An Efficient Framework for Autonomous UAV Missions in Partially-Unknown GNSS-Denied Environments
Nowadays, multirotors are versatile systems that can be employed in several scenarios, where their increasing autonomy allows them to achieve complex missions without human intervention. This paper presents a framework for autonomous missions with low-cost Unmanned Aerial Vehicles (UAVs) in Global N...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/7/7/471 |
| _version_ | 1797589617751359488 |
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| author | Michael Mugnai Massimo Teppati Losé Edwin Paúl Herrera-Alarcón Gabriele Baris Massimo Satler Carlo Alberto Avizzano |
| author_facet | Michael Mugnai Massimo Teppati Losé Edwin Paúl Herrera-Alarcón Gabriele Baris Massimo Satler Carlo Alberto Avizzano |
| author_sort | Michael Mugnai |
| collection | DOAJ |
| description | Nowadays, multirotors are versatile systems that can be employed in several scenarios, where their increasing autonomy allows them to achieve complex missions without human intervention. This paper presents a framework for autonomous missions with low-cost Unmanned Aerial Vehicles (UAVs) in Global Navigation Satellite System-denied (GNSS-denied) environments. This paper presents hardware choices and software modules for localization, perception, global planning, local re-planning for obstacle avoidance, and a state machine to dictate the overall mission sequence. The entire software stack has been designed exploiting the Robot Operating System (ROS) middleware and has been extensively validated in both simulation and real environment tests. The proposed solution can run both in simulation and in real-world scenarios without modification thanks to a small sim-to-real gap with PX4 software-in-the-loop functionality. The overall system has competed successfully in the Leonardo Drone Contest, an annual competition between Italian Universities with a focus on low-level, resilient, and fully autonomous tasks for vision-based UAVs, proving the robustness of the entire system design. |
| first_indexed | 2024-03-11T01:09:05Z |
| format | Article |
| id | doaj.art-c15715708c2f4879bca6a29ec8223984 |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-11T01:09:05Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-c15715708c2f4879bca6a29ec82239842023-11-18T19:01:33ZengMDPI AGDrones2504-446X2023-07-017747110.3390/drones7070471An Efficient Framework for Autonomous UAV Missions in Partially-Unknown GNSS-Denied EnvironmentsMichael Mugnai0Massimo Teppati Losé1Edwin Paúl Herrera-Alarcón2Gabriele Baris3Massimo Satler4Carlo Alberto Avizzano5Institute of Mechanical Intelligence, Sant’Anna School of Advanced Studies, 56127 Pisa, ItalyInstitute of Mechanical Intelligence, Sant’Anna School of Advanced Studies, 56127 Pisa, ItalyInstitute of Mechanical Intelligence, Sant’Anna School of Advanced Studies, 56127 Pisa, ItalyInstitute of Mechanical Intelligence, Sant’Anna School of Advanced Studies, 56127 Pisa, ItalyInstitute of Mechanical Intelligence, Sant’Anna School of Advanced Studies, 56127 Pisa, ItalyInstitute of Mechanