A physics engine in computer games takes charge of the calculations simulating the physical world. In this paper, we evaluate the performance of three numerical integral methods: Euler method, Improved Euler method, and Runge-Kutta method. We utilized a car moving game for the simulation experiments logging fps (frame per second). Each numerical integral was evaluated under two different settings, one with collision detection and the other without it. The simulation environment without collision detection was divided into two sections, a uniform velocity section and a variable velocity section. The Euler method was shown to have the best fps in the simulation environment with collision detection. Simulation with collision detection shows similar fps for all three methods and the Runge-Kutta method showed the greatest accuracy. Since we tested with rigid bodies only, we are currently studying efficient numerical integral methods for soft body objects.
[1]
A. Jameson,et al.
Improvements to the aircraft Euler method
,
1987
.
[2]
Gabriel Zachmann,et al.
Minimal hierarchical collision detection
,
2002,
VRST '02.
[3]
Gordon S. Novak,et al.
Representation of models for solving real-world physics problems
,
1990,
Sixth Conference on Artificial Intelligence for Applications.
[4]
Klaus Mueller,et al.
Evaluation and Design of Filters Using a Taylor Series Expansion
,
1997,
IEEE Trans. Vis. Comput. Graph..
[5]
H. Munthe-Kaas.
High order Runge-Kutta methods on manifolds
,
1999
.
[6]
Laxmikant V. Kalé,et al.
A voxel-based parallel collision detection algorithm
,
2002,
ICS '02.