publication . Other literature type . Preprint . Article . Conference object . 2019

Generalized Multiple Correlation Coefficient as a Similarity Measurements between Trajectories

Urain, Julen; Peters, Jan;
Open Access
  • Published: 24 Jun 2019
  • Publisher: Zenodo
Abstract
Comment: 7 pages, 4 figures, IROS 2019
Subjects
free text keywords: Robotics, Imitation Learning, Computer Science - Human-Computer Interaction, Computer Science - Robotics
Funded by
EC| SHAREWORK
Project
SHAREWORK
Safe and effective HumAn-Robot coopEration toWards a better cOmpetiveness on cuRrent automation lacK manufacturing processes.
  • Funder: European Commission (EC)
  • Project Code: 820807
  • Funding stream: H2020 | RIA
Validated by funder
Communities
Rural Digital Europe
Download fromView all 5 versions
Zenodo
Other literature type . 2019
Provider: Datacite
Zenodo
Other literature type . 2019
Provider: Datacite
20 references, page 1 of 2

[1] T. Osa, J. Pajarinen, G. Neumann, J. A. Bagnell, P. Abbeel, J. Peters, et al., “An algorithmic perspective on imitation learning,” Foundations and Trends R in Robotics, vol. 7, no. 1-2, pp. 1-179, 2018.

[2] S. Schaal, “Learning from demonstration,” in Advances in neural information processing systems, pp. 1040-1046, 1997.

[3] O. Dermy, A. Paraschos, M. Ewerton, J. Peters, F. Charpillet, and S. Ivaldi, “Prediction of intention during interaction with icub with probabilistic movement primitives,” Frontiers in Robotics and AI, vol. 4, p. 45, 2017.

[4] H. B. Amor, O. Kroemer, U. Hillenbrand, G. Neumann, and J. Peters, “Generalization of human grasping for multi-fingered robot hands,” in 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2043-2050, IEEE, 2012. [OpenAIRE]

[5] M. A. Goodrich, A. C. Schultz, et al., “Human-robot interaction: a survey,” Foundations and Trends R in Human-Computer Interaction, vol. 1, no. 3, pp. 203-275, 2008.

[6] H. B. Amor, D. Vogt, M. Ewerton, E. Berger, B. Jung, and J. Peters, “Learning responsive robot behavior by imitation,” in 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3257- 3264, IEEE, 2013.

[7] G. Maeda, M. Ewerton, R. Lioutikov, H. B. Amor, J. Peters, and G. Neumann, “Learning interaction for collaborative tasks with probabilistic movement primitives,” in 2014 IEEE-RAS International Conference on Humanoid Robots, pp. 527-534, IEEE, 2014. [OpenAIRE]

[8] H. B. Amor, G. Neumann, S. Kamthe, O. Kroemer, and J. Peters, “Interaction primitives for human-robot cooperation tasks,” in 2014 IEEE international conference on robotics and automation (ICRA), pp. 2831-2837, IEEE, 2014. [OpenAIRE]

[9] A. Paraschos, C. Daniel, J. R. Peters, and G. Neumann, “Probabilistic movement primitives,” in Advances in neural information processing systems, pp. 2616-2624, 2013. [OpenAIRE]

[10] S. Gomez-Gonzalez, G. Neumann, B. Scho¨lkopf, and J. Peters, “Adaptation and robust learning of probabilistic movement primitives,” arXiv preprint arXiv:1808.10648, 2018.

[11] X. Wang, M. Xia, H. Cai, Y. Gao, and C. Cattani, “Hidden-markovmodels-based dynamic hand gesture recognition,” Mathematical Problems in Engineering, vol. 2012, 2012.

[12] H. Hotelling, “Relations between two sets of variates,” in Breakthroughs in statistics, pp. 162-190, Springer, 1992.

[13] Y. Escoufier, “Le traitement des variables vectorielles,” Biometrics, pp. 751-760, 1973. [OpenAIRE]

[14] G. J. Sze´kely, M. L. Rizzo, et al., “Brownian distance covariance,” The annals of applied statistics, vol. 3, no. 4, pp. 1236-1265, 2009.

[15] S. Salvador and P. Chan, “Toward accurate dynamic time warping in linear time and space,” Intelligent Data Analysis, vol. 11, no. 5, pp. 561-580, 2007.

20 references, page 1 of 2
Any information missing or wrong?Report an Issue