Ammo.js Performance: Spheres vs Complex Box Shapes

When building 3D physics simulations on the web using ammo.js—the Emscripten port of the Bullet physics engine—choosing the right collision shapes is critical for maintaining high frame rates. This article analyzes the performance differences between mathematically simple sphere shapes and complex box or compound shapes, explaining why spheres are significantly faster to calculate and how shape selection impacts the physics engine’s collision detection phases.

Mathematical Simplicity of Spheres

The primary reason sphere shapes outperform all other collision shapes in ammo.js lies in the mathematics of collision detection. To determine if two spheres are colliding, the physics engine only needs to calculate the distance between their center points and compare it to the sum of their radii.

This calculation requires a simple distance formula: \[d = \sqrt{(x_2-x_1)^2 + (y_2-y_1)^2 + (z_2-z_1)^2}\]

If the squared distance is less than the squared sum of the radii, a collision has occurred. This avoids expensive square root calculations during initial checks, making sphere-to-sphere collision detection incredibly lightweight and computationally cheap.

The Complexity of Box Shapes

While a simple Axis-Aligned Bounding Box (AABB) is relatively fast to calculate, complex box shapes—such as Oriented Bounding Boxes (OBBs), skewed boxes, or compound shapes made of multiple boxes—require significantly more CPU overhead.

To detect collisions between complex or rotated boxes, ammo.js must employ algorithms like the Separating Axis Theorem (SAT). This process involves: * Projecting the vertices of both shapes onto up to 15 potential separating axes. * Checking for overlaps on every single axis. * Calculating precise contact points, normals, and penetration depths when an overlap is found.

As the complexity of the box shapes or the number of grouped boxes in a compound shape increases, the number of mathematical operations required to resolve a single collision grows exponentially.

Impact on Broadphase and Narrowphase CPU Cycles

Ammo.js processes collisions in two main steps: the broadphase and the narrowphase.

1. Broadphase: The engine uses simple bounding boxes (AABBs) to quickly eliminate pairs of objects that are nowhere near each other. At this stage, the actual shape of the object matters very little.
2. Narrowphase: For the remaining object pairs that might be colliding, the engine performs exact shape-to-shape intersection tests.

This narrowphase is where the performance gap widens. If your scene contains hundreds of active rigid bodies, using complex box shapes will saturate the CPU during the narrowphase. Conversely, using sphere shapes allows the narrowphase solver to resolve contact points almost instantly, freeing up vital CPU cycles for rendering and game logic.

Practical Recommendations for Performance

To optimize your ammo.js physics simulation, apply the following shape selection strategies:

• Use Spheres as Proxies: Whenever possible, represent complex objects with sphere colliders. Even if an asset is not perfectly spherical, a sphere approximation is often close enough for gameplay purposes.
• Use Capsules for Characters: For upright characters or projectiles, use capsule shapes (which are mathematically treated as swept spheres) rather than boxes.
• Limit Compound Boxes: Only use complex boxes or compound shapes for static environment geometry, where the shapes do not need to be updated or solved against other complex moving shapes dynamically.