Online intention learning for human-robot interaction by scene observation

Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO

Volumn , Issue , 2012, Pages 13-18

  Awais, Muhammad ^a   Henrich, Dominik ^a  

^a UNIVERSITY OF BAYREUTH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ACTION SEQUENCES; HUMAN ACTIONS; HUMAN INTENTIONS; INTENTION RECOGNITION; SEQUENCE OF ACTIONS;

ECONOMIC AND SOCIAL EFFECTS; MAPPING; ROBOTICS;

HUMAN ROBOT INTERACTION;

EID: 84863641239     PISSN: 21627568     EISSN: 21627576     Source Type: Conference Proceeding    
DOI: 10.1109/ARSO.2012.6213391     Document Type: Conference Paper

References (20)

1. A. Billard and A. Hayes, G., DARMA 1999. a connectionist architecture for control and learning. autonomous robots, Adaptive. Behavior. 7 (1), 35-64.
2. A. Fathi and G. Mori, Action recognition by learning mid-level motion features, in Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR'08), Anchorage, AK, June 2008, pp. 1-8.
3. B. Argall and S. Schall, 1997. Robot learning from demonstration. In Proceedings of 14th International Conference on Machine Learning (ICML).
4. C. Lee and Y. Xu, 1996. Online, Interactive Learning of Gestures for Human/Robot Interface. In IEEE Proc. International Conference on Robotics and Automation (ICRA) 2982-2987, vol.4.
5. C. Thurau and V. Hlaváč, Pose primitive based human action recognition in videos or still images, in Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR'08), Anchorage, AK, June 2008, pp. 1-6.
6. F. Lv, R. Nevatia, Single view human action recognition using key pose matching and Viterbi path searching, in: Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR'07), Minneapolis, MN,June 2007, pp. 1-8
7. H. Jeon, T. Kim, and J. Choi. Ontology-based user intention recognition for proactive planning of intelligent robot behaviour. International Conference on Multimedia and Ubiquitous Engineering, 2008.
8. J. Yang and Y. Xu, 1993. Hidden Markov model approach to skill learning and its application in telerobotics. In IEEE Proc International Conference on Robotics and Automation (ICRA), 396-402.
9. K. Mikolajczyk and H. Uemura, Action recognition with motion appearance vocabulary forest, in Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR'08), Anchorage, AK, June 2008, pp. 1-8
10. K. A. Tahb. Intention recognition of a human commanding a mobile robot. Proceedings of the IEEE, Conference on Cybernetics and Intelligent Systems, Singapore, pages 896:1-6, 1-3 December, 2004.
11. L, Wang and D. Sutter, Learning and matching of dynamic shape manifolds for human action recognition. IEEE Transactions On Image Processing (TIP) 16 (6) (2007) 1646-1661.
12. M. Awais and D. Henrich, 2010. Human-Robot Collaboration using Probabilistic State Machines. In Proceedings of 19th International Workshop on Robotics in Alpe-Adria-Danube Region (RAAD).
13. O. Weede, C. Schrempf, and U. D. Hanebeck. A Generic Model for Estimating User-Intentions in Human-Robot Cooperation, in Proceedings of the 2nd International Conference on Informatics in Control, Automation and Robotics, ICINCO 05, 2005.
14. R. Sutton and A. Barto, 1998. Reinforcement learning: An introduction, The MIT Press, Cambridge, MA, London, England.
15. R. Poppe. A survey on vision-based human action recognition. Image and Vision Computing, 28(6) : 976-990, June 2010.
16. Richard et al. Understanding Human intentions via Hidden Markov Model in Autonomous Mobile Robots, Proceedings of ACM/IEEE international conference on Human-robot interactions, pages 367-374.
17. S. Youn, and K. Oh. Intention Recognition using a Graph Representation. World Academy of Science, Engineering and Technology, 25, 2007.
18. W. Mao, and J. Gratch. A utility-based approach to intention recognition. Workshop on Agent Tracking: Modeling Other Agents from Observation, 2004
19. W. Smart and L. Kaelbling, 2002. Effective reinforcement learning for mobile robots. In IEEE Proc. International Conference on Robotics and Automation (ICRA), 3404-3410, vol.4.
20. Y. Ke, R. Sukthankar, and M. Hebert, Spatio-temporal shape and flow correlation for action recognition, in Proc. Visual Surveillance Workshop, 2007, pp. 1-8