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Integration for physically based animation CSE 3541 Matt Boggus.

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Presentation on theme: "Integration for physically based animation CSE 3541 Matt Boggus."— Presentation transcript:

1 Integration for physically based animation CSE 3541 Matt Boggus

2 What is motion? Observe an object’s position over time We could say y = f(time)

3 Equations of motion – terms Position (x,y,z) – Point with respect to the origin Velocity (x,y,z) – Speed (vector magnitude) – Direction Acceleration (x,y,z) – Rate of change of velocity – Magnitude and direction r

4 Equations of motion graph examples Initial conditions: – p = 0, v = 5 If we have the function for acceleration, we can integrate it and use initial conditions to solve for the velocity and position functions acceleration velocity position

5 Euler integration For arbitrary function f(t) with known derivative Step in the direction of the derivative

6 Integration – derivative field For arbitrary function, f(t) The force acting on a point may vary in space

7 Sampling A fixed amount of time passes between frames. Approximate the continuous position curve with discrete samples.

8 Integration and step size

9 Inaccuracy and instability

10 Runge Kutta Integration: 2 nd order aka Midpoint Method Compute a “full” Euler step Evaluate f at midpoint Take a step from the original point using the midpoint f value

11 Runge Kutta Integration: 2 nd order aka Midpoint Method For unknown function, f(t); known f ’(t)

12 Step size Euler Integration Midpoint Method

13 Integration comparison Image from http://www.physics.drexel.edu/students/courses/Comp_Phys/Integrators/simple.html


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