Interactive imitation learning of object movement skills

Autonomous Robots

Volumn 32, Issue 2, 2012, Pages 97-114

  Mühlig, Manuel ^a   Gienger, Michael ^a   Steil, Jochen J ^b  

^a HONDA RESEARCH INSTITUTE EUROPE GMBH   (Germany)

^b BIELEFELD UNIVERSITY   (Germany)

Author keywords

Human robot interaction; Imitation learning; Kinematics; Robot control

Indexed keywords

BODY PARTS; BODY SCHEMA; GENERALIZATION CAPABILITY; HUMANOID ROBOT; IMITATION LEARNING; MOTOR SKILLS; NOVEL CONCEPT; OBJECT MOVEMENTS; ONE-HANDED; OPTIMIZATION SCHEME; REAL OBJECTS; ROBOT CONTROLS; SELF-COLLISION AVOIDANCE; TASK SPACE;

ANTHROPOMORPHIC ROBOTS; KINEMATICS; TEACHING;

HUMAN ROBOT INTERACTION;

EID: 84862134145     PISSN: 09295593     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10514-011-9261-0     Document Type: Article

References (54)

1. Acosta-Calderon, C. A., & Hu, H. (2005). Robot imitation: body schema and body percept. Applied Bionics and Biomechanics, 2, 131-148.
2. Asfour, T., Gyarfas, F., Azad, P., & Dillmann, R. (2006). Imitation learning of dual-arm manipulation tasks in humanoid robots. In International conference on humanoid robots, 2006 6th IEEE-RAS (pp. 40-47).
3. Azad, P., Asfour, T., & Dillmann, R. (2007). Toward an unified representation for imitation of human motion on humanoids. In Proceedings 2007 IEEE international conference on robotics and automation, IEEE, April (pp. 2558-2563). (Pubitemid 350140562)
4. Beetz, M., Jain, D., Mösenlechner, L., & Tenorth, M. (2010). Towards performing everyday manipulation activities. Robotics and Autonomous Systems, 58(9), 1085-1095.
5. Bohg, J., Barck-Holst, C., Huebner, K., Ralph, M., Rasolzadeh, B., Song, D., & Kragic, D. (2009). Towards grasp-oriented visual perception for humanoid robots. International Journal of Humanoid Robotics, 6(3), 387-434.
6. Bolder, B., Dunn, M., Gienger, M., Janssen, H., Sugiura, H., & Goer-ick, C. (2007). Visually guided whole body interaction. In IEEE international conference on robotics and automation (ICRA) (pp. 3054-3061). (Pubitemid 350140648)
7. Bundesen, C. (1990). A theory of visual attention. Psychological Review, 97(4), 523-547.
8. Burghart, C., Mikut, R., Stiefelhagen, R., Asfour, T., Holzapfel, H., Steinhaus, P., & Dillmann, R. (2005). A cognitive architecture for a humanoid robot: a first approach. In Proceedings of 2005 5th IEEE-RAS international conference on humanoid robots (pp. 357-362). (Pubitemid 46170840)
9. Calinon, S. (2009). Robot programming by demonstration: a probabilistic approach. Lausanne: EPFL Press.
10. Calinon, S., & Billard, A. (2008). A framework integrating statistical and social cues to teach a humanoid robot new skills. In Proc. IEEE intl conf. on robotics and automation (ICRA), workshop on social interaction with intelligent indoor robots.
11. Calinon, S., Guenter, F., & Billard, A. G. (2007). On learning, representing, and generalizing a task in a humanoid robot. IEEE Transactions on Systems, Man and Cybernetics. Part B. Cybernetics: A Publication of the IEEE Systems, Man, and Cybernetics Society, 37(2), 286-298. (Pubitemid 46523219)
12. Einecke, N., Mühlig, M., Schmüdderich, J., & Gienger, M. (2011). "Bring it to me"-Generation of behavior-relevant scene elements for interactive robot scenarios. In 2011 IEEE international conference on robotics and automation (ICRA).
13. Eppner, C., Sturm, J., Bennewitz, M., Stachniss, C., & Burgard, W. (2009). Imitation learning with generalized task descriptions. In Proceedings of the IEEE/RSJ international conference on robotics and automation (ICRA), Kobe, Japan.
14. Gienger, M., Janssen, H., & Goerick, C. (2005). Task-oriented whole body motion for humanoid robots. In 2005 5th IEEE-RAS international conference on humanoid robots (pp. 238-244). (Pubitemid 46170821)
