# Lessons from Robot-Assisted Disaster Response Deployments by the German Rescue Robotics Center Task Force

arXiv: https://arxiv.org/abs/2212.09354 · HTML: https://mlsanity.com/paper/2212.09354/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Dec 2022.

## Built on by (most cited first, 4 of 4)

- [AHA -- Predicting What Matters Next: Online Highlight Detection Without Looking Ahead](https://mlsanity.com/paper/2509.16421/) (2025)
- [Redefining Recon: Bridging Gaps with UAVs, 360 degree Cameras, and Neural Radiance Fields](https://mlsanity.com/paper/2401.06143/) (2023)
- [LiDAR-based Registration against Georeferenced Models for Globally Consistent Allocentric Maps](https://mlsanity.com/paper/2412.02533/) (2024)
- [A 360-Degree Vision Dataset for Learning Yaw Control on GPS-Denied Micro-UAVs in Disaster-Response-Relevant Environments](https://mlsanity.com/paper/2608.19866/) (2026)

## Abstract (arXiv)

Earthquakes, fire, and floods often cause structural collapses of buildings. The inspection of damaged buildings poses a high risk for emergency forces or is even impossible, though. We present three recent selected missions of the Robotics Task Force of the German Rescue Robotics Center, where both ground and aerial robots were used to explore destroyed buildings. We describe and reflect the missions as well as the lessons learned that have resulted from them. In order to make robots from research laboratories fit for real operations, realistic test environments were set up for outdoor and indoor use and tested in regular exercises by researchers and emergency forces. Based on this experience, the robots and their control software were significantly improved. Furthermore, top teams of researchers and first responders were formed, each with realistic assessments of the operational and practical suitability of robotic systems.