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A Ragdoll-less Approach To Physics Animations of Characters In Vehicles
- 1. A RAGDOLL-LESS APPROACH TO PHYSICAL ANIMATIONS OF CHARACTERS IN VEHICLES © 2019 SIGGRAPH. ALL RIGHTS RESERVED.1
- 3. © 2019 SIGGRAPH. ALL RIGHTS RESERVED. HYOJONG SHIN EXPERT ANIMATION PROGRAMMER Ubisoft Reflections Expert Animation Programmer at Ubisoft and currently doing R&D for Physics-based Procedural Animation. Previously he was involved in developing Unreal Engine 4 at Epic Games and in-house physics engines at NAMCO BANDAI Games. His first job was on developing PC online games. After that, he completed his master’s degree in Computer Science at The University of Tokyo and worked in the simulation industry. He was in charge of developing real-time fluid simulation engines which eventually facilitated him entering the game industry again. Throughout his experiences, his interests have shifted to combining physics and animations.
- 4. Follow Target Poses with Physics- based Procedural Solutions / MAIN GOALS Self-Balanced Character to reduce Authored Animations
- 6. /ACTIVE RAGDOLL ? Just Cause 2 Uncharted 4 GDC 2010: Physics Meets Animation : Character Stunts in Just Cause 2 GDC 2017 : Physics Animation in 'Uncharted 4: A Thief's End'
- 7. /COMPLICATIONS A bunch of vehicles — Need to be stable with few animations Complicated setups — Ragdoll setups / many gains Seen through car window — Need to be exaggerated Characters inside vehicle is not high priority — Computing cost
- 8. /GOALS Unconditionally Stable Intuitive and Less control parameters — No ragdoll setup — Understandable Range ( i.e. > 0.0 ~ 1.0 , 0 ~ 100 ) Independent of frameworks — Should be easy to port to other game engines Computing Cost — Should be cheap considering even for Mobile Platforms
- 9. /RESULTS Animations are a bit exaggerated to show the difference clearly
- 10. IMPLEMENTATION
- 12. /FIRST STEP Simplify spine movement Apply Position-Based Dynamics to only spine chain Post-process After Vehicle Simulation IK for hands
- 13. /PARTICLE DYNAMICS Consider each bone as a particle Each particle moves independently Fix the root bone to a vehicle — Root bone completely follows the target
- 14. /BASIC IDEA 14
- 15. /BASIC IDEA 15
- 16. /BASIC IDEA 16
- 17. /BASIC IDEA 17
- 18. /BASIC IDEA 18
- 19. /BASIC IDEA 19
- 22. /DISTANCE CONSTRAINTS 22 Solved in only one step Doesn’t need iteration
- 23. /MODIFY ORIENTATIONS Adjust each bone’s orientation
- 24. /TIME INTEGRATION Move particles with their velocities Should follow the target position How can we compute velocity?
- 25. /MESHLESS DEFORMATIONS Meshless Deformations Based on Shape Matching[ Muller et al. 2005]
- 26. /VELOCITY COMPUTATION Added Damping Coefficient 𝛼 : stiffness parameter 𝒗𝑖(𝑡 + ℎ) = 𝛼 𝒈𝑖 𝑡 − 𝒙𝑖 𝑡 ℎ + 1 − 𝛼 𝒗𝑖(𝑡) Restoration term
- 27. /VELOCITY COMPUTATION Added Damping Coefficient 𝛼 : stiffness parameter If 𝛼 is 1.0, completely solid 𝒗𝑖(𝑡 + ℎ) = 𝛼 𝒈𝑖 𝑡 − 𝒙𝑖 𝑡 ℎ + 1 − 𝛼 𝒗𝑖(𝑡)
- 28. /VELOCITY COMPUTATION Added Damping Coefficient 𝛼 : stiffness parameter If 𝛼 is 1.0, completely solid If 𝛼 is 0.0, no recovery impulse 𝒗𝑖(𝑡 + ℎ) = 𝛼 𝒈𝑖 𝑡 − 𝒙𝑖 𝑡 ℎ + 1 − 𝛼 𝒗𝑖(𝑡)
- 29. /INTUITIVE PARAMETERS Stiffness : 0.0 ~ 1.0 Component-based Stiffness — Forward-Backward direction — Left-Right direction — Up-Down direction Regardless of a value, It ends up following the reference pose
- 31. /JUMP! Apply dynamics to Hip / Pelvis bone From Fixed to Movable
- 32. /EXTEND TO LEGS Not simply solved Need to satisfy all chains — Not solved in one step
- 33. /FABRIK Forward And Backward Reaching Inverse Kinematics
- 34. /HIP MOVEMENT Animations are quite exaggerated to show the hip movements clearly
- 35. /DEVIATION End bone’s Stiffness Interpolate middle bones’ weight Or use weight curve 1.0 α 0.8 α
- 36. /EXAMPLE
- 37. /ANGULAR CONSTRAINTS Cone constraint — Project to 2D-plane — Just compare X )𝜃 𝜃
- 38. POSE MODIFIER
- 39. /MODIFY TARGET POSES Key-framed Animation Physics Bone Controller Modify Target Reference Poses
- 40. /WHY DO WE NEED THIS? Unnatural on slopes or uneven terrains Solve without additional animations Anti-gravity / Counter-balance
- 41. /EXAMPLE 42
- 42. /BALANCING ZMP ( Zero Moment Point ) 43 Right Foot Left Foot Center Of Mass Comfort Zone
- 43. /BALANCING 𝑣 : velocity of COM 44 V
- 44. /LINEAR MOMENTUM 𝑃 = 𝑖=0 𝑛 𝑚𝑖 𝒗𝑖 𝑃 = 𝑀𝑽 𝑝 = 𝑚𝑣 𝑀 : Total sum of masses 𝐹−1
- 45. /MOVING COM 48
- 46. /MOVING COM 49
- 48. /REALITY 51
- 49. /NEED ONE MORE CONDITION 52 Fix feet positions
- 50. /POSITION CONDITIONS IK Solver — Jacobian Pseudo-Inverse Velocity-based concept ሶ𝒓 = 𝑱 𝑣 ሶ𝜽 𝑱 = 𝜕𝒓 𝜕𝜽 ሶ𝒓 フルボディIKエンジンの作り方(How to make Full-body IK Engne) – Tsuda, CEDEC 2011
- 52. /COMBINE WITH BALANCE CONDITION Consider COM ( Center Of Mass ) Construct Jacobian with COM condition ሶ𝑟 𝑀𝑉 = 𝐽𝑣 𝐽 𝑚 ሶ𝜃 = 𝐽 ሶ𝜃 𝑃 = 𝑀𝑉 = 𝐽 𝑚 ሶ𝜃 フルボディIKエンジンの作り方(How to make Full-body IK Engne) – Tsuda, CEDEC 2011
- 54. /BALANCING
- 55. /SITTING POSE
- 56. /ASSUMPTIONS Assuming keyframed COM is correct
- 57. /BALANCING ON THE SIDE OF A VEHICLE
- 58. /MIX WITH PHYSICS - MOVEMENT ON A BOAT This character has only one key-pose
- 59. /CLINGING ON THE SIDE OF A TRUCK This character has only one idle animation
- 60. /STANDING ON A TRUCK This character has only one idle animation
- 61. /CONCLUSIONS Works with few poses Not focusing on high quality but More efficient — Intuitive and less parameters Robust and stable — Imagine you need to check up hundreds of vehicles Computing cost is cheap Engine agnostic
- 62. ? QUESTIONS