Optimality principles in sensorimotor control, Nat Neurosci, vol.7, issue.9, pp.907-915, 2004. ,
Planning algorithms, 2006. ,
URL : https://hal.archives-ouvertes.fr/hal-01993243
The quest for optimality: A positive heuristic of science?, Behav Brain Sci, vol.14, issue.2, pp.205-220, 1991. ,
, Optimality and Modularity in Human Movement: From Optimal Control to Muscle Synergies, pp.105-133, 2019.
URL : https://hal.archives-ouvertes.fr/hal-01744832
Deterministic and stochastic optimal control. Applications of mathematics, 1975. ,
Optimal control theory: An Introduction, 1970. ,
Contrôle optimal : Théorie & applications. Vuibert, editor, 2008. ,
, Stochastic Controls: Hamiltonian Systems and HJB Equations, 1999.
Applied Optimal Control, 1969. ,
DOI : 10.1201/9781315137667
The Role and Use of the Stochastic Linear-Quadratic-Gaussian Problem in Control System Design, IEEE Trans Autom Control, vol.16, issue.6, pp.529-552, 1971. ,
A probabilistic numerical method for fully nonlinear parabolic PDEs, Ann Appl Probab, vol.21, issue.4, pp.1322-1364, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00367103
Semi-Lagrangian approximation schemes for linear and Hamilton-Jacobi equations, Society for Industrial and Applied Mathematics, 2014. ,
DOI : 10.1137/1.9781611973051
URL : https://hal.archives-ouvertes.fr/hal-00916055
Adaptive control of mechanical impedance by coactivation of antagonist muscles, IEEE Trans Autom Control, vol.29, issue.8, pp.681-690, 1984. ,
The central nervous system stabilizes unstable dynamics by learning optimal impedance, Nature, vol.414, issue.6862, pp.446-449, 2001. ,
Processes controlling arm movements in monkeys, Science, vol.201, pp.1235-1237, 1978. ,
Characteristics of motor programs underlying arm movements in monkeys, J Neurophysiol, vol.42, pp.183-194, 1979. ,
Noise in the nervous system, Nat Rev Neurosci, vol.9, issue.4, pp.292-303, 2008. ,
A generalized iterative LQG method for locally-optimal feedback control of constrained nonlinear stochastic systems, American Control Conference, vol.1, pp.300-306, 2005. ,
Constrained model predictive control: Stability and optimality, Automatica, vol.36, issue.6, pp.789-814, 2000. ,
DOI : 10.1016/s0005-1098(99)00214-9
A Fokker-Planck control framework for multidimensional stochastic processes, J Comput Appl Math, vol.237, issue.1, pp.487-507, 2013. ,
DOI : 10.1016/j.cam.2012.06.019
URL : https://doi.org/10.1016/j.cam.2012.06.019
A Hamiltonian approach using partial differential equations for open-loop stochastic optimal control, Proc. American Control Conf. (ACC), pp.2056-2061, 2011. ,
DOI : 10.1109/acc.2011.5991442
The role of execution noise in movement variability, J Neurophysiol, vol.91, issue.2, pp.1050-1063, 2004. ,
Biologically Inspired Joint Stiffness Control, Proc. IEEE Int. Conf. Robotics and Automation, pp.4508-4513, 2005. ,
DOI : 10.1109/robot.2005.1570814
Variable impedance actuators: Moving the robots of tomorrow, Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems, pp.5454-5455, 2012. ,
Stochastic models, estimation, and control, vol.1, 1979. ,
Sixty years of stochastic linearization technique, Meccanica, vol.52, issue.1, pp.299-305, 2017. ,
DOI : 10.1007/s11012-016-0399-x
Random vibration and statistical linearization, vol.1076193, 2003. ,
Linearization methods for stochastic dynamic systems, Lecture Notes in Physics, vol.730, 2008. ,
DOI : 10.1007/978-3-540-72997-6
URL : https://link.springer.com/content/pdf/bfm%3A978-3-540-72997-6%2F1.pdf
Applied Stochastic Differential Equations, Institute of Mathematical Statistics Textbooks, 2019. ,
Stochastic models, estimation, and control, vol.2, 1982. ,
Some Relations Between Extended and Unscented Kalman Filters, IEEE Trans Signal Process, vol.60, issue.2, pp.545-555, 2012. ,
DOI : 10.1109/tsp.2011.2172431
URL : http://liu.diva-portal.org/smash/get/diva2:505951/FULLTEXT01
