1 research outputs found
Efficient n-to-n Collision Detection for Space Debris using 4D AABB Trees (Extended Report)
Collision detection algorithms are used in aerospace, swarm robotics,
automotive, video gaming, dynamics simulation and other domains. As many
applications of collision detection run online, timing requirements are imposed
on the algorithm runtime: algorithms must, at a minimum, keep up with the
passage of time. In practice, this places a limit on the number of objects, n,
that can be tracked at the same time. In this paper, we improve the scalability
of collision detection, effectively raising the limit n for online object
tracking.
The key to our approach is the use of a four-dimensional axis-aligned
bounding box (AABB) tree, which stores each object's three-dimensional
occupancy region in space during a one-dimensional interval of time. This
improves efficiency by permitting per-object variable times steps. Further, we
describe partitioning strategies that can decompose the 4D AABB tree search
into several smaller-dimensional problems that can be solved in parallel. We
formalize the collision detection problem and prove our algorithm's
correctness. We demonstrate the feasibility of online collision detection for
an orbital space debris application, using publicly available data on the full
catalog of n=16848 objects provided by www.space-track.org