15. Gienger, M., Mühlig, M., & Steil, J. J. (2010a). Imitating object movement skills with robots-a task-level approach exploiting generalization and invariance. In 2010 IEEE/RSJ international conference on intelligent robots and systems (IROS 2010).
16. Gienger, M., Toussaint, M., & Christian, G. (2010b). Motion planning for humanoid robots. In K. Harada, E. Yoshida, & K. Yokoi (Eds.), Whole-body motion planning-building blocks for intelligent systems. Berlin: Springer. Chap. 3.
17. Hecht, F., Azad, P., & Dillmann, R. (2009). Markerless human motion tracking with a flexible model and appearance learning. In IEEE international conference on robotics and automation (ICRA).
18. Heracles, M., Bolder, B., & Goerick, C. (2009). Fast detection of arbitrary planar surfaces from unreliable 3D data. In International conference on intelligent robots and systems (IROS), IEEE/RSJ.
19. Hersch, M., Sauser, E., & Billard, A. (2008). Online learning of the body schema. International Journal of Humanoid Robotics, 5(2), 161-181.
20. Igel, C., & Hüsken, M. (2003). Empirical evaluation of the improved Rprop learning algorithm. Neurocomputing, 50(C), 105-123. (Pubitemid 36131033)
21. Ijspeert, A., Nakanishi, J., & Schaal, S. (2003). Learning attractor landscapes for learning motor primitives. In Advances in neural information processing systems (pp. 1547-1554).
22. Inamura, T., Toshima, I., Tanie, H., & Nakamura, Y. (2004). Embodied symbol emergence based on mimesis theory. The International Journal of Robotics Research, 23, 363-377.
23. Itti, L., Koch, C., & Niebur, E. (1998). A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(11), 1254-1259. (Pubitemid 128742001)
24. Khansari-Zadeh, S., & Billard, A. G. (2010). Imitation learning of globally stable non-linear point-to-point robot motions using nonlinear programming. In Proceeding of the 2010 IEEE/RSJ international conference on intelligent robots and systems (IROS) (pp. 2676-2683).
25. Kober, J., & Peters, J. (2009). Learning motor primitives for robotics. In 2009 IEEE international conference on robotics and automation, IEEE (pp. 2112-2118).
26. Kormushev, P., Calinon, S., & Caldwell, D. G. (2010). Robot motor skill coordination with EM-based reinforcement learning. In 2010 IEEE/RSJ international conference on intelligent robots and systems (pp. 3232-3237).
27. Liégeois, A. (1977). Automatic supervisory control of configuration and behavior of multibody mechanisms. IEEE Transactions on Systems, Man, and Cybernetics, 7(12), 861-871.
28. Lopes, M., & Santos-Victor, J. (2005). Visual learning by imitation with motor representations. IEEE Transactions on Systems, Man, and Cybernetics. Part B, 35(3), 438-449. (Pubitemid 40794856)
29. Lopes, M., Melo, F. S., & Montesano, L. (2007). Affordance-based imitation learning in robots. In Proceedings of the 2007 IEEE/RSJ international conference on intelligent robots and systems.
30. Matarić, M. J., & Pomplun, M. (1998). Fixation behavior in observation and imitation of human movement. Cognitive Brain Research, 7, 191-202. (Pubitemid 28475231)
31. McGuire, P., Fritsch, J., Steil, J. J., Röthling, F., Fink, G. A., Wachsmuth, S., Sagerer, G., & Ritter, H. (2002). Multi-modal human-machine communication for instructing robot grasping tasks. In Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS) (pp. 1082-1088). (Pubitemid 35437953)
32. Mühlig, M., Gienger, M., Hellbach, S., Steil, J. J., & Goer-ick, C. (2009a). Task-level imitation learning using variance-based movement optimization. In IEEE international conference on robotics and automation (ICRA).
33. Mühlig, M., Gienger, M., Steil, J. J., & Goerick, C. (2009b). Automatic selection of task spaces for imitation learning. In 2009 IEEE/RSJ international conference on intelligent robots and systems.
34. Mühlig, M., Gienger, M., & Steil, J. J. (2010). Human-robot interaction for learning and adaptation of object movements. In 2010 IEEE/RSJ international conference on intelligent robots and systems (IROS 2010).
