1. Sig2011 seminar Jin Zhou 2011.7.6

2. Animal Control –Composite Control of Physically Simulated Characters (Tog 10) –Character Animation in Two-Player Adversarial Games (Tog 10) –Space-Time Planning with Parameterized Locomotion Controllers (Sig 11) –Locomotion Skills for Simulated Quadrupeds (Sig 11) –Articulated Swimming Creatures (Sig 11) Simulation –Efficient elasticity for character skinning with contact and collisions (Sig 11) –Sensitive Couture for Interactive Garment Design (Sig 11) –Physics-Inspired Upsampling for Cloth Simulation in Games

4. Authors Uldarico Muico ?

5. Motivation Natural responses to certain disturbances – a single motion trajectory (traditional) –composite controllers that track multiple trajectories –Motion recovery

6. Contributions A trajectory tracking control framework Learn a control policy over a rich set of motions Combine these ideas cohesively in an interactive control setting

7. Related work State-based spring-damper systems –A broad set of skills –Hodgins et al. 1995; Hodgins and Pollard 1997;Wooten and Hodgins 2000; Faloutsos et al. 2001; Yin et al. 2007; Coros et al. 2008 Reproduce motion trajectories within simulations –Laszlo et al. 1996; Zordan and Hodgins 2002; –Indistinguishable from motion capture

8. Character model

9. Control system An example –a controller forwalking straight ahead – a controller for stepping sideways

10. Create controller System Dynamics Trajectory tracking Composite Trajectory Tracking Constrained Control Contact Adaptation

11. Motion graph

12. Slope tests Horizontal: slope angle (a): composited a faster motion (b): composited a slower motion Ordinate: walk speed (c): composited motions in (a) and (b) Horizontal: slope angle Ordinate: walk speed (a): composited a faster motion (b): composited a slower motion (c): composited motions in (a) and (b) (a): composited a faster motion (b): composited a slower motion

13. Pushing tests Horizontal: force Ordinate: walk speed (c): composited motions in (a) and (b) (a): composited a faster motion (b): composited a slower motion

15. Authors Kevin Wampler ? Evan Herbst Yongjoon Lee Erik Andersen ?? Yongjoon Lee ?

16. Motivation Intelligent real-time controller Game theory and long-term planning

17. Related work Character controller –Turn-based framework, e.g. tic-tac-toe –Randomized actions set, Lee and Lee [2006] Reinforcement learning –generate intelligent single-character behavior –Ikemoto et al. [2005]

18. Motion model Parametric Motion Graph (PMG) [Heck and Gleicher 2007] –Allow simultaneous actions –Compact parameterized –Game state(node, time, parameters)

19. Markov game Stateless Games –E.g. rock-paper-scissors –Reward matrix –Policy vector –Linear Program

20. Games With State

21. Conclusion Control characters Game theory Precompute a value function A runtime controller

22. Limitations Cannot be applied to all possible games – two-player games

24. Authors Sergey LevineYongjoon Lee ? Vladlen Koltun ?

25. Motivation Characters traverse complex dynamic environments A space-time planner

26. Sample landmarks

27. Locomotion controllers Jumping Obstacle avoidance Corner

28. Space-time planning

29. Conclusion The first of its kind for planning animations for virtual character Ability of traversing complex, highly dynamic environments. Generate high-quality animations from a large body of motion capture.

31. Authors Stelian CorosAndrej KarpathyBenjamin JonesLionel ReveretMichiel van de Panne ?

32. Contributions Several abstractions –a dual leg frame model –a flexible abstracted spine –the extensive use of internal virtual forces A flexibly parameterized jump Creation of gaits –walk, trot, pace, canter, and transverse and rotary gallop

33. Quadruped model

34. Controller overview

35. Gaits Gait graphs

36. Virtual forces Virtural forces controller

37. Gait optimization Motion capture data

38. Limitations Lack of self collisions Motions of the head and tail are not modeled A simple model of the feet

40. Authors Jie TanGreg TurkC. Karen Liu Yuting Gu ?

41. Contribution A general approach to creating realistic swimming behavior

42. Related Work Articulated Figure Control –Swimming trajectory –Optimization techniques Solid-Fluid Coupling –Combine creature’s motions and fluid Simulated Swimmers –Move the body parts of an articulated figure

43. Articulated Rigid Body Simulation Modified Proportional-Derivative Controller –a framework to compute control forces for tracking a kinematic state of a joint trajectory –Tan et al. [2011]

44. Fluid Simulation Use the inviscid, incompressible fluid equations Coupling Articulated Figures with Fluids

45. Path Following turning maneuvers

46. Limitations soft-body creatures

48. Author Aleka McAdamsYongning ZhuAndrew Selle Eftychios Sifakis ?

49. Goal Near-interactive simulation of skeleton driven Soft tissue deformation for character animation

50. Algorithm Discretization

51. Algorithm Corotational linear elasticity model –energy density function

52. Results

55. Author Nobuyuki UMETANI Danny M. KaufmanTakeo IgarashiEitan Grinspun

56. Motivation Interactive tool for garment design bidirectional editing between 2D and 3D

57. Related Work Sketch-Based Design Cloth Simulation Interactive Cloth Design and Simulation Design Sensitivity Analysis

58. Interaction Tools Curve edits Darts Sewing/pleating Symmetry Sloper parameters

59. Sloper templates

60. Results

61. Thanks !