Multi-UAV path planning in obstacle rich environments using Rapidly-exploring Random Trees

Mangal Kothari, Ian Postlethwaite, Da-Wei Gu

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    52 Citations (Scopus)

    Abstract

    This paper presents path planning algorithms using Rapidly-exploring Random Trees (RRTs) to generate paths for multiple unmanned air vehicles (UAVs) in real time, from given starting locations to goal locations in the presence of static, pop-up and dynamic obstacles. Generating non-conflicting paths in obstacle rich environments for a group of UAVs within a given short time window is a challenging task. The difficulty further increases because the turn radius constraints of the UAVs have to be comparable with the corridors where they intend to fly. Hence we first generate a path quickly using RRT by taking the kinematic constraints of the UAVs into account. Then in order to generate a low cost path we develop an anytime algorithm that yields paths whose quality improves as flight proceeds. When the UAV detects a dynamic obstacle, the path planner avoids it based on a set of criteria. In order to track generated paths, a guidance law based on pursuit and line-of-sight is developed. Simulation studies are carried out to show the performance of the proposed algorithm
    Original languageEnglish
    Title of host publicationProceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference
    Place of PublicationPiscataway, NJ
    PublisherIEEE
    Pages3069-3074
    ISBN (Print)978-1424438716
    DOIs
    Publication statusPublished - 2009
    Event48th IEEE Conference on Decision and Control - Shanghai, China
    Duration: 29 Jan 2009 → …

    Conference

    Conference48th IEEE Conference on Decision and Control
    Period29/01/09 → …

    Fingerprint Dive into the research topics of 'Multi-UAV path planning in obstacle rich environments using Rapidly-exploring Random Trees'. Together they form a unique fingerprint.

    Cite this