# SARDO: An Automated Search-and-Rescue Drone-based Solution for Victims Localization

arXiv: https://arxiv.org/abs/2003.05819 · HTML: https://mlsanity.com/paper/2003.05819/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Mar 2020.

## Built on by (most cited first, 9 of 9)

- [SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water](https://mlsanity.com/paper/2105.01922/) (2021)
- [Selective Exploration and Information Gathering in Search and Rescue Using Hierarchical Learning Guided by Natural Language Input](https://mlsanity.com/paper/2409.13445/) (2024)
- [SeaDroneSim: Simulation of Aerial Images for Detection of Objects Above Water](https://mlsanity.com/paper/2210.16107/) (2022)
- [Whale Detection Enhancement through Synthetic Satellite Images](https://mlsanity.com/paper/2308.07766/) (2023)
- [NOMAD: A Natural, Occluded, Multi-scale Aerial Dataset, for Emergency Response Scenarios](https://mlsanity.com/paper/2309.09518/) (2023)
- [ADAPT: An Open-Source sUAS Payload for Real-Time Disaster Prediction and Response with AI](https://mlsanity.com/paper/2201.10366/) (2022)
- [Leveraging Event Streams with Deep Reinforcement Learning for End-to-End UAV Tracking](https://mlsanity.com/paper/2410.14685/) (2024)
- [MGPRL: Distributed Multi-Gaussian Processes for Wi-Fi-based Multi-Robot Relative Localization in Large Indoor Environments](https://mlsanity.com/paper/2506.23514/) (2025)
- [Statistical-Geometric Degeneracy in UAV Search: A Physics-Aware Asymmetric Filtering Approach](https://mlsanity.com/paper/2602.15893/) (2026)

## Abstract (arXiv)

Natural disasters affect millions of people every year. Finding missing persons in the shortest possible time is of crucial importance to reduce the death toll. This task is especially challenging when victims are sparsely distributed in large and/or difficult-to-reach areas and cellular networks are down. In this paper we present SARDO, a drone-based search and rescue solution that exploits the high penetration rate of mobile phones in the society to localize missing people. SARDO is an autonomous, all-in-one drone-based mobile network solution that does not require infrastructure support or mobile phones modifications. It builds on novel concepts such as pseudo-trilateration combined with machine-learning techniques to efficiently locate mobile phones in a given area. Our results, with a prototype implementation in a field-trial, show that SARDO rapidly determines the location of mobile phones (~3 min/UE) in a given area with an accuracy of few tens of meters and at a low battery consumption cost (~5%). State-of-the-art localization solutions for disaster scenarios rely either on mobile infrastructure support or exploit onboard cameras for human/computer vision, IR, thermal-based localization. To the best of our knowledge, SARDO is the first drone-based cellular search-and-rescue solution able to accurately localize missing victims through mobile phones.