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The video shows a very high resolution 3D point cloud !!! of the outdoor area of the German Rescue Robotics Center. For the recording, a 25-second POI flight was performed with a Mavic 3. From the 4K video footage captured during this flight, 77 images were cropped and localized within 4 minutes using colmap and processed using Neural Radiance Fields (NeRF). The nerfacto model of Nerfstudio was trained on an Nvidia RTX 4090 for 8 minutes. In summary, a top 3D model is available to task forces after about 13 minutes. The calculation is performed locally on site by the RobLW of the DRZ. The video shown here shows a free camera path rendered at 60 hz (Full HD).
Durch Panoramen in Kombination mit dem ORB-SLAM ist ein schnelles Tracking möglich, liefert jedoch ausschließlich spärliche Daten. Durch die Kombination mit einem neuronalen Netz soll der SLAM Algorithmus zu einem RGBD-SLAM erweitert werden, um ein besseres Tracking und eine dichtere Punktwolke zu gewährleisten.
This technical report is about the architecture and integration of commercial UAVs in Search and Rescue missions. We describe a framework that consists of heterogeneous UAVs, a UAV task planner, a bridge to the UAVs, an intelligent image hub, and a 3D point cloud generator. A first version of the framework was developed and tested in several training missions in the EU project TRADR.
At the integration sprint of the E-DRZ consortium in march 2023 we improve the information captured by the human spotter (of the fire brigade) by extending him through a 360° drone. The UAV needs 3 minutes to capture the outdoor scenario and the hall from inside and outside. The hall ist about 70 x 20 meters. When the drone is landed we have all information in 360° degree at 5.7k as you can see it in the video. Furthermore it is a perfect documentation of the deployment scenario. In the next video we will show how to spatial localize the 360° video and how to generate a 3D point cloud from it.
At the integration sprint of the E-DRZ consortium in march 2023 we improve the information captured by the human spotter (of the fire brigade) by extending him through a 360° drone i.e. the DJI Avata with an Insta360 on top of it. The UAV needs 3 minutes to capture the outdoor scenario and the hall from inside and outside. The hall ist about 70 x 20 meters. When the drone is landed we have all information in 360° degree at 5.7k as you can see it in the video. Furthermore it is a perfect documentation of the deployment scenario. In the next video we will show how to spatial localize the 360° video and how to generate a 3D point cloud from it.