Forschungsprojekt
HELIOS - Heidelberg LiDAR Operations Simulator
News
Stay up-to-date by following HELIOS on ResearchGate. Research news can be found in our GIScience News Blog.
Download and Use HELIOS
HELIOS is open source (GNU GPL) and hosted in our github repository. A pre-compiled version can be downloaded here. The corresponding wiki contains information on how to set up and handle HELIOS.
Some impressions of HELIOS
Publications
3DGeo Publications
- Hämmerle, M., Lukač, N., Chen, K.-C., Koma, Zs., Wang, C.-K., Anders, K., & Höfle, B. (2017): Simulating Various Terrestrial and UAV LiDAR Scanning Configurations for Understory Forest Structure Modelling. In: ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W4, pp. 59-65. DOI: 10.5194/isprs-annals-IV-2-W4-59-2017.
- Bechtold, S., Hämmerle, M. & Höfle, B. (2016): Simulated full-waveform laser scanning of outcrops for development of point cloud analysis algorithms and survey planning: An application for the HELIOS lidar simulation framework. In: Proceedings of the 2nd Virtual Geoscience Conference, Bergen, Norway, 21-23 September 2016, pp. 57-58.
- Bechtold, S. & Höfle, B. (2016): HELIOS: A Multi-purpose LiDAR Simulation Framework for Research, Planning and Training of Laser Scanning Operations With Airborne, Ground-based Mobile and Stationary Platforms. In: ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-3, pp. 161-168. DOI: 10.5194/isprs-annals-III-3-161-2016.
Publications from Other Research Groups
- Xiao, W., Zaforemska, A., Smigaj, M., Wang, Y., Gaulton, R. (2019): Mean Shift Segmentation Assessment for Individual Forest Tree Delineation from Airborne Lidar Data. In: Remote Sensing, 11, pp. 1-19. DOI: https://doi.org/10.3390/rs11111263.
- Liu, J., Skidmore, A.K., Wang, T., Zhu, X., Premier, J., Heurich, M., Beudert, B. & Jones, S. (2019): Variation of leaf angle distribution quantified by terrestrial LiDAR in natural European beech forest. In: ISPRS Journal of Photogrammetry and Remote Sensing, 148, pp. 208-220. DOI: 10.1016/j.isprsjprs.2019.01.005.
- Rebolj, D., Pučko, Z., Babič, N.Č., Bizjak, M. & Mongus, D. (2017). Point cloud quality requirements for Scan-vs-BIM based automated construction progress monitoring. In: Automation in Construction, 84, pp. 323-334. DOI: 10.1016/j.autcon.2017.09.021.
Objective
In many technical domains of modern society, there is a growing demand for fast, precise and automatic acquisition of digital 3D models of a wide variety of physical objects and environments. Laser scanning is a popular and widely used technology to cover this demand, but it is also expensive and complex to use to its full potential.
There are scenarios in which the operation of a real laser scanner can be replaced by a computer simulation, in order to save time and costs. This includes scenarios like teaching and training of laser scanning, development of new scanner hardware and scanning methods, or generation of artificial scan data sets to support the development of point cloud processing and analysis algorithms.
Following this idea, we develop a highly flexible laser scanning simulation framework named Heidelberg LiDAR Operations Simulator (HELIOS).
Project Tasks
HELIOS is implemented as a Java library and split up into a core component and multiple extension modules. Extensible Markup Language (XML) is used to define scanner, platform and scene models and to configure the behaviour of modules. Modules are developed and implemented for (1) loading of simulation assets and configuration (i.e. 3D scene models, scanner definitions, survey descriptions etc.), (2) playback of XML survey descriptions, (3) TLS survey planning (i.e. automatic computation of recommended scanning positions) and (4) interactive real-time 3D visualization of simulated surveys.
How to Cite HELIOS
If you use HELIOS in your work, please cite:
Bechtold, S. & Höfle, B. (2016): HELIOS: A Multi-Purpose LiDAR Simulation Framework for Research, Planning and Training of Laser Scanning Operations with Airborne, Ground-Based Mobile and Stationary Platforms. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. III-3, pp. 161-168. DOI: 10.5194/isprs-annals-III-3-161-2016
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