I'm using an octree of axis aligned bounding boxes to segment the space in my scene where I do a physics simulation.The problem is, the scene is very large(space) and I need to detect collision of large objects at large distances as well as small objects at close distances.The thing is, there are only a few of them on the scene, but kilometers apart, so this means a lot of empty space.So basically I'm wasting 2 gigs of RAM to store bounding boxes for empty sectors.I'd like to only allocate memory for the sectors that actually contain something(to have them be pointers to AABBs), but that would mean thousands of allocations each frame to re-create the octree.If I use a pool to counter the slowdown from allocations it would still mean I'm allocating 2 gigs of RAM for my application.Is there any other way to achieve this?
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1How exactly do you arrive at 2GB with only a few objects? – n. m. could be an AI Mar 03 '13 at 17:19
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the 2 GB is from having millions of AABBs in the octree – ulak blade Mar 03 '13 at 17:33
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Look into Loose Octrees (for dealing with many objects) or a more adaptive system such as AABB-trees built around each object rather than one for the entire space. You can perform general distance/collision using the overall AABB (the root) and get finer collisions using the tree under each object (and eventually a ray-triangle intersection test if you need that fine a resolution). The only disadvantage with AABB-trees is that if the object rotates you need to rebuild the tree (you can adaptively scale and translate the AABB-tree).
Robert Templeton
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