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http://hdl.handle.net/10397/91930
Title: | An end-to-end UAV simulation platform for visual SLAM and navigation aerospace | Authors: | Chen, S Zhou, W Yang, AS Chen, H Li, B Wen, CY |
Issue Date: | Feb-2022 | Source: | Aerospace, Feb. 2022, v. 9, no. 2, 48 | Abstract: | Visual simultaneous localization and mapping (v-SLAM) and navigation of unmanned aerial vehicles (UAVs) are receiving increasing attention in both research and education. However, extensive physical testing can be expensive and time-consuming due to safety precautions, battery constraints, and the complexity of hardware setups. For the efficient development of navigation algorithms and autonomous systems, as well as for education purposes, the ROS-Gazebo-PX4 simulator was customized in-depth, integrated into our previous released research works, and provided as an end-to-end simulation (E2ES) solution for UAV, v-SLAM, and navigation applications. Unlike most other similar works, which can only stimulate certain parts of the navigation algorithms, the E2ES platform simulates all of the localization, mapping, and path-planning kits in one simulator. The navigation stack performs well in the E2ES test bench with the absolute pose errors of 0.3 m (translation) and 0.9 degree (rotation), respectively, for an 83 m length trajectory. Moreover, the E2ES provides an out-of-box, click-and-fly autonomy in UAV navigation. The project source code is opened for the benefit of the research community. | Keywords: | UAV Robotic simulation Stereo camera SLAM Path planning |
Publisher: | Molecular Diversity Preservation International (MDPI) | Journal: | Aerospace | ISSN: | 2226-4310 | DOI: | 10.3390/aerospace9020048 | Rights: | © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The following publication Chen, S.; Zhou, W.; Yang, A.-S.; Chen, H.; Li, B.; Wen, C.-Y. An End-to-End UAV Simulation Platform for Visual SLAM and Navigation. Aerospace 2022, 9, 48 is available at https://dx.doi.org/10.3390/aerospace9020048. |
Appears in Collections: | Journal/Magazine Article |
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