Papers
Topics
Authors
Recent
2000 character limit reached

Actuators À La Mode: Modal Actuations for Soft Body Locomotion (2405.18609v1)

Published 28 May 2024 in cs.GR

Abstract: Traditional character animation specializes in characters with a rigidly articulated skeleton and a bipedal/quadripedal morphology. This assumption simplifies many aspects for designing physically based animations, like locomotion, but comes with the price of excluding characters of arbitrary deformable geometries. To remedy this, our framework makes use of a spatio-temporal actuation subspace built off of the natural vibration modes of the character geometry. The resulting actuation is coupled to a reduced fast soft body simulation, allowing us to formulate a locomotion optimization problem that is tractable for a wide variety of high resolution deformable characters.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (62)
  1. Jernej Barbič and Doug L. James. 2005. Real-Time Subspace Integration for St. Venant-Kirchhoff Deformable Models. ACM Trans. Graph. 24, 3 (jul 2005), 982–990. https://doi.org/10.1145/1073204.1073300
  2. Fast Complementary Dynamics via Skinning Eigenmodes. arXiv:2303.11886 [cs.GR]
  3. DReCon: data-driven responsive control of physics-based characters. ACM Trans. Graph. 38, 6, Article 206 (nov 2019), 11 pages. https://doi.org/10.1145/3355089.3356536
  4. Evolution gym: A large-scale benchmark for evolving soft robots. Advances in Neural Information Processing Systems 34 (2021).
  5. Projective dynamics: fusing constraint projections for fast simulation. ACM Trans. Graph. 33, 4, Article 154 (jul 2014), 11 pages. https://doi.org/10.1145/2601097.2601116
  6. Hyper-reduced projective dynamics. ACM Trans. Graph. 37, 4, Article 80 (jul 2018), 13 pages. https://doi.org/10.1145/3197517.3201387
  7. Christopher Brandt and Klaus Hildebrandt. 2017. Compressed vibration modes of elastic bodies. Computer Aided Geometric Design 52-53 (2017), 297–312. https://doi.org/10.1016/j.cagd.2017.03.004 Geometric Modeling and Processing 2017.
  8. Jinxiang Chai and Jessica K. Hodgins. 2005. Performance animation from low-dimensional control signals. ACM Trans. Graph. 24, 3 (jul 2005), 686–696. https://doi.org/10.1145/1073204.1073248
  9. LiCROM: Linear-Subspace Continuous Reduced Order Modeling with Neural Fields. arXiv:2310.15907 [cs.GR]
  10. Deformable Objects Alive! ACM Trans. Graph. 31, 4, Article 69 (jul 2012), 9 pages. https://doi.org/10.1145/2185520.2185565
  11. Nonlinear Compliant Modes for Large-Deformation Analysis of Flexible Structures. ACM Trans. Graph. 42, 2, Article 21 (nov 2022), 11 pages. https://doi.org/10.1145/3568952
  12. Flexible muscle-based locomotion for bipedal creatures. ACM Transactions on Graphics (TOG) 32, 6 (2013), 1–11.
  13. Pierre A Guertin. 2009. The mammalian central pattern generator for locomotion. Brain research reviews 62, 1 (2009), 45–56.
  14. Nikolaus Hansen. 2006. The CMA evolution strategy: a comparing review. Towards a new evolutionary computation: Advances in the estimation of distribution algorithms (2006), 75–102.
  15. CMA-ES/pycma on Github. Zenodo, DOI:10.5281/zenodo.2559634. https://doi.org/10.5281/zenodo.2559634
  16. Emergence of locomotion behaviours in rich environments. arXiv preprint arXiv:1707.02286 (2017).
  17. Learned motion matching. ACM Trans. Graph. 39, 4, Article 53 (aug 2020), 13 pages. https://doi.org/10.1145/3386569.3392440
  18. Phase-functioned neural networks for character control. ACM Trans. Graph. 36, 4, Article 42 (jul 2017), 13 pages. https://doi.org/10.1145/3072959.3073663
  19. Learning motion manifolds with convolutional autoencoders. In SIGGRAPH Asia 2015 Technical Briefs (Kobe, Japan) (SA ’15). Association for Computing Machinery, New York, NY, USA, Article 18, 4 pages. https://doi.org/10.1145/2820903.2820918
  20. DiffTaichi: Differentiable Programming for Physical Simulation. CoRR abs/1910.00935 (2019). arXiv:1910.00935 http://arxiv.org/abs/1910.00935
  21. DittoGym: Learning to Control Soft Shape-Shifting Robots. arXiv:2401.13231 [cs.RO]
  22. Phace: physics-based face modeling and animation. ACM Trans. Graph. 36, 4, Article 153 (jul 2017), 14 pages. https://doi.org/10.1145/3072959.3073664
  23. Fast Automatic Skinning Transformations. ACM Trans. Graph. 31, 4, Article 77 (jul 2012), 10 pages. https://doi.org/10.1145/2185520.2185573
  24. Sumit Jain and C Karen Liu. 2011. Modal-space control for articulated characters. ACM Transactions on Graphics 30, 5 (2011), 118.
  25. From Skin to Skeleton: Towards Biomechanically Accurate 3D Digital Humans. ACM Trans. Graph. 42, 6, Article 253 (dec 2023), 12 pages. https://doi.org/10.1145/3618381
  26. Junggon Kim and Nancy S Pollard. 2011a. Direct control of simulated nonhuman characters. IEEE Computer Graphics and Applications 31, 4 (2011), 56–65.
  27. Junggon Kim and Nancy S Pollard. 2011b. Fast simulation of skeleton-driven deformable body characters. ACM Transactions on Graphics (TOG) 30, 5 (2011), 1–19.
  28. Theodore Kim and David Eberle. 2022. Dynamic Deformables: Implementation and Production Practicalities (Now with Code!). In ACM SIGGRAPH 2022 Courses (Vancouver, British Columbia, Canada) (SIGGRAPH ’22). Association for Computing Machinery, New York, NY, USA, Article 7, 259 pages. https://doi.org/10.1145/3532720.3535628
  29. Modal Locomotion: Animating Virtual Characters with Natural Vibrations. Computer Graphics Forum 28, 2 (2009), 289–298. https://doi.org/10.1111/j.1467-8659.2009.01368.x arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1467-8659.2009.01368.x
  30. Scalable muscle-actuated human simulation and control. ACM Transactions On Graphics (TOG) 38, 4 (2019), 1–13.
  31. Comprehensive biomechanical modeling and simulation of the upper body. ACM Trans. Graph. 28, 4, Article 99 (sep 2009), 17 pages. https://doi.org/10.1145/1559755.1559756
  32. Locomotion control for many-muscle humanoids. ACM Transactions on Graphics (TOG) 33, 6 (2014), 1–11.
  33. Learning Reduced-Order Soft Robot Controller. arXiv:2311.01720 [cs.RO]
  34. SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation. CoRR abs/2011.07215 (2020). arXiv:2011.07215 https://arxiv.org/abs/2011.07215
  35. Simulation and control of skeleton-driven soft body characters. ACM Trans. Graph. 32, 6, Article 215 (nov 2013), 8 pages. https://doi.org/10.1145/2508363.2508427
  36. DiffAqua: A Differentiable Computational Design Pipeline for Soft Underwater Swimmers with Shape Interpolation. ACM Transactions on Graphics (TOG) 40, 4 (2021), 132.
  37. Localized Manifold Harmonics for Spectral Shape Analysis. CoRR abs/1707.02596 (2017). arXiv:1707.02596 http://arxiv.org/abs/1707.02596
  38. SoftCon: Simulation and Control of Soft-Bodied Animals with Biomimetic Actuators. ACM Trans. Graph. 38, 6, Article 208 (nov 2019), 12 pages. https://doi.org/10.1145/3355089.3356497
  39. Using Natural Vibrations to Guide Control for Locomotion. In Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games (Costa Mesa, California) (I3D ’12). Association for Computing Machinery, New York, NY, USA, 87–94. https://doi.org/10.1145/2159616.2159631
  40. Zherong Pan and Dinesh Manocha. 2018. Active Animations of Reduced Deformable Models with Environment Interactions. ACM Trans. Graph. 37, 3, Article 36 (aug 2018), 17 pages. https://doi.org/10.1145/3197565
  41. DeepMimic: example-guided deep reinforcement learning of physics-based character skills. ACM Trans. Graph. 37, 4, Article 143 (jul 2018), 14 pages. https://doi.org/10.1145/3197517.3201311
  42. AMP: Adversarial motion priors for stylized physics-based character control. ACM Transactions on Graphics 40, 4, Article 1 (July 2021), 15 pages.
  43. A. Pentland and J. Williams. 1989. Good Vibrations: Modal Dynamics for Graphics and Animation. SIGGRAPH Comput. Graph. 23, 3 (jul 1989), 207–214. https://doi.org/10.1145/74334.74355
  44. Motor Babble: Morphology-Driven Coordinated Control of Articulated Characters. In Proceedings of the 14th ACM SIGGRAPH Conference on Motion, Interaction and Games (Virtual Event, Switzerland) (MIG ’21). Association for Computing Machinery, New York, NY, USA, Article 6, 10 pages. https://doi.org/10.1145/3487983.3488291
  45. Learning to Locomote: Understanding How Environment Design Matters for Deep Reinforcement Learning. In Proceedings of the 13th ACM SIGGRAPH Conference on Motion, Interaction and Games (Virtual Event, SC, USA) (MIG ’20). Association for Computing Machinery, New York, NY, USA, Article 16, 10 pages. https://doi.org/10.1145/3424636.3426907
  46. Differentiable implicit soft-body physics. arXiv preprint arXiv:2102.05791 (2021).
  47. Computational bodybuilding: Anatomically-based modeling of human bodies. ACM Transactions on Graphics (TOG) 34, 4 (2015), 1–12.
  48. Peter Hans Schoenemann. 1964. A solution of the orthogonal Procrustes problem with applications to orthogonal and oblique rotation. University of Illinois at Urbana-Champaign.
  49. Data-Free Learning of Reduced-Order Kinematics. (2023).
  50. Olga Sorkine and Marc Alexa. 2007. As-Rigid-as-Possible Surface Modeling. In Proceedings of the Fifth Eurographics Symposium on Geometry Processing (Barcelona, Spain) (SGP ’07). Eurographics Association, Goslar, DEU, 109–116.
  51. DeepPhase: periodic autoencoders for learning motion phase manifolds. ACM Trans. Graph. 41, 4, Article 136 (jul 2022), 13 pages. https://doi.org/10.1145/3528223.3530178
  52. Articulated swimming creatures. ACM Transactions on Graphics (TOG) 30, 4 (2011), 1–12.
  53. Stable proportional-derivative controllers. IEEE Computer Graphics and Applications 31, 4 (2011), 34–44.
  54. Soft body locomotion. ACM Trans. Graph. 31, 4, Article 26 (jul 2012), 11 pages. https://doi.org/10.1145/2185520.2185522
  55. Subspace Mixed Finite Elements for Real-Time Heterogeneous Elastodynamics. In SIGGRAPH Asia 2023 Conference Papers (¡conf-loc¿, ¡city¿Sydney¡/city¿, ¡state¿NSW¡/state¿, ¡country¿Australia¡/country¿, ¡/conf-loc¿) (SA ’23). Association for Computing Machinery, New York, NY, USA, Article 112, 10 pages. https://doi.org/10.1145/3610548.3618220
  56. Mixed Variational Finite Elements for Implicit Simulation of Deformables. In SIGGRAPH Asia 2022 Conference Papers (Daegu, Republic of Korea) (SA ’22). Association for Computing Machinery, New York, NY, USA, Article 40, 8 pages. https://doi.org/10.1145/3550469.3555418
  57. Xiaoyuan Tu and Demetri Terzopoulos. 1994. Artificial fishes: Physics, locomotion, perception, behavior. In Proceedings of the 21st annual conference on Computer graphics and interactive techniques. 43–50.
  58. Wikipedia contributors. 2023. Orthogonal Procrustes problem — Wikipedia, The Free Encyclopedia. https://en.wikipedia.org/w/index.php?title=Orthogonal_Procrustes_problem&oldid=1190317617 [Online; accessed 18-May-2024].
  59. Pei Xu and Ioannis Karamouzas. 2021. A GAN-Like Approach for Physics-Based Imitation Learning and Interactive Character Control. Proc. ACM Comput. Graph. Interact. Tech. 4, 3, Article 44 (sep 2021), 22 pages. https://doi.org/10.1145/3480148
  60. AdaptNet: Policy Adaptation for Physics-Based Character Control. ACM Transactions on Graphics 42, 6 (2023). https://doi.org/10.1145/3618375
  61. SIMBICON: simple biped locomotion control. ACM Trans. Graph. 26, 3 (jul 2007), 105–es. https://doi.org/10.1145/1276377.1276509
  62. Learning symmetric and low-energy locomotion. ACM Trans. Graph. 37, 4, Article 144 (jul 2018), 12 pages. https://doi.org/10.1145/3197517.3201397

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now
Slide Deck Streamline Icon: https://streamlinehq.com

Whiteboard

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Generate Now
Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Generate Now
List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

User Circle Single Streamline Icon: https://streamlinehq.com Sign Up
X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets

Sign up for free to view the 1 tweet with 0 likes about this paper.

User Circle Single Streamline Icon: https://streamlinehq.com Sign Up for Free