Non-linear quadratic gaussian control, Int J Control, vol.39, issue.2, pp.343-361, 1984. ,
A half-century of stochastic equivalent linearization. Structural Control and Health Monitoring, vol.13, pp.27-40, 20061. ,
Approximate moment dynamics for polynomial and trigonometric stochastic systems, 2017 IEEE 56th Annual Conference on Decision and Control, pp.1864-1869, 2017. ,
DOI : 10.1109/cdc.2017.8263922
Path integrals and symmetry breaking for optimal control theory, J Stat Mech: Theory Exp, issue.11, p.11011, 2005. ,
DOI : 10.1088/1742-5468/2005/11/p11011
URL : http://arxiv.org/pdf/physics/0505066
The Mathematical Theory of Optimal Processes, 1964. ,
The computational and neural basis of voluntary motor control and planning. Trends in cognitive sciences, vol.16, pp.541-549, 2012. ,
Role of cocontraction in arm movement accuracy, J Neurophysiol, vol.89, issue.5, pp.2396-2405, 2003. ,
Stochastic optimal control with variable impedance manipulators in presence of uncertainties and delayed feedback, Proc. IEEE/RSJ Int Intelligent Robots and Systems (IROS) Conf, pp.4354-4359, 2011. ,
Design and Control of a Passive Noise Rejecting Variable Stiffness Actuator, pp.235-262, 2019. ,
Iterative linearization methods for approximately optimal control and estimation of non-linear stochastic system, Int J Control, vol.80, issue.9, pp.1439-1453, 2007. ,
Stochastic differential dynamic programming, Proceedings of the 2010 American Control Conference. IEEE, pp.1125-1132, 2010. ,
DOI : 10.1109/acc.2010.5530971
URL : http://www-clmc.usc.edu/publications/e/sddp.pdf
A linear theory for control of non-linear stochastic systems, Phys Rev Lett, vol.95, pp.200-201, 2005. ,
Optimal control theory and the linear Bellman equation, Bayesian Time Series Models, pp.363-387, 2011. ,
,
Efficient computation of optimal actions, Proc Natl Acad Sci, vol.106, issue.28, pp.11478-11483, 2009. ,
A generalized path integral control approach to reinforcement learning. journal of machine learning research, vol.11, pp.3137-3181, 2010. ,
Open-loop stochastic optimal control of a passive noise-rejection variable stiffness actuator: Application to unstable tasks, Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems, pp.3029-3034, 2013. ,
Stochastic optimal control and estimation methods adapted to the noise characteristics of the sensorimotor system, Neural Comput, vol.17, issue.5, pp.1084-1108, 2005. ,
Virtual trajectory and stiffness ellipse during multijoint arm movement predicted by neural inverse models, Biol Cybern, vol.69, pp.353-362, 1993. ,
DOI : 10.1007/bf01185407
The coordination of arm movements: an experimentally confirmed mathematical model, J Neurosci, vol.5, issue.7, pp.1688-1703, 1985. ,
The inactivation principle: mathematical solutions minimizing the absolute work and biological implications for the planning of arm movements, PLoS Comput Biol, vol.4, issue.10, p.1000194, 2008. ,
URL : https://hal.archives-ouvertes.fr/inserm-00705805
Evidence for composite cost functions in arm movement planning: an inverse optimal control approach, PLoS Comput Biol, vol.7, issue.10, p.1002183, 2011. ,
DOI : 10.1371/journal.pcbi.1002183
URL : https://hal.archives-ouvertes.fr/inserm-00704789
Muscle coactivation: definitions, mechanisms, and functions, J Neurophysiol, vol.120, pp.88-104, 2018. ,
DOI : 10.1152/jn.00084.2018
Signal-dependent noise determines motor planning, Nature, vol.394, issue.6695, pp.780-784, 1998. ,
DOI : 10.1038/29528
Adaptation to stable and unstable dynamics achieved by combined impedance control and inverse dynamics model, J Neurophysiol, vol.90, pp.3270-3282, 2003. ,
DOI : 10.1152/jn.01112.2002
URL : http://www.cns.atr.jp/~kawato/Ppdf/FranklinJNP2003.pdf
New Insights on the Application of Moment Closure Methods to Nonlinear Stochastic Systems, IUTAM Symposium on Advances in Nonlinear Stochastic Mechanics, pp.479-488, 1996. ,