Multilayer Mapping Kit for Autonomous UAV Navigation
Mapping, as the back-end of perception and the front-end of path planning in the modern UAV navigation system, draws our interest. Considering the requirements of UAV navigation and the features of the current embedded computation platforms, we designed and implemented a novel multilayer mapping fra...
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doaj-ef0d071315204ca2a29da6d0a688c0072021-03-30T15:11:16ZengIEEEIEEE Access2169-35362021-01-019314933150310.1109/ACCESS.2021.30550669336584Multilayer Mapping Kit for Autonomous UAV NavigationShengyang Chen0https://orcid.org/0000-0003-1506-0615Han Chen1https://orcid.org/0000-0002-1106-6617Ching-Wei Chang2Chih-Yung Wen3https://orcid.org/0000-0002-1181-8786Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hong KongInterdisciplinary Division of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hong KongDepartment of Mechanical Engineering, The Hong Kong Polytechnic University, Hong KongDepartment of Mechanical Engineering, The Hong Kong Polytechnic University, Hong KongMapping, as the back-end of perception and the front-end of path planning in the modern UAV navigation system, draws our interest. Considering the requirements of UAV navigation and the features of the current embedded computation platforms, we designed and implemented a novel multilayer mapping framework. In this framework, we divided the map into three layers: awareness, local, and global. The awareness map is constructed in cylindrical coordinate, enabling fast raycasting. The local map is a probability-based volumetric map. The global map adopts dynamic memory management, allocating memory for the active mapping area, and recycling the memory from the inactive mapping area. We implemented this mapping framework in three parallel threads: awareness thread, local-global thread, and visualization thread. Finally, we evaluated the mapping kit in both the simulation environment and the real-world scenario with the vision-based sensors. The framework supports different kinds of map outputs for the global or local path planners. The implementation is open-source for the research community.https://ieeexplore.ieee.org/document/9336584/Mappingreconstructionunmanned aerial vehiclenavigationsimultaneous localization and mappingnavigation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shengyang Chen Han Chen Ching-Wei Chang Chih-Yung Wen |
spellingShingle |
Shengyang Chen Han Chen Ching-Wei Chang Chih-Yung Wen Multilayer Mapping Kit for Autonomous UAV Navigation IEEE Access Mapping reconstruction unmanned aerial vehicle navigation simultaneous localization and mapping navigation |
author_facet |
Shengyang Chen Han Chen Ching-Wei Chang Chih-Yung Wen |
author_sort |
Shengyang Chen |
title |
Multilayer Mapping Kit for Autonomous UAV Navigation |
title_short |
Multilayer Mapping Kit for Autonomous UAV Navigation |
title_full |
Multilayer Mapping Kit for Autonomous UAV Navigation |
title_fullStr |
Multilayer Mapping Kit for Autonomous UAV Navigation |
title_full_unstemmed |
Multilayer Mapping Kit for Autonomous UAV Navigation |
title_sort |
multilayer mapping kit for autonomous uav navigation |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2021-01-01 |
description |
Mapping, as the back-end of perception and the front-end of path planning in the modern UAV navigation system, draws our interest. Considering the requirements of UAV navigation and the features of the current embedded computation platforms, we designed and implemented a novel multilayer mapping framework. In this framework, we divided the map into three layers: awareness, local, and global. The awareness map is constructed in cylindrical coordinate, enabling fast raycasting. The local map is a probability-based volumetric map. The global map adopts dynamic memory management, allocating memory for the active mapping area, and recycling the memory from the inactive mapping area. We implemented this mapping framework in three parallel threads: awareness thread, local-global thread, and visualization thread. Finally, we evaluated the mapping kit in both the simulation environment and the real-world scenario with the vision-based sensors. The framework supports different kinds of map outputs for the global or local path planners. The implementation is open-source for the research community. |
topic |
Mapping reconstruction unmanned aerial vehicle navigation simultaneous localization and mapping navigation |
url |
https://ieeexplore.ieee.org/document/9336584/ |
work_keys_str_mv |
AT shengyangchen multilayermappingkitforautonomousuavnavigation AT hanchen multilayermappingkitforautonomousuavnavigation AT chingweichang multilayermappingkitforautonomousuavnavigation AT chihyungwen multilayermappingkitforautonomousuavnavigation |
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1724179930862845952 |