• Computer Science > Networking and Internet Architecture [Submitted on 18 Feb 2026] Title:Collection: UAV-Based Wireless Multi-modal Measurements from AERPAW Autonomous Data Mule (AADM) Challenge in Digital Twin and Real-World Environments View PDF HTML (experimental)Abstract:In this work, we present an unmanned aerial vehicle (UAV) wireless dataset collected as part of the AERPAW Autonomous Aerial Data Mule (AADM) challenge, organized by the NSF Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW) project. • The AADM challenge was the second competition in which an autonomous UAV acted as a data mule, where the UAV downloaded data from multiple base stations (BSs) in a dynamic wireless environment. • Participating teams designed flight control and decision-making algorithms for choosing which BSs to communicate with and how to plan flight trajectories to maximize data download within a mission completion time. • The competition was conducted in two stages: Stage 1 involved development and experimentation using a digital twin (DT) environment, and in Stage 2, the final test run was conducted on the outdoor testbed. • The total score for each team was compiled from both stages. • The resulting dataset includes link quality and data download measurements, both in DT and physical environments.
Article Summaries:
- The AERPAW Autonomous Aerial Data Mule (AADM) challenge released a comprehensive UAV‑based wireless dataset. In the second iteration of the competition, autonomous drones acted as data mules, downloading information from multiple base stations while planning flight paths to maximize throughput within a fixed mission time. The contest ran in two phases: a digital‑twin simulation and an outdoor field test, with team scores aggregated across both stages. The dataset contains link‑quality and download metrics, UAV telemetry, RF sensor positions, LoRa receiver data, and radar measurements. It is intended to support reproducible research in autonomous UAV networking, multi‑cell association, propagation modeling, and digital‑twin to real‑world transfer learning.
- Computer Science > Networking and Internet Architecture [Submitted on 18 Feb 2026 (v1), last revised 19 Feb 2026 (this version, v2)] Title:Collection: UAV-Based Wireless Multi-modal Measurements from AERPAW Autonomous Data Mule (AADM) Challenge in Digital Twin and Real-World Environments View PDF HTML (experimental)Abstract:In this work, we present an unmanned aerial vehicle (UAV) wireless dataset collected as part of the AERPAW Autonomous Aerial Data Mule (AADM) challenge, organized by the NSF Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW) project. The AADM challe
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