L. Rozo, P. Jiménez, and T. Carme, A robot learning from demonstration framework to perform force-based manipulation tasks, Intelligent Service Robotics, vol.21, issue.9, pp.33-51, 2013.
DOI : 10.1007/s11370-012-0128-9

J. Englsberger, P. Kozlowski, and C. Ott, Biologically inspired deadbeat controller for bipedal running in 3d, IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.989-996, 2015.

S. Ha, Y. Bai, and C. K. Liu, Human motion reconstruction from force sensors, Proceedings of the 2011 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, SCA '11, pp.129-138, 2011.
DOI : 10.1145/2019406.2019424

P. Zhang, K. Siu, J. Zhang, C. K. Liu, and J. Chai, Leveraging depth cameras and wearable pressure sensors for full-body kinematics and dynamics capture, ACM Transactions on Graphics, vol.33, issue.6, 2014.
DOI : 10.1145/2661229.2661286

N. Kyriazis and A. Argyros, Physically Plausible 3D Scene Tracking: The Single Actor Hypothesis, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013.
DOI : 10.1109/CVPR.2013.9

T. Pham, A. Kheddar, A. Qammaz, and A. A. Argyros, Capturing and reproducing hand-object interactions through vision-based force sensing, IEEE ICCV Workshop on Object Understanding for Interaction, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01372238

R. S. Dahiya, G. Metta, M. Valle, and G. Sandini, Tactile Sensing—From Humans to Humanoids, IEEE Transactions on Robotics, vol.26, issue.1, pp.1-20, 2010.
DOI : 10.1109/TRO.2009.2033627

D. Michel, K. Panagiotakis, and A. A. Argyros, Tracking the articulated motion of the human body with two RGBD cameras, Machine Vision Applications, pp.41-54, 2015.
DOI : 10.1007/s00138-014-0651-0

V. M. Zatsiorsky, Kinetics of human motion, Human Kinetics, 2002.

B. I. Prilutsky and V. M. Zatsiorsky, Optimization-Based Models of Muscle Coordination, Exercise and sport sciences reviews, p.32, 2002.
DOI : 10.1097/00003677-200201000-00007

G. Rao, D. Amarantini, E. Berton, and D. Favier, Influence of body segments??? parameters estimation models on inverse dynamics solutions during gait, Journal of Biomechanics, vol.39, issue.8, pp.1531-1536, 2006.
DOI : 10.1016/j.jbiomech.2005.04.014
URL : https://hal.archives-ouvertes.fr/hal-00091846

A. Muller, C. Germain, C. Pontonnier, and G. Dumont, A comparative study of 3 body segment inertial parameters scaling rules, Computer Methods in Biomechanics and Biomedical Engineering, vol.6, issue.sup1, pp.2010-2011, 2015.
DOI : 10.1016/j.jbiomech.2013.11.002
URL : https://hal.archives-ouvertes.fr/hal-01174120

R. Chandler, C. E. Clauser, J. T. Mcconville, H. Reynolds, and J. W. Young, Investigation of inertial properties of the human body, DTIC Document, 1975.

V. Zatsiorsky, V. Seluyanov, and L. Chugunova, In vivo body segment inertial parameters determination using a gamma-scanner method Biomechanics of human movement: Applications in rehabilitation, sports and ergonomics, pp.186-202, 1990.

J. Jovic, A. Escande, K. Ayusawa, E. Yoshida, A. Kheddar et al., Humanoid and Human Inertia Parameter Identification Using Hierarchical Optimization, IEEE Transactions on Robotics, vol.32, issue.3, pp.726-735, 2016.
DOI : 10.1109/TRO.2016.2558190
URL : https://hal.archives-ouvertes.fr/lirmm-01348410

S. Nakaoka, S. Hattori, F. Kanehiro, S. Kajita, and H. Hirukawa, Constraint-based dynamics simulator for humanoid robots with shock absorbing mechanisms, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.3641-3647, 2007.
DOI : 10.1109/IROS.2007.4399415

M. Mohammadi, T. L. Baldi, S. Scheggi, and D. Prattichizzo, Fingertip force estimation via inertial and magnetic sensors in deformable object manipulation, 2016 IEEE Haptics Symposium (HAPTICS), pp.284-289, 2016.
DOI : 10.1109/HAPTICS.2016.7463191

Y. Zhu, C. Jiang, Y. Zhao, D. Terzopoulos, and S. Zhu, Inferring Forces and Learning Human Utilities from Videos, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.3823-3833, 2016.
DOI : 10.1109/CVPR.2016.415

I. Mordatch, K. Lowrey, G. Andrew, Z. Popovic, and E. V. Todorov, Interactive control of diverse complex characters with neural networks, Advances in Neural Information Processing Systems, pp.3132-3140, 2015.

T. Pham, A. Kheddar, A. Qammaz, and A. A. Argyros, Towards force sensing from vision: Observing hand-object interactions to infer manipulation forces, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
URL : https://hal.archives-ouvertes.fr/hal-01356136

R. Dumas, L. Cheze, and J. Verriest, Adjustments to McConville et al. and Young et al. body segment inertial parameters, Journal of Biomechanics, vol.40, issue.3, pp.543-553, 2007.
DOI : 10.1016/j.jbiomech.2006.02.013

Y. Nakamura, K. Yamane, Y. Fujita, and I. Suzuki, Somatosensory computation for man-machine interface from motion-capture data and musculoskeletal human model, IEEE Transactions on Robotics, vol.21, issue.1, pp.58-66, 2005.
DOI : 10.1109/TRO.2004.833798

D. E. Orin, A. Goswami, and S. Lee, Centroidal dynamics of a humanoid robot, Autonomous Robots, vol.104, issue.4, pp.161-176, 2013.
DOI : 10.1007/s10514-013-9341-4

J. L. Elman, Finding Structure in Time, Cognitive Science, vol.49, issue.2, pp.179-211, 1990.
DOI : 10.1207/s15516709cog1402_1

S. Hochreiter and J. Schmidhuber, Long Short-Term Memory, Neural Computation, vol.4, issue.8, pp.1735-1780, 1997.
DOI : 10.1016/0893-6080(88)90007-X

R. Collobert, K. Kavukcuoglu, and C. Farabet, Torch7: A matlab-like environment for machine learning, BigLearn, NIPS Workshop, no. EPFL-CONF-192376, 2011.

N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, Dropout: A simple way to prevent neural networks from overfitting, The Journal of Machine Learning Research, vol.15, issue.1, pp.1929-1958, 2014.

M. Andersen, J. Dahl, and L. Vandenberghe, Cvxopt: A python package for convex optimization, 2013.

Z. Yan, J. Fan, and J. Wang, A Collective Neurodynamic Approach to Constrained Global Optimization, IEEE Transactions on Neural Networks and Learning Systems, 2016.
DOI : 10.1109/TNNLS.2016.2524619

K. Bouyarmane and A. Kheddar, Humanoid Robot Locomotion and Manipulation Step Planning, Advanced Robotics, vol.31, issue.2, pp.1099-1126, 2012.
DOI : 10.1080/01691864.2012.686345
URL : https://hal.archives-ouvertes.fr/lirmm-00777728