Real-time path planning with limited information for automonous unmanned air vehicles

Yoonsoo Kim, Gu Da-Wei, Ian Postlethwaite

    Research output: Contribution to journalArticlepeer-review

    71 Citations (Scopus)

    Abstract

    We propose real-time path planning schemes employing limited information for fully autonomous unmanned air vehicles (UAVs) in a hostile environment. Two main algorithms are proposed under different assumptions on the information used and the threats involved. They consist of several simple (computationally tractable) deterministic rules for real-time applications. The first algorithm uses extremely limited information (only the probabilistic risk in the surrounding area with respect to the UAV’s current position) and memory, and the second utilizes more knowledge (the location and strength of threats within the UAV’s sensory range) and memory. Both algorithms provably converge to a given target point and produce a series of safe waypoints whose risk is almost less than a given threshold value. In particular, we characterize a class of dynamic threats (so-called, static-dependent threats) so that the second algorithm can efficiently handle such dynamic threats while guaranteeing its convergence to a given target. Challenging scenarios are used to test the proposed algorithms.
    Original languageEnglish
    Pages (from-to)696-712
    JournalAutomatica
    Volume44
    Issue number3
    DOIs
    Publication statusPublished - 2008

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