# A UAV-assisted Wireless Localization Challenge on AERPAW

arXiv: https://arxiv.org/abs/2407.12180 · HTML: https://mlsanity.com/paper/2407.12180/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Jul 2024.

## Built on by (most cited first, 1 of 1)

- [Bridging Simulation and Reality: A 3D Clustering-Based Deep Learning Model for UAV-Based RF Source Localization](https://mlsanity.com/paper/2502.13969/) (2025)

## Abstract (arXiv)

As wireless researchers are tasked to enable wireless communication as infrastructure in more dynamic aerial settings, there is a growing need for large-scale experimental platforms that provide realistic, reproducible, and reliable experimental validation. To bridge the research-to-implementation gap, the Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW) offers open-source tools, reference experiments, and hardware to facilitate and evaluate the development of wireless research in controlled digital twin environments and live testbed flights. The inaugural AERPAW Challenge, "Find a Rover," was issued to spark collaborative efforts and test the platform's capabilities. The task involved localizing a narrowband wireless signal, with teams given ten minutes to find the "rover" within a twenty-acre area. By engaging in this exercise, researchers can validate the platform's value as a tool for innovation in wireless communications research within aerial robotics. This paper recounts the methods and experiences of the top three teams in automating and rapidly locating a wireless signal by automating and controlling an aerial drone in a realistic testbed scenario.