aerial-mapper

Overview

Load camera poses from different formats (such as PIX4D, COLMAP)
Generates a dense point cloud from raw images, camera poses and camera intrinsics
Generates Digital Surface Models (DSMs) from raw point clouds and exports e.g. to GeoTiff format
Different methods to generate (ortho-)mosaics from raw images, camera poses and camera intrinsics

Package Overview

aerial_mapper: Meta package
aerial_mapper_demos: Sample executables.
aerial_mapper_dense_pcl: Dense point cloud generation using planar rectification.
aerial_mapper_dsm: Digitial Surface Map/Model generation.
aerial_mapper_google_maps_api: Wrapper package for Google Maps API.
aerial_mapper_grid_map: Wrapper package for grid_map.
aerial_mapper_io: Input/Output handler that reads/writes poses, intrinsics, point clouds, GeoTiffs etc.
aerial_mapper_ortho: Different methods for (ortho-)mosaic generation.
aerial_mapper_thirdparty: Package containing thirdparty code.
aerial_mapper_utils: Package for common utility functions.

Getting started

Output samples

Dense point cloud (from virtual stereo pair, 2 images)	Digital Surface Map (DSM, exported as GeoTiff)	(Ortho-)Mosaic (from homography, 249 images)

Raw images	Dense point cloud	Digital Surface Map

Observation Angle (red: nadir)	Grid-based Orthomosaic (Cell resolution: 0.5m)	Textured DSM

Publications

If you use this work in an academic context, please cite the following publication:

T. Hinzmann, J. L. Schönberger, M. Pollefeys, and R. Siegwart, "Mapping on the Fly: Real-time 3D Dense Reconstruction, Digital Surface Map and Incremental Orthomosaic Generation for Unmanned Aerial Vehicles" [PDF]

@INPROCEEDINGS{fsr_hinzmann_2017,
   Author = {T. Hinzmann, J. L. Schönberger, M. Pollefeys, and R. Siegwart},
   Title = {Mapping on the Fly: Real-time 3D Dense Reconstruction, Digital Surface Map and Incremental Orthomosaic Generation for Unmanned Aerial Vehicles},
   Booktitle = {Field and Service Robotics - Results of the 11th International Conference},
   Year = {2017}
}

Acknowledgment

This work was partially funded by the European FP7 project SHERPA (FP7-600958) and the Federal office armasuisse Science and Technology under project number 050-45. Furthermore, the authors wish to thank Lucas P. Teixeira from the Vision for Robotics Lab at ETH Zurich for sharing scripts that bridge the gap between Blender and Gazebo.

tfgbestneal/aerial_mapper