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EasyChair Preprint No 1350 Large-scale 3 D Mapping of Subarctic Forests
| Content Provider | Semantic Scholar |
|---|---|
| Author | Babin, Philippe Dandurand, Philippe Kubelka, Vladimir Giguère, Philippe Pomerleau, François |
| Abstract | The ability to map challenging subarctic environments opens new horizons for robotic deployments in industries such as forestry, surveillance, and openpit mining. In this paper, we explore possibilities of large-scale lidar mapping in a boreal forest. Computational and sensory requirements with regards to contemporary hardware are considered as well. The lidar mapping is often based on the Simultaneous Localization and Mapping (SLAM) technique relying on pose graph optimization, which fuses the Iterative Closest Point (ICP) algorithm, Global Navigation Satellite System (GNSS) positioning, and Inertial Measurement Unit (IMU) measurements. To handle those sensors directly within the ICP minimization process, we propose an alternative approach of embedding external constraints. Furthermore, a novel formulation of a cost function is presented and cast into the problem of handling uncertainties from GNSS and lidar points. To test our approach, we acquired a large-scale dataset in the Forêt Montmorency research forest. We report on the technical problems faced during our winter deployments aiming at building 3D maps using our new cost function. Those maps demonstrate both global and local consistency over 4.1 km. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://easychair.org/publications/preprint_download/lRrh |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
