Abstract
Understanding and synthesizing human motions are an important scientific quest. It also has broad applications in computer animation. Research on physically based character animation in the last two decades has achieved impressive advancement. A large variety of human activities are synthesized automatically in a physically simulated environment. The two key components of physically based character animation are (1) physical simulation that models the dynamics of humans and their environment and (2) controller optimization that optimizes the character’s motions in the simulation. This approach has an inherent realism because we all live in a world that obeys physical laws, and we evolved to survive in this physical environment. In this chapter, we will review the state of the art of physically based character animation, introduce a few established methods in physical simulation and motor control, and discuss promising future directions.
References
Abe Y, da Silva M, Popovic’ J (2007) Multiobjective control with frictional contacts. In: Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation. SCA”07. pp 249–258
Andrews S, Kry P (2013) Goal directed multi-finger manipulation: control policies and analysis. Comput Graph 37(7):830–839
Bai Y, Liu CK (2014) Coupling cloth and rigid bodies for dexterous manipulation. In: Proceedings of the seventh international conference on motion in games. MIG”14. ACM, pp 139–145
Bharaj G, Coros S, Thomaszewski B, Tompkin J, Bickel B, Pfister H (2015) Computational design of walking automata. In: Proceedings of the 14th ACM SIGGRAPH/eurographics symposium on computer animation. SCA”15. ACM, pp 93–100
Clegg A, Tan J, Turk G, Liu CK (2015) Animating human dressing. ACM Trans Graph 34(4):116:1–116:9
Coros S, Beaudoin P, van de Panne M (2009) Robust task-based control policies for physics-based characters. ACM Trans Graph 28(5):170:1–170:9
Coros S, Beaudoin P, van de Panne M (2010) Generalized biped walking control. ACM Trans Graph 29(4):130, Article 130
Coros S, Karpathy A, Jones B, Reveret L, van de Panne M (2011) Locomotion skills for simulated quadrupeds. ACM Trans Graph 30(4):59
Da Silva M, Abe Y, Popovic’ J (2008) Interactive simulation of stylized human locomotion. In: ACM SIGGRAPH 2008 Papers. SIGGRAPH”08. ACM, pp 82:1–82:10
DiLorenzo PC, Zordan VB, Sanders BL (2008) Laughing out loud: control for modeling anatomically inspired laughter using audio. In: ACM SIGGRAPH Asia 2008 papers. SIGGRAPH Asia”08. pp 125:1–125:8
Erez T, Tassa Y, Todorov E (2015) Simulation tools for model-based robotics: comparison of bullet, havok, mujoco, ode and physx. In: ‘ICRA’, IEEE. pp 4397–4404
Erleben K (2007) Velocity-based shock propagation for multibody dynamics animation. ACM Transactions on Graphics (TOG), 26(2), Article No. 12.
Geijtenbeek T, van de Panne M, van der Stappen AF (2013) Flexible muscle-based locomotion for bipedal creatures. ACM Trans Graph 32(6)
Ha S, Ye Y, Liu CK (2012) Falling and landing motion control for character animation. ACM Trans Graph 31(6):1
Hansen N (2006) The cma evolution strategy: a comparing review. In: Towards a new evolutionary computation. Springer, New York, pp 75–102
Hinton GE (2012) A practical guide to training restricted Boltzmann machines. In: Montavon G, Orr GB, Mller K-R (eds) Neural networks: tricks of the trade, 2nd edn, Lecture notes in computer science. Springer, New York, pp 599–619
Hodgins JK, Wooten WL, Brogan DC, O’Brien JF (1995) Animating human athletics. In: SIGGRAPH. pp 71–78
Jain S, Ye Y, Liu CK (2009) Optimization-based interactive motion synthesis. ACM Trans Graph 28(1):1–10
Kaelbling LP, Littman ML, Moore AP (1996) Reinforcement learning: a survey. J Artif Intell Res 4:237–285
Kaufman DM, Sueda S, James DL, Pai DK (2008) Staggered projections for frictional contact in multibody systems. ACM Trans Graph 27:164:1–164:11
Kim J, Pollard NS (2011) Direct control of simulated non-human characters. IEEE Comput Graph Appl 31(4):56–65
Kober J, Bagnell JAD, Peters J (2013) Reinforcement learning in robotics: a survey. Int J Robot Res 32:1238
Kwatra N, Wojtan C, Carlson M, Essa I, Mucha P, Turk G (2009) Fluid simulation with articulated bodies. IEEE Trans Vis Comput Graph 16(1):70–80
