Game Physics

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Game Physics. Chris Miles. The Goal. To learn how to create game objects with realistic physics models To learn how to simulate aspects of reality in order to make them behave more realistically. Overview. Newton’s laws Data types Particle implementation Rigid body implementation. - PowerPoint PPT Presentation

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Game Physics

Chris Miles

The Goal

To learn how to create game objects with realistic physics models

To learn how to simulate aspects of reality in order to make them behave more realistically

Overview

Newton’s laws Data types Particle implementation Rigid body implementation

Newton’s Laws of Motion

1. Inertia

2. F = ma

3. Equal and opposite

How They Apply

Velocity remains constant unless acted on by a force.

Objects accelerate via f = ma

Interactions between objects should affect both similarly

How They Don’t Apply

1. Velocities that reduce over time give better numerical stability

2. Objects are often moved instantaneously

3. Many interactions are one-sided, there is no reason to simulate the other side.

An Object – Rigid Body

An object that moves but does not change shape

“Mass properties” define how these objects are affected by forces

1. Mass

2. Moment of inertia

3. Center of gravity

Simulation

We want to write a simulation describing the motion of the object

look at the universe after 1 second, 2 seconds, so on and so on.

integrate the equations of motion between those steps

Data Types

Scalar Vector Matrix Quaternion Euler Angles Rotation Matrix Tensor

Scalars

Scalars are a single number

They represent simple characteristics, such as mass

Vectors

[2,5] [1,5,17] [-.14,5,-7]

Vectors usually represent a location, both in world and local space

Quaternion

Quaternion’s contain an orientation Explaining how they work is long and fruitless Know that they hold an orientation in some

undecipherable way Can quickly rotate vectors, cumulate easily, and

interpolate smoothly Used by virtually every modern game engine

(Laura Croft gets points for pioneering)

Particles

First we will look at particles, which are a reduced form of Rigid Bodies

Particles differ in that they do not have orientation, they just have positions

Euler angles

What quaternions were developed to replace Vector containing rotations around x,y,z Suffers from gimbal lock - makes it impossible to

go from some orientations to others in a single step

Interpolates poorly - very ugly animations / camera movement

Understandable

Rotation matrixes

Another alternative to quaternions Too large, requires 9 variables vs. 4 Numerically unstable – unnormalizes over

time Slower

Tensor

Don’t worry about them, math term Generalization of scalars/vectors/matrix’s Scalars are rank 0 tensor, vectors 1,

matrix’s 2 Concerned with rank 2 tensors, for

moment of inertia Can also accurately simulate drag

Particle Class Definition

Class Particle– vector position– vector velocity– vector resultantForce– scalar mass– Function Integrate( dtime ) – Called every time step to update position

Function Integrate( dtime )

//dtime = how much time has passed in this time step

position += velocity * dtime

velocity += force / mass

force = 0

Improvements

Violate law #1, have velocities slowly decrease – greatly increases numerical stability

Original: – velocity += force / mass * dtime

New: – velocity += (force/mass – velocity*cf)* dtime

cf should be a coefficient of on the order of .999 or so

Implicit Integration

We are doing explicit (forward) euler integration so far in our modeling.

If stability is an issue you can use implicit integration

http://www.mech.gla.ac.uk/~peterg/software/MTT/examples/Simulation_rep/node89.html is a good overview

Runge-Kutta

Precise integration technique

Sample several times for each time step. t = 0, t = .25, t = .5, t = .75 to find value at t = 1

Provides very accurate results

http://mathworld.wolfram.com/Runge-KuttaMethod.html

Rigid Body

Position and Orientation

Linear and Angular movements are independent and analagous

Rigid Body Class Definition

Class RigidBody– vector position– vector velocity– vector resultantForce– scalar mass

– quaternion orientation– vector rotationalVelocity– vector resultantTorque– tensor momentOfInertia

– Function Integrate( dtime )

Moments of Inertia

The moment of inertia is the rotational equivalent to mass, it describes how hard an object is to rotate

Depends on the axis of rotation so it is a tensor, mapping from a direction to a magnitude

3x3 matrix

Just using a simple scalar in this example7

Calculating Moments of Inertia

Producing the values that go inside the moment of inertia is non trivial.

Assign point masses to the object, representing where things are distributed

Then Σmr2

Ideal Integrate function

position += velocity * dtimevelocity += force / mass * dtimeforce = 0

orientation += rotationalVelocity * dtimerotationalVelocity += torque / momentOfInertia *

dtimetorque = 0

Complications

Quaternion operators are odd so to add rotationalVelocity

from– orientation += rotationalVelocity * dtime

to– o += (rv * o) / 2.0f * dtime;

Point Forces

To calculate the torque caused by point forces

Use the vector cross product force X position = torque Where position is the vector from the

center of gravity to the point

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