Multi-modal Mapping and Localization of Unmanned Aerial Robots based on Ultra-Wideband and RGB-D sensing

F.J. Perez-Grau, F. Caballero, L. Merino, and A. Viguria. Multi-modal Mapping and Localization of Unmanned Aerial Robots based on Ultra-Wideband and RGB-D sensing. In Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, pp. 3495–3502, 2017.

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Abstract

This paper presents a methodology for mapping and localization of Unmanned Aerial Vehicles (UAVs) based on the integration of sensors from different modalities. Particularly, we integrate distance estimations to Ultra-Wideband (UWB) sensors and 3D point-clouds from RGB-D sensors. First, a novel approach for environment mapping is introduced, exploiting the synergies between UWB sensors and point-clouds to produce a multi-modal 3D map that integrates the estimated UWB sensors position. This map is further integrated into a Monte Carlo Localization method to robustly estimate the UAV pose. Finally, the full approach is tested with real indoor flights and validated with a motion tracking system

BibTeX Entry

@INPROCEEDINGS{iros17aerial,
  author = {F.J. Perez-Grau and F. Caballero and L. Merino and A. Viguria},
  title = {{Multi-modal Mapping and Localization of Unmanned Aerial Robots based on Ultra-Wideband and RGB-D sensing}},
  booktitle = IROS,
  year = {2017},
  pages = {3495--3502},
  doi = {10.1109/IROS.2017.8206191},
  abstract={This paper presents a methodology for mapping and localization of Unmanned Aerial Vehicles (UAVs) based on the integration of sensors from different modalities. Particularly, we integrate distance estimations to Ultra-Wideband (UWB) sensors and 3D point-clouds from RGB-D sensors. First, a novel approach for environment mapping is introduced, exploiting the synergies between UWB sensors and point-clouds to produce a multi-modal 3D map that integrates the estimated UWB sensors position. This map is further integrated into a Monte Carlo Localization method to robustly estimate the UAV pose. Finally, the full approach is tested with real indoor flights and validated with a motion tracking system},
}

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