{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/efficient-large-scale-multi-drone-delivery","title":"Efficient Large-Scale Multi-Drone Delivery Using Transit Networks","arxiv_id":"1909.11840","date":"2019-09-26","proceeding":null,"authors":["Shushman Choudhury","Kiril Solovey","Mykel J. Kochenderfer","Marco Pavone"],"abstract":"We consider the problem of controlling a large fleet of drones to deliver packages simultaneously across broad urban areas. To conserve energy, drones hop between public transit vehicles (e.g., buses and trams). We design a comprehensive algorithmic framework that strives to minimize the maximum time to complete any delivery. We address the multifaceted complexity of the problem through a two-layer approach. First, the upper layer assigns drones to package delivery sequences with a near-optimal polynomial-time task allocation algorithm. Then, the lower layer executes the allocation by periodically routing the fleet over the transit network while employing efficient bounded-suboptimal multi-agent pathfinding techniques tailored to our setting. Experiments demonstrate the efficiency of our approach on settings with up to $200$ drones, $5000$ packages, and transit networks with up to $8000$ stops in San Francisco and Washington DC. Our results show that the framework computes solutions typically within a few seconds on commodity hardware, and that drones travel up to $360 \\%$ of their flight range with public transit.","url_abs":"https://arxiv.org/abs/1909.11840v5","url_pdf":"https://arxiv.org/pdf/1909.11840v5.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"efficient-large-scale-multi-drone-delivery","repo_url":"https://github.com/sisl/MultiAgentAllocationTransit.jl","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"efficient-large-scale-multi-drone-delivery","repo_url":"https://github.com/Shushman/MultiAgentPathFinding.jl","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}