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Space Debris Collision Detection using Reachability

11 pagesPublished: September 17, 2018


Benchmark Proposal: Space debris tracking and collision prediction is a growing world- wide problem as more and more objects are placed into orbit. While traditional methods simulate particles with Gaussian uncertainty to make collision predictions, we instead ana- lyze the problem from a reachability perspective. The problem appears to require methods capable of quickly analyzing high-dimensional nonlinear systems, but we take advantage multiple kinds of problem structure to show that reachability analysis may be viable for this problem. In particular we present an initial analysis approach that uses numerical simulation for reachability analysis, and interval arithmetic with AABB trees for fast col- lision detection. The analysis uses a variable size time step with a counter-example guided abstraction refinement (CEGAR) method to increase analysis speed without sacrificing accuracy. Our approach can analyze upwards of thousands of orbiting objects faster than real-time, where each object is subject to some initial state uncertainty.

Keyphrases: AABB Trees, CEGAR, collision detection, orbital dynamics, reachability

In: Goran Frehse (editor). ARCH18. 5th International Workshop on Applied Verification of Continuous and Hybrid Systems, vol 54, pages 218--228

BibTeX entry
  author    = {Kerianne Hobbs and Peter Heidlauf and Alexander Collins and Stanley Bak},
  title     = {Space Debris Collision Detection using Reachability},
  booktitle = {ARCH18. 5th International Workshop on Applied Verification of Continuous and Hybrid Systems},
  editor    = {Goran Frehse},
  series    = {EPiC Series in Computing},
  volume    = {54},
  pages     = {218--228},
  year      = {2018},
  publisher = {EasyChair},
  bibsource = {EasyChair,},
  issn      = {2398-7340},
  url       = {},
  doi       = {10.29007/5313}}
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