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1 Physics for Games Programmers Problem Overview Squirrel Eiserloh Technical Director MumboJumbo Games

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2 Types of Problems Knowing when to cheat Simplifying things Giving shape to things Moving things around Simulation baggage Detecting (and resolving) collisions Sustained interactions Dealing with the impossible Making it fast enough

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3 Knowing When To Cheat

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4 Knowing When to Cheat Discrete physics simulation falls embarrassingly short of reality. Real physics is prohibitively expensive......so we cheat. We need to cheat enough to be able to run in real time. We need to not cheat so much that things break in a jarring and unrecoverable way. Much of the challenge is knowing how and when to cheat.

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5 Knowing When to Cheat Ask: Will the player notice? Will the player care? Will the results be predictable? Are we at least cheating in a consistent way? Will the simulation break? If the simulation breaks, they will notice and they will care Some crimes are greater than others

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6 Simplifying Things

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7 Simplified bodies

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8 Simplifying Things Simplified bodies Even more simplified bodies

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9 Simplifying Things Simplified bodies Even more simplified bodies Convex bodies

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10 Simplifying Things Simplified bodies Even more simplified bodies Convex bodies Homogeneous bodies

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11 Simplifying Things Simplified bodies Even more simplified bodies Convex bodies Homogeneous bodies Rigid bodies

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12 Simplifying Things Simplified bodies Even more simplified bodies Convex bodies Homogeneous bodies Rigid bodies Indestructible bodies

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13 Simplifying Things Movement is often assumed to be in a vacuum (ignoring air resistance)

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14 Simplifying Things Movement is often assumed to be in a vacuum (ignoring air resistance) Even when air resistance does get simulated, it is hugely oversimplified

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15 Simplifying Things Collisions are often assumed to be perfect and elastic That is, 100% of the energy before the collision is maintained after the collision Think billiard balls

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16 Giving Shape to Things

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17 Giving Shape to Things N-sphere 2d: Disc 3d: Sphere

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18 Giving Shape to Things N-sphere 2d: Disc 3d: Sphere Simplex 2d: Triangle 3d: Tetrahedron

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19 Giving Shape to Things N-sphere 2d: Disc 3d: Sphere Simplex 2d: Triangle 3d: Tetrahedron Convex Polytope 2d: Convex Polygon 3d: Convex Polyhedron a.k.a. Convex Hull a.k.a. Brush (Quake)

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20 Giving Shape to Things Discrete Oriented Polytope (DOP)

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21 Giving Shape to Things Discrete Oriented Polytope (DOP) Oriented Bounding Box (OBB)

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22 Giving Shape to Things Discrete Oriented Polytope (DOP) Oriented Bounding Box (OBB) Axis-Aligned Bounding Box (AABB)

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23 Giving Shape to Things Discrete Oriented Polytope (DOP) Oriented Bounding Box (OBB) Axis-Aligned Bounding Box (AABB) Capsule

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24 Giving Shape to Things Discrete Oriented Polytope (DOP) Oriented Bounding Box (OBB) Axis-Aligned Bounding Box (AABB) Capsule Cylinder (3d only)

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25 Moving Things Around

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26 Moving Things Around Kinematics Describes motion Uses position, velocity, momentum, acceleration

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27 Moving Things Around Kinematics Describes motion Uses position, velocity, momentum, acceleration Dynamics Explains motion Uses forces...and impulses

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28 Moving Things Around Kinematics Describes motion Uses position, velocity, momentum, acceleration Dynamics Explains motion Forces (F=ma) Impulses Rotation Torque Angular momentum Moment of inertia

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29 Moving Things Around How to compute the next position and velocity from current position and velocity? This process is called integration; An algorithm for doing this in an integrator

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30 Moving Things Around How to compute the next position and velocity from current position and velocity? This process is called integration; An algorithm for doing this in an integrator

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31 Moving Things Around How to compute the next position and velocity from current position and velocity? This process is called integration; An algorithm for doing this in an integrator

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32 Moving Things Around How to compute the next position and velocity from current position and velocity? This process is called integration; An algorithm for doing this in an integrator

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33 Moving Things Around How to compute the next position and velocity from current position and velocity? This process is called integration; An algorithm for doing this in an integrator

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34 Moving Things Around How to compute the next position and velocity from current position and velocity? This process is called integration; An algorithm for doing this in an integrator Which integration method to use?

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35 Moving Things Around How to compute the next position and velocity from current position and velocity? This process is called integration; An algorithm for doing this in an integrator Which integration method to use?

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36 Moving Things Around How to compute the next position and velocity from current position and velocity? This process is called integration; An algorithm for doing this in an integrator Which integration method to use?

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37 Moving Things Around How to compute the next position and velocity from current position and velocity? This process is called integration; An algorithm for doing this in an integrator Which integration method to use?

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38 Moving Things Around How to compute the next position and velocity from current position and velocity? This process is called integration; An algorithm for doing this in an integrator Which integration method to use?

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39 Simulation Baggage

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40 Simulation Baggage Flipbook syndrome

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41 Simulation Baggage Flipbook syndrome Things can happen in-between snapshots

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42 Simulation Baggage Flipbook syndrome Things mostly happen in-between snapshots

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43 Simulation Baggage Flipbook syndrome Things mostly happen in-between snapshots Curved trajectories treated as piecewise linear

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44 Simulation Baggage Flipbook syndrome Things mostly happen in-between snapshots Curved trajectories treated as piecewise linear Terms often assumed to be constant throughout the frame

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45 Simulation Baggage (contd) Error accumulates

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46 Simulation Baggage (contd) Error accumulates Energy is not always conserved Energy loss can be undesirable Energy gain is evil Simulations explode!

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47 Simulation Baggage (contd) Error accumulates Energy is not always conserved Energy loss can be undesirable Energy gain is evil Simulations explode! Rotations are often assumed to happen instantaneously at frame boundaries

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48 Simulation Baggage (contd) Error accumulates Energy is not always conserved Energy loss can be undesirable Energy gain is evil Simulations explode! Rotations are often assumed to happen instantaneously at frame boundaries Numerical nightmares!

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49 Collision Detection

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50 Collision Detection We need to determine if A and B intersect

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51 Collision Detection We need to determine if A and B intersect Worse yet, they could be (and probably are) in motion

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52 Collision Detection We need to determine if A and B intersect Worse yet, they could be (and probably are) in motion If they did collide, we probably also need to know when they collided

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53 Collision Response...and we need to figure out how to resolve the collision

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54 Sustained Interactions

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55 Sustained Interactions Surface contact

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56 Sustained Interactions Surface contact Edge contact

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57 Sustained Interactions Surface contact Edge contact Contact points Different solutions

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58 Sustained Interactions Surface contact Edge contact Contact points Different solutions

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59 Sustained Interactions Surface contact Edge contact Contact points Different solutions Stacking

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60 Sustained Interactions Surface contact Edge contact Contact points Different solutions Stacking Friction Static & Kinetic

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61 Sustained Interactions Surface contact Edge contact Contact points Different solutions Stacking Friction Static & Kinetic Constraints & Joints

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62 Dealing With the Impossible

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63 Dealing With the Impossible Interpenetration

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64 Dealing With the Impossible Interpenetration Tunneling

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65 Dealing With the Impossible Interpenetration Tunneling

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66 Dealing With the Impossible Interpenetration Tunneling

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67 Dealing With the Impossible Interpenetration Tunneling

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68 Tunneling (Sucks)

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69 Tunneling Small objects tunnel more easily

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70 Tunneling (contd) Possible solutions Minimum size requirement? Inadequate; fast objects still tunnel

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71 Tunneling (contd) Fast-moving objects tunnel more easily

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72 Tunneling (contd) Possible solutions Minimum size requirement? Inadequate; fast objects still tunnel Maximum speed limit? Inadequate; since speed limit is a function of object size, this would mean small & fast objects (bullets) would not be allowed Smaller time step? Helpful, but inadequate; this is essentially the same as a speed limit

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73 Tunneling (contd) Besides, even with min. size requirements and speed limits and a small timestep, you still have degenerate cases that cause tunneling!

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74 Tunneling (contd) Besides, even with min. size requirements and speed limits and a small timestep, you still have degenerate cases that cause tunneling!

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75 Tunneling (contd) Besides, even with min. size requirements and speed limits and a small timestep, you still have degenerate cases that cause tunneling!

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76 Tunneling (contd) Besides, even with min. size requirements and speed limits and a small timestep, you still have degenerate cases that cause tunneling!

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77 Tunneling (contd) Tunneling is very, very bad – this is not a mundane detail Things falling through world Bullets passing through people or walls Players getting places they shouldnt Players missing a trigger boundary

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78 Tunneling (contd) Interpenetration Tunneling Rotational tunneling

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79 Making It Fast Enough

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80 Making It Fast Enough Dont be too particular too soon Avoid unnecessary work

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81 Making It Fast Enough Dont be too particular too soon Avoid unnecessary work Eschew n-squared operations Avoid the everything vs. everything case

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82 Making It Fast Enough Dont be too particular too soon Avoid unnecessary work Eschew n-squared operations Avoid the everything vs. everything case Try using simulation islands and space partitioning to divide and conquer

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83 Simulation Islands Consider: 1000 objects, 1 island 1000x1000 checks = 1 Million checks

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84 Simulation Islands Consider: 1000 objects, 1 island 1000x1000 checks = 1 Million checks Verses: 1000 objects, divided into 10 islands of x (100x100) checks = 100,000 checks 1/10 th as many!

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85 Simulation Islands Simulation islands can go to sleep when they become stable i.e. when forces and motion remain unchanged

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86 Simulation Islands Simulation islands can go to sleep when they become stable i.e. when forces and motion remain unchanged

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87 Simulation Islands Simulation islands can go to sleep when they become stable i.e. when forces and motion remain unchanged When an object enters the islands bounds...

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88 Simulation Islands Simulation islands can go to sleep when they become stable i.e. when forces and motion remain unchanged When an object enters the islands bounds...

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89 Simulation Islands Simulation islands can go to sleep when they become stable i.e. when forces and motion remain unchanged When an object enters the islands bounds......the island wakes up

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90 Simulation Islands Add the newcomer to this simulation island

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91 Simulation Islands Add the newcomer to this simulation island...and put it back to sleep once it stabilizes This is just one of many ways to reduce complexity Well be covering several others later on

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92 Making It Fast Enough Can also exploit work previously done Make educated assumptions using: Temporal / frame coherence: Things tend not to have changed a whole lot in the 15ms or so since the previous frame, so save the previous frames results! Spatial coherence: Things tend to miss each other far more often than they collide, and only things in the same neighborhood can collide with each other

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93 Summary

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94 Summary The nature of simulation causes us real problems... problems which cant be ignored So we cheat And we simplify things And even then, it can get quite complex...

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95 Summary (contd) Problems were concerned with: How should we choose to represent physical bodies? How should we simulate and compute motion? How can we prevent energy build-up? How do we cope with floating point error? How can we detect collisions – especially when large numbers of objects are involved? How can we prevent tunneling? How should we resolve penetration? How should we handle contact? How do we deal with non-rigid bodies? How can we relieve CPU burden?

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96 Questions? Feel free to reach me by at:

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