Anytime computation algorithms for stochastically parametric approach-evasion differential games

Erich Mueller, Sze Zheng Yong, Minghui Zhu, Emilio Frazzoli

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    3 Scopus citations

    Abstract

    We consider an approach-evasion differential game where the inputs of one of the players are upper bounded by a random variable. The game enjoys the order preserving property where a larger relaxation of the random variable induces a smaller value function. Two numerical computation algorithms are proposed to asymptotically recover the expected value function. The performance of the proposed algorithms is compared via a stochastically parametric homicidal chauffeur game. The algorithms are also applied to the scenario of merging lanes in urban transportation.

    Original languageEnglish (US)
    Title of host publicationIROS 2013
    Subtitle of host publicationNew Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
    Pages3816-3821
    Number of pages6
    DOIs
    StatePublished - Dec 1 2013
    Event2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013 - Tokyo, Japan
    Duration: Nov 3 2013Nov 8 2013

    Publication series

    NameIEEE International Conference on Intelligent Robots and Systems
    ISSN (Print)2153-0858
    ISSN (Electronic)2153-0866

    Other

    Other2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013
    CountryJapan
    CityTokyo
    Period11/3/1311/8/13

    All Science Journal Classification (ASJC) codes

    • Control and Systems Engineering
    • Software
    • Computer Vision and Pattern Recognition
    • Computer Science Applications

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  • Cite this

    Mueller, E., Yong, S. Z., Zhu, M., & Frazzoli, E. (2013). Anytime computation algorithms for stochastically parametric approach-evasion differential games. In IROS 2013: New Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 3816-3821). [6696902] (IEEE International Conference on Intelligent Robots and Systems). https://doi.org/10.1109/IROS.2013.6696902