On the laboratory carpet:
On a foam mat:
On a desk:
On a wet desk with slippery surface:
On a linoleum surface:
The Crawling Robot Software (OpenSource GPL)
- Microcontroller Code (download)
- The Teaching-Box at SourceForge (website)
- 3D-Simulation as VMWare Virtual Machine (download)
Obtaining the Crawling Robot
If you are interessted in buying the crawling robot, please contact either Prof. Dr. Wolfgang Ertel or Michel Tokic or Joachim Fessler.
Relevant Literature
- M. Tokic and H. Bou Ammar.
Teaching reinforcement learning using a physical robot.
In Proceedings of the Workshop on Teaching Machine Learning at
the 29th International Conference on Machine Learning, Edinburgh, UK,
2012.
(to appear). - W. Ertel. Introduction to Artificial Intelligence. Springer London, 2011.
- S. Montresor, J. Kay, M. Tokic, and J. Summerton.
Work in progress: Programming in a confined space – a case study in
porting modern robot software to an antique platform.
In Proceedings of the 41st ASEE/IEEE Frontiers in Education
Conference, pages T3H-1-T3H-3, Rapid City, SD, USA, 2011. IEEE
Press. - M. Tokic, A. Usadel, J. Fessler, and W. Ertel.
On an educational approach to behavior learning for robots.
In Proceedings of the 1st International Conference on Robotics
in Education, pages 171-176, Bratislava, Slovak Republic, 2010. Slovak
University of Technology in Bratislava. - M. Tokic, J. Fessler, and W. Ertel.
The crawler, a class room demonstrator for reinforcement learning.
In C. Lane and H. Guesgen, editors, Proceedings of the 22th
International Florida Artificial Intelligence Research Society Conference
FLAIRS’09, pages 160-165, Menlo Park, California, USA, 2009. AAAI
Press. - W. Ertel, M. Schneider, R. Cubek, and M. Tokic.
The Teaching-Box: a universal robot learning framework.
In Proceedings of the 14th International Conference on Advanced
Robotics ICAR’09., pages 1-6, 2009. - H. Kimura, K. Miyazaki, and S. Kobayashi.
Reinforcement learning in POMDPs with function approximation.
In Proceedings of the 14th International Conference on Machine
Learning (ICML’97), pages 152-160, San Francisco, CA, USA, 1997.
Morgan Kaufmann Publishers Inc.