Hybrid Path Planning for UAV Traffic Management

Eyal Zehavi, Noa Agmon

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Unmanned Aircraft System Traffic Management (UTM) becomes a highly relevant complex challenge, as the UAV activity is rapidly growing bringing more amateur and professional drones to the urban skies. The main concern of managing such a system is safely navigating and controlling hundreds or thousands of drones simultaneously, flying in a crowded dense environments. This paper introduces an innovative approach of hybrid path planning, which tries to make the best out of the commonly used centralized and decentralized planning approaches. The Hybrid Path Planner (HPP) defines two configuration spaces: the Local Zone, which represents the crowded city zone with many obstacles and constrains, and the Global Zone, which represents the outer suburban zone, mostly open space with predefined flight corridors. The HPP server communicates with each UAV, assigning it a close-to-optimal path in the global zone, while leaving the relatively heavy-duty local zone path planning task to be performed by the UAV, mostly using stochastic methods like RRT*. This approach reduces the complex path panning task of the centralized server to a simpler task of calculating only the entry and exit points to and from the global zone. This robust approach supports handling a high number of UAVs, while keeping close to optimal performance.

Original languageEnglish
Title of host publicationIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages7
ISBN (Electronic)9781665417143
StatePublished - 2021
Event2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021 - Prague, Czech Republic
Duration: 27 Sep 20211 Oct 2021

Publication series

NameIEEE International Conference on Intelligent Robots and Systems


Conference2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
Country/TerritoryCzech Republic

All Science Journal Classification (ASJC) codes

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


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