35. Nabeshima, C., Kuniyoshi, Y., & Lungarella, M. (2006). Adaptive body schema for robotic tool-use. Advanced Robotics, 20(10), 1105-1126. (Pubitemid 44671138)
36. Nagai, Y., Muhl, C., & Rohlfing, K. J. (2008). Toward designing a robot that learns actions from parental demonstrations. In 2008 IEEE international conference on robotics and automation, Pasadena, CA, USA (pp. 3545-3550).
37. Nakamura, Y. (1991). Advanced robotics: redundancy and optimization. Reading: Addison-Wesley.
38. Nicolescu, M., & Matarić, M. J. (2003). Natural methods for robot task learning: instructive demonstrations, generalization and practice. In Proceedings of the second international joint conference on autonomous agents and multi-agent systems (pp. 241-248). New York: ACM.
39. Nicolescu, M., & Matarić, M. J. (2006). Task learning through imitation and human-robot interaction. In Models and mechanisms of imitation and social learning in robots, humans and animals: behavioural, social and communicative dimensions (pp. 407-424).
40. Orabona, F., Metta, G., & Sandini, G. (2007). A proto-object based visual attention model. In Attention in cognitive systems theories and systems from an interdisciplinary viewpoint (pp. 198-215). (Pubitemid 351153883)
41. Pastor, P., Hoffmann, H., Asfour, T., & Schaal, S. (2009). Learning and generalization of motor skills by learning from demonstration. In IEEE international conference on robotics and automation.
42. Sakoe, H. (1978). Dynamic programming algorithm optimization for spoken word recognition. IEEE Transactions on Acoustics, Speech, and Signal Processing, 26, 43-49. (Pubitemid 8601900)
43. Schaal, S., Ijspeert, A., & Billard, A. G. (2003). Computational approaches to motor learning by imitation. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 358(1431), 537-547. (Pubitemid 36380533)
44. Schmuedderich, J. (2010). Multimodal learning of grounded concepts in embodied systems. Berichte aus der Robotik. Aachen: Shaker.
45. Scholl, B. J. (2001). Objects and attention: the state of the art. Cognition, 80(1-2), 1-46. (Pubitemid 32178138)
46. Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6(2), 461-464.
47. Steil, J. J., Roethling, F., Haschke, R., & Ritter, H. (2004). Situated robot learning for multi-modal instruction and imitation of grasping. Robotics and Autonomous Systems Special Issue, 47, 129-141.
48. Stoytchev, A. (2003). Computational model for an extendable robot body schema. Tech. Rep. GIT-CC-03-44, Georgia Institute of Technology, College of Computing.
49. Sugiura, K., Iwahashi, N., Kashioka, H., & Nakamura, S. (2010). Statistical imitation learning in sequential object manipulation tasks. In Advances in robot manipulators (pp. 589-606).
50. Toussaint, M., Gienger, M., & Goerick, C. (2007). Optimization of sequential attractor-based movement for compact behaviour generation. In 7th IEEE-RAS international conference on humanoid robots (Humanoids 2007).
51. Toussaint, M., Plath, N., Lang, T., & Jetchev, N. (2010). Integrated motor control, planning, grasping and high-level reasoning in a blocks world using probabilistic inference. In Robotics and automation (ICRA), 2010 IEEE international conference on, IEEE (pp. 385-391).
52. Walther, D., & Koch, C. (2006). Modeling attention to salient proto-objects. Neural Networks, 19(9), 1395-1407. (Pubitemid 44708603)
53. Wischnewski, M., Belardinelli, A., Schneider, W. X., & Steil, J. J. (2010). Where to look next? Combining static and dynamic proto-objects in a TVA-based model of visual attention. In Cognitive computation (pp. 1-18).
54. Yamashita, Y., & Tani, J. (2008). Emergence of functional hierarchy in a multiple timescale neural network model: a humanoid robot experiment. PLoS computational biology, 4(11).