{"ID":2837776,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.19653","arxiv_id":"2511.19653","title":"Flow-Based Path Planning for Multiple Homogenous UAVs for Outdoor Formation-Flying","abstract":"Collision-free path planning is the most crucial component in multi-UAV formation-flying (MFF). We use unlabeled homogenous quadcopters (UAVs) to demonstrate the use of a flow network to create complete (inter-UAV) collision-free paths. This procedure has three main parts: 1) Creating a flow network graph from physical GPS coordinates, 2) Finding a path of minimum cost (least distance) using any graph-based path-finding algorithm, and 3) Implementing the Ford-Fulkerson Method to find the paths with the maximum flow (no collision). Simulations of up to 64 UAVs were conducted for various formations, followed by a practical experiment with 3 quadcopters for testing physical plausibility and feasibility. The results of these tests show the efficacy of this method's ability to produce safe, collision-free paths.","short_abstract":"Collision-free path planning is the most crucial component in multi-UAV formation-flying (MFF). We use unlabeled homogenous quadcopters (UAVs) to demonstrate the use of a flow network to create complete (inter-UAV) collision-free paths. This procedure has three main parts: 1) Creating a flow network graph from physical...","url_abs":"https://arxiv.org/abs/2511.19653","url_pdf":"https://arxiv.org/pdf/2511.19653v1","authors":"[\"Mahmud Suhaimi Ibrahim\",\"Shantanu Rahman\",\"Muhammad Samin Hasan\",\"Minhaj Uddin Ahmad\",\"Abdullah Abrar\"]","published":"2025-11-24T19:35:56Z","proceeding":"cs.RO","tasks":"[\"cs.RO\"]","methods":"[]","has_code":false}