Synthesis of biologically realistic human motion using joint torque actuation
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C. Karen Liu | Friedl De Groote | Yifeng Jiang | C. K. Liu | Tom Van Wouwe | F. De Groote | F. D. Groote | T. Van Wouwe | Yifeng Jiang | T. V. Wouwe | C. K. Liu
[1] Eftychios Sifakis,et al. Realistic Biomechanical Simulation and Control of Human Swimming , 2014, ACM Trans. Graph..
[2] B. R. Umberger,et al. Stance and swing phase costs in human walking , 2010, Journal of The Royal Society Interface.
[3] Vladlen Koltun,et al. Optimizing locomotion controllers using biologically-based actuators and objectives , 2012, ACM Trans. Graph..
[4] Ronald Fedkiw,et al. Automatic determination of facial muscle activations from sparse motion capture marker data , 2005, ACM Trans. Graph..
[5] Zoran Popovic,et al. Discovery of complex behaviors through contact-invariant optimization , 2012, ACM Trans. Graph..
[6] Zoran Popovic,et al. Physically based motion transformation , 1999, SIGGRAPH.
[7] Sergey Levine,et al. DeepMimic , 2018, ACM Trans. Graph..
[8] Eftychios Sifakis,et al. Dexterous manipulation and control with volumetric muscles , 2018, ACM Trans. Graph..
[9] Jehee Lee,et al. Precomputing avatar behavior from human motion data , 2004, SCA '04.
[10] D. C. Lin,et al. Experimental determination of sarcomere force-length relationship in type-I human skeletal muscle fibers. , 2009, Journal of biomechanics.
[11] Philip E. Martin,et al. A Model of Human Muscle Energy Expenditure , 2003, Computer methods in biomechanics and biomedical engineering.
[12] Tim W Dorn,et al. Comparison of different methods for estimating muscle forces in human movement , 2012, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.
[13] Tao Zhou,et al. Deep learning of biomimetic sensorimotor control for biomechanical human animation , 2018, ACM Trans. Graph..
[14] Ross H Miller. A comparison of muscle energy models for simulating human walking in three dimensions. , 2014, Journal of biomechanics.
[15] Jessica K. Hodgins,et al. Synthesizing physically realistic human motion in low-dimensional, behavior-specific spaces , 2004, ACM Trans. Graph..
[16] Zoran Popović,et al. Compact character controllers , 2009, SIGGRAPH 2009.
[17] Taesoo Kwon,et al. Locomotion control for many-muscle humanoids , 2014, ACM Trans. Graph..
[18] Matthew Millard,et al. Flexing computational muscle: modeling and simulation of musculotendon dynamics. , 2013, Journal of biomechanical engineering.
[19] Michiel van de Panne,et al. Flexible muscle-based locomotion for bipedal creatures , 2013, ACM Trans. Graph..
[20] F. Zajac. Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. , 1989, Critical reviews in biomedical engineering.
[21] Anil V. Rao,et al. ( Preprint ) AAS 09-334 A SURVEY OF NUMERICAL METHODS FOR OPTIMAL CONTROL , 2009 .
[22] Lorenz T. Biegler,et al. On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming , 2006, Math. Program..
[23] G. C. Joyce,et al. The mechanical properties of cat soleus muscle during controlled lengthening and shortening movements , 1969, The Journal of physiology.
[24] Zoran Popovic,et al. Generalizing locomotion style to new animals with inverse optimal regression , 2014, ACM Trans. Graph..
[25] Dinesh K. Pai,et al. Musculotendon simulation for hand animation , 2008, SIGGRAPH 2008.
[26] C. Karen Liu,et al. Learning to dress , 2018, ACM Trans. Graph..
[27] Antonio Pedotti,et al. Optimization of muscle-force sequencing in human locomotion , 1978 .
[28] Marko Ackermann,et al. Optimality principles for model-based prediction of human gait. , 2010, Journal of biomechanics.
[29] Ronald Fedkiw,et al. Automatic determination of facial muscle activations from sparse motion capture marker data , 2005, SIGGRAPH '05.
[30] Christopher L. Dembia,et al. Stretching Your Energetic Budget: How Tendon Compliance Affects the Metabolic Cost of Running , 2016, PloS one.
[31] Arjan Egges,et al. Evaluating the Physical Realism of Character Animations Using Musculoskeletal Models , 2010, MIG.
[32] M. Pandy,et al. A phenomenological model for estimating metabolic energy consumption in muscle contraction. , 2004, Journal of biomechanics.
[33] Taku Komura,et al. Creating and retargetting motion by the musculoskeletal human body model , 2000, The Visual Computer.
[34] C. Karen Liu,et al. Learning symmetric and low-energy locomotion , 2018, ACM Trans. Graph..
[35] Nancy S. Pollard,et al. Responsive characters from motion fragments , 2007, SIGGRAPH 2007.
[36] M. Nussbaum,et al. Maximum voluntary joint torque as a function of joint angle and angular velocity: model development and application to the lower limb. , 2007, Journal of biomechanics.
[37] Antonie J van den Bogert,et al. A metabolic energy expenditure model with a continuous first derivative and its application to predictive simulations of gait , 2018, Computer methods in biomechanics and biomedical engineering.
[38] Jinxiang Chai,et al. Synthesis and editing of personalized stylistic human motion , 2010, I3D '10.
[39] Matthias Zwicker,et al. Real-time planning for parameterized human motion , 2008, SCA '08.
[40] Sergey M. Plis,et al. Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments , 2018, ArXiv.
[41] M. Pandy,et al. Dynamic optimization of human walking. , 2001, Journal of biomechanical engineering.
[42] Michael Gleicher,et al. Retargetting motion to new characters , 1998, SIGGRAPH.
[43] Andrew P. Witkin,et al. Spacetime constraints , 1988, SIGGRAPH.
[44] Jungdam Won,et al. Aerobatics control of flying creatures via self-regulated learning , 2018, ACM Trans. Graph..
[45] M G Pandy,et al. Static and dynamic optimization solutions for gait are practically equivalent. , 2001, Journal of biomechanics.
[46] C. Karen Liu,et al. Animating responsive characters with dynamic constraints in near-unactuated coordinates , 2008, SIGGRAPH 2008.
[47] Michiel van de Panne,et al. Learning locomotion skills using DeepRL: does the choice of action space matter? , 2016, Symposium on Computer Animation.
[48] Maarten F Bobbert,et al. Robust passive dynamics of the musculoskeletal system compensate for unexpected surface changes during human hopping. , 2009, Journal of applied physiology.
[49] Vladlen Koltun,et al. Animating human lower limbs using contact-invariant optimization , 2013, ACM Trans. Graph..
[50] Michael F. Cohen,et al. Efficient generation of motion transitions using spacetime constraints , 1996, SIGGRAPH.
[51] W S Levine,et al. An optimal control model for maximum-height human jumping. , 1990, Journal of biomechanics.
[52] C. Karen Liu,et al. Learning physics-based motion style with nonlinear inverse optimization , 2005, ACM Trans. Graph..
[53] Sergey Levine,et al. Learning to Run challenge: Synthesizing physiologically accurate motion using deep reinforcement learning , 2018, ArXiv.
[54] A. J. van den Bogert,et al. Intrinsic muscle properties facilitate locomotor control - a computer simulation study. , 1998, Motor control.
[55] Anil V. Rao,et al. Evaluation of Direct Collocation Optimal Control Problem Formulations for Solving the Muscle Redundancy Problem , 2016, Annals of Biomedical Engineering.
[56] F.E. Zajac,et al. An interactive graphics-based model of the lower extremity to study orthopaedic surgical procedures , 1990, IEEE Transactions on Biomedical Engineering.
[57] M. Pandy,et al. A Dynamic Optimization Solution for Vertical Jumping in Three Dimensions. , 1999, Computer methods in biomechanics and biomedical engineering.
[58] David A Gabriel,et al. Maximum isometric arm forces in the horizontal plane. , 2006, Journal of biomechanics.
[59] Sepp Hochreiter,et al. Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) , 2015, ICLR.
[60] D. Dowson,et al. Elbow joint force predictions for some strenuous isometric actions. , 1980, Journal of biomechanics.
[61] Glen Berseth,et al. DeepLoco , 2017, ACM Trans. Graph..
[62] Eugene Fiume,et al. Helping hand: an anatomically accurate inverse dynamics solution for unconstrained hand motion , 2005, SCA '05.
[63] Jessica K. Hodgins,et al. Synthesizing physically realistic human motion in low-dimensional, behavior-specific spaces , 2004, SIGGRAPH 2004.
[64] Philippe Beaudoin,et al. Robust task-based control policies for physics-based characters , 2009, SIGGRAPH 2009.
[65] Jeffrey A Reinbolt,et al. OpenSim: a musculoskeletal modeling and simulation framework for in silico investigations and exchange. , 2011, Procedia IUTAM.
[66] Nancy S. Pollard,et al. Efficient synthesis of physically valid human motion , 2003, ACM Trans. Graph..
[67] M. Kass,et al. Animating oscillatory motion with overlap: wiggly splines , 2008, SIGGRAPH 2008.
[68] Demetri Terzopoulos,et al. Heads up!: biomechanical modeling and neuromuscular control of the neck , 2006, SIGGRAPH 2006.
[69] C. Karen Liu,et al. Synthesis of complex dynamic character motion from simple animations , 2002, ACM Trans. Graph..
[70] Demetri Terzopoulos,et al. Realistic modeling for facial animation , 1995, SIGGRAPH.
[71] Eftychios Sifakis,et al. Comprehensive biomechanical modeling and simulation of the upper body , 2009, TOGS.
[72] M. V. D. Panne,et al. LEARNING LOCOMOTION SKILLS USING DEEPRL: DOES , 2017 .