References
- 1. Gracias, X., S. Negahdaripour. Underwater Mosaic Creation Using Video Sequences from Different Altitudes. - In: OCEANS, 2005. Proceedings of MTS/IEEE, Vol. 2, 17-23 September 2005, 1295-1300.
- 2. Billar, S. Calinon, R. Dillmann, S. Schaal. Survey, Robot Programming by Demonstration. Handbook of Robotic. Chapter 59. 2008.
- 3. Guo, S., X. Lin. Development of a Vectored Water-Jet-Based Spherical Underwater Vehicle. - In: N. A. Cruz, Ed. Autonomous Underwater Vehicles. InTech, Janeza Tardin 9, 51000 Rijeka, Croatia, 2011, 3-20.
- 4. Ryu, J. H. Control of Underwater Manipulators Mounted on an ROV Using Base Force Information. - In: IEEE Int. Conf. on Robotics and Automation (ICRA), Vol. 4, 2001, 3238-3243.
- 5. Prats, M., D. Ribas, N. Palomeras, J. C. Gacía, V. Nannen, S. Wirth, J. J. Frenández, J. P. Beltráns, R. Campos, P. Ridao. Reconfigurable AUV for Intervention Missions: A Case Study on Underwater Object Recovery. - Intelligent Service Robotics, Vol. 5, 2012, 19-31.
- 6. Persistent Autonomy through learNing, aDaptation, Observation and Re-plAnning (PANDORA). http://persistentautonomy.com/
- 7. Ijspeert, A. J., J. Nakanishi, S. Schaal. Trajectory Formation for Imitation with Nonlinear Dynamical Systems - In: Proc. IEEE Intl. Conf. on Intelligent Robots and Systems (IROS), Maui, USA, 2001, 752-757.
- 8. An, C. H., C. G. Atkeson, J. M. Hollerback. Model-Based Control of a Robot Manipulator. MIT Press, 1988.
- 9. Miyamoto, H., S. Schaal, F. Gandolfo, Y. Koike, R. Osu, E. Nakano, Y. Wada, M. Kawato. A Kendama Learning Robot Based on Bi-Directional Theory. - Neural Networks, Vol. 9, 1996, 1281-1302.
- 10. Kawato, M. Trajectory Formation in Arm Movements: Minimization Principles and Procedures. - In: H. Z. Zelaznik, Ed. Advanced in Motor Learning and Control. Champaign Illinois, Human Kinetics Publisher, 1996, 225-259.
- 11. Sutton, R., A. G. Barto. Reinforcement Learning: An Introduction. MIT Press, 1998.
- 12. Welch, G., G. Bishop. An Introduction to the Kalman Filter. ACM SIGGRAPH 2001, Course 8. http://ww.cs.unc.edu/~welch/kalman/
- 13. Ribas, D., N. Palomeras, P. Ridao, M. Carreras, A. Mallios. Girona 500 AUV, from Survey to Intervention - IEEE/ASME Transactions on Mechatronics, Vol. 17, 2012, 46-57.
- 14. Albu-Schäffer, A., C. Ott, G. Hirzinger. A Unified Passivity-Based Control Framework for Position, Torque and Impedance Control of Flexible Joint Robots. - Int. Journal of Robotics Research, Vol. 26, 2007, No 1, 23-39.
- 15. Schreiber, G., A. Stemmer, R. Bischoff. The Fast Research Interface for the KUKA Lightweight Robot. - In: IEEE ICRA, 2010.
- 16. Funk, N. A Study of the Kalman Filter Applied to Visual Tracking. Technical Report. University of Alberta, 2003.
- 17. Zhou, Q., J. K. Aggarwal. Object Tracking in an Outdoor Environment Using Fusion of Features and Cameras. - Image and Vision Computing, Vol. 24, 2006, 1244-1255.
- 18. Schaal, S., P. Mohajerian, A. J. Ijspeert. Dynamics Systems Vs. Optimal Control a Unifying View. - Progress in Brain Research, Vol. 165, 2007, 425-445.
- 19. Hoffmann, H., P. Pastor, D. H. Park, S. Schaal. Biologically-Inspired Dynamical Systems for Movement Generation: Automatic Real-Time Goal Adaptation and Obstacle Avoidance. - In: Proc. IEEE Intl. Conf. on Robotics and Automation (ICRA), Kobe, Japan, May 2009, 2587-2592.
- 20. Kormushev, P., S. Calinon, D. G. Caldwell. Imitation Learning of Positional and Force Skills Demonstrated via Kinesthetic Teaching and Haptic Input. - Advanced Robotics, Vol. 25, 2011, No 5, 581-603.
- 21. Wang, L. X. A Course in Fuzzy System and Control. 2nd Edition. Prentice-Hall International, Inc., 1997. ISBN: 0135408822.