag, 2004.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Frank Hees
    • 1
  • Sabina Jeschke
    • 2
  • Nicole Natho
    • 3
  • Olivier Pfeiffer
    • 3
  1. 1.ZLW/IMA & IfU, RWTH Aachen UniversityAachenGermany
  2. 2.IMA/ZLW & IfU - RWTH Aachen UniversityAachenGermany
  3. 3.MuLF, Berlin University of TechnologyBerlinGermany

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