Kwon T, Hodgins J (2010) Control systems for human running using an inverted pendulum model and a reference motion capture sequence. In: Proceedings of the 2010 ACM SIGGRAPH/eurographics symposium on computer animation. SCA”10. Eurographics Association, pp 129–138
Laszlo J, van de Panne M, Fiume E (1996) Limit cycle control and its application to the animation of balancing and walking. In: Proceedings of the 23rd annual conference on computer graphics and interactive techniques. SIGGRAPH”96. ACM, pp 155–162
Lee S-H, Terzopoulos D (2006) Heads up! Biomechanical modeling and neuromuscular control of the neck. ACM Trans Graph 25(3):1188–1198
Lee S-H, Sifakis E, Terzopoulos D (2009) Comprehensive biomechanical modeling and simulation of the upper body. ACM Trans Graph 28:99:1–99:17
Levine S, Wang JM, Haraux A, Popovic’ Z, Koltun V (2012) Continuous character control with low-dimensional embeddings. ACM Trans Graph 31(4):28:1–28:10
Liu CK (2009) Dextrous manipulation from a grasping pose. ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH 2009, 28(3), Article No. 59.
Liu CK, Jain S (2012) A short tutorial on multibody dynamics, Technical report GIT-GVU-15-01-1, Georgia Institute of Technology, School of Interactive Computing
Liu CK, Popovic’ Z (2002) Synthesis of complex dynamic character motion from simple animations. In: Proceedings of the 29th annual conference on computer graphics and interactive techniques. SIGGRAPH”02. ACM, pp 408–416
Liu L, Yin K, van de Panne M, Shao T, Xu W (2010) Sampling-based contact-rich motion control. ACM Trans Graph 29(4), Article 128
Lloyd J (2005) Fast implementation of Lemke’s algorithm for rigid body contact simulation. In: Proceedings of the 2005 I.E. international conference on robotics and automation. ICRA 2005. pp 4538–4543
Megaro V, Thomaszewski B, Nitti M, Hilliges O, Gross M, Coros S (2015) Interactive design of 3d-printable robotic creatures. ACM Trans Graph 34(6):216:1–216:9
Mordatch I, de Lasa M, Hertzmann A (2010) Robust physics-based locomotion using low-dimensional planning. In: ACM SIGGRAPH 2010 papers. SIG- GRAPH”10. ACM, pp 71:1–71:8
Mordatch I, Popovic’ Z, Todorov E (2012) Contact-invariant optimization for hand manipulation. In: Proceedings of the ACM SIGGRAPH/eurographics symposium on computer animation. SCA”12. Eurographics Association, pp 137–144
Mordatch I, Wang JM, Todorov E, Koltun V (2013) Animating human lower limbs using contact-invariant optimization. ACM Trans Graph 32(6):203:1–203:8
Muico U, Lee Y, Popovic’ J, Popovic’ Z (2009) Contact-aware nonlinear control of dynamic characters. In: ACM SIGGRAPH 2009 papers. SIGGRAPH”09. ACM, pp 81:1–81:9
Ng AY, Jordan M (2000) Pegasus: a policy search method for large MDPs and POMDPs. In: Proceedings of the sixteenth conference on uncertainty in artificial intelligence, UAI’00. Morgan Kaufmann Publishers, San Francisco, pp 406–415
Ng AY, Russell SJ (2000) Algorithms for inverse reinforcement learning. In: Proceedings of the seventeenth international conference on machine learning, ICML”00. Morgan Kaufmann Publishers, San Francisco, pp 663–670
Otaduy MA, Tamstorf R, Steinemann D, Gross M (2009) Implicit contact handling for deformable objects. Comput Graph Forum (Proc. of Euro- graphics) 28(2):559-568
Pratt JE, Chew C-M, Torres A, Dilworth P, Pratt GA (2001) Virtual model control: an intuitive approach for bipedal locomotion. Int J Robot Res 20(2):129–143
Si W, Lee S-H, Sifakis E, Terzopoulos D (2014) Realistic biomechanical simulation and control of human swimming. ACM Trans Graph 34(1):10:1–10:15
Sueda S, Kaufman A, Pai DK (2008) Musculotendon simulation for hand animation. ACM Trans Graph 27:83:1–83:8
Tan J, Siu K, Liu CK (2012a) Contact handling for articulated rigid bodies using lcp. Technical report GIT-GVU-15-01-2, Georgia Institute of Technology, School of Interactive Computing
Tan J, Turk G, Liu CK (2012a) Soft body locomotion. ACM Trans Graph 31(4):26:1–26:11
Tan J, Gu Y, Liu CK, Turk G (2014) Learning bicycle stunts. ACM Trans Graph 33(4):50:1–50:12
Thomas F, Johnston O (1995) The illusion of life: Disney animation, Hyperion. Abbeville Press, New York, NY.
Todorov E (2006) Optimal control theory. In: Bayesian brain: probabilistic approaches to neural coding. MIT Press, Cambridge, MA. pp 269–298
Treuille A, Lee Y, Popovic’ Z (2007) Near-optimal character animation with continuous control. ACM Trans Graph 26(3):7
Tsai Y-Y, Lin W-C, Cheng KB, Lee J, Lee T-Y (2010) Real-time physics-based 3D biped character animation using an inverted pendulum model. IEEE Trans Vis Comput Graph 16(2):325–337
Tsang W, Singh K, Eugene F (2005) Helping hand: an anatomically accurate inverse dynamics solution for unconstrained hand motion. In: Proceedings of the 2005 ACM SIGGRAPH/eurographics symposium on computer animation. SCA”05. pp 319–328
Vincent P, Larochelle H, Bengio Y, Manzagol P-A (2008) Extracting and composing robust features with denoising autoencoders. In: Proceedings of the 25th international conference on machine learning. ICML”08. ACM, pp 1096–1103
Wampler K, Popovic’ Z (2009) Optimal gait and form for animal locomotion. ACM Trans Graph 28(3):60:1–60:8
Wang JM, Fleet DJ, Hertzmann A (2009) Optimizing walking controllers. ACM Trans Graph 28(5):168:1–168:8
Wang JM, Fleet DJ, Hertzmann A (2010) Optimizing walking controllers for uncertain inputs and environments. ACM Trans Graph 29(4):73:1–73:8
Wang JM, Hamner SR, Delp SL, Koltun V (2012) Optimizing locomotion controllers using biologically-based actuators and objectives. ACM Trans Graph 31(4):25:1–25:11
Witkin A, Kass M (1988) Spacetime constraints. In: Proceedings of the 15th annual Conference on computer graphics and interactive techniques. SIG- GRAPH”88. ACM, pp 159–168
Wu J-C, Popovic’ Z (2010) Terrain-adaptive bipedal locomotion control. In: ACM SIGGRAPH 2010 papers. SIGGRAPH”10. ACM, pp 72:1–72:10
Ye Y, Liu CK (2010) Optimal feedback control for character animation using an abstract model. In: SIGGRAPH”10: ACM SIGGRAPH 2010 papers. ACM, New York, pp 1–9
Ye Y, Liu CK (2012) Synthesis of detailed hand manipulations using contact sampling. ACM Trans Graph 31(4):41:1–41:10
Yin K, Loken K, van de Panne M (2007) SIMBICON: simple biped locomotion control. In: ACM SIGGRAPH 2007 papers. SIGGRAPH”07
Yin K, Coros S, Beaudoin P, van de Panne M (2008) Continuation methods for adapting simulated skills. ACM Trans Graph 27(3):81
Zordan VB, Celly B, Chiu B, DiLorenzo PC (2006) Breathe easy: model and control of human respiration for computer animation. Graph Models 68:113–132
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this entry
Cite this entry
Tan, J. (2016). Physically Based Character Animation Synthesis. In: Müller, B., et al. Handbook of Human Motion. Springer, Cham. https://doi.org/10.1007/978-3-319-30808-1_11-1
Download citation
DOI: https://doi.org/10.1007/978-3-319-30808-1_11-1
Received:
Accepted:
Published:
Publisher Name: Springer, Cham
Online ISBN: 978-3-319-30808-1
eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering