Comparison between A* and RRT Algorithms for UAV Path Planning

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Unmanned Aerial Vehicles (UAVs) are being integrated into a wide range of indoor and outdoor applications. In this light, robust and efficient path planning is paramount. An extensive literature review showed that the A* and Rapidly{Exploring Random Tree (RRT) algorithms and their variants are the most promising path planning algorithms candidates for 3D UAV scenarios. These two algorithms are tested in different complexity 3D scenarios consisting of a box and a combination of vertical and horizontal plane obstacles with apertures. The path length and generation time are considered as the performance measures. The A* with a spectrum of resolutions, the standard RRT with different step{ size constraints, RRT without step size constraints and the Multiple RRT (MRRT) with various seeds are implemented and their performance measures compared. Results confirm that all algorithms are able to generate a path in all scenarios for all resolutions, step sizes and seeds considered, respectively. Overall A*'s path length is more optimal and generation time is shorter than RRT projecting A* as a better candidate for online 3D path planning of UAVs.
Original languageEnglish
Title of host publicationProceedings of the 2018 AIAA Guidance, Navigation, and Control Conference
PublisherAmerican Institute of Aeronautics and Astronautics Inc. (AIAA)
Number of pages22
ISBN (Electronic)978-1-62410-526-5
Publication statusPublished - 2018
EventAIAA Guidance, Navigation, and Control Conference, 2018 - Kissimmee, United States
Duration: 8 Jan 201812 Jan 2018


ConferenceAIAA Guidance, Navigation, and Control Conference, 2018
Country/TerritoryUnited States
Internet address


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