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Anytime computation algorithms for approach-evasion differential games

Authors
  • Mueller, Erich
  • Zhu, Minghui
  • Karaman, Sertac
  • Frazzoli, Emilio
Type
Preprint
Publication Date
Sep 27, 2013
Submission Date
Aug 05, 2013
Identifiers
arXiv ID: 1308.1174
Source
arXiv
License
Yellow
External links

Abstract

This paper studies a class of approach-evasion differential games, in which one player aims to steer the state of a dynamic system to the given target set in minimum time, while avoiding some set of disallowed states, and the other player desires to achieve the opposite. We propose a class of novel anytime computation algorithms, analyze their convergence properties and verify their performance via a number of numerical simulations. Our algorithms significantly outperform the multi-grid method for the approach-evasion differential games both theoretically and numerically. Our technical approach leverages incremental sampling in robotic motion planning and viability theory.

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