What is an AABB tree?

What is an AABB tree?

AABBTree is a pure Python implementation of a static d-dimensional axis aligned bounding box (AABB) tree. It is inspired by Introductory Guide to AABB Tree Collision Detection from Azure From The Trenches. Left: An AABB tree, leaves numbered by insertion order. Right: The AABBs and their bounding boxes.

What is the difference between AABB and OBB?

AABB – is Axis-Aligned Bounding Box. OBB – Oriented Bounding Box. Those are well established computer science terms. The difference is pretty simple – AABB is not rotated, OBB can be rotated.

What is AABB in Python?

Provides functions to calculate and manipulate Axis-Aligned Bounding Boxes (AABB). AABB are a simple 3D rectangle with no orientation. It is up to the user to provide translation. An AABB is represented by an array of 2 x 3D vectors.

How do you make an AABB tree?

Create a new branch node for the located node and the new leaf and assign it an AABB that contains both nodes (essentially combine the AABBs of the two located node and the new leaf). Attach the new leaf to the new branch node. Remove the existing node from the tree and attach it to the new branch node.

When should I use AABB collision detection?

If you have an object that is axis-aligned, ie. not rotated and doesn’t need tight collision detection then AABB collision detection is the route you are going to want to take.

How to detect collision between two AABB (axis-aligned bounding box)?

An example showing how to detect collision between two AABB (Axis-Aligned Bounding Box) in 2D (uses HTML5/JS). Two rectangles that are [XY] axis aligned do not collide if they are separated along an axis. If they overlap on both axes then they collide.

What is AABB and how does it work?

What is AABB? An AABB is an axis aligned bounding box. AABB vs AABB is a box vs box or bounding box collision detection. It’s mainly used in broadphase physics detection.

What is AABB in 3D modeling?

2 Answers 2. AABB stands for “Axis-Aligned Bounding Box.”. It is a fairly computationally- and memory-efficient way of representing a volume, typically used to see if two objects might be touching. Since it is axis-aligned, it does not necessarily “fit” your real 3D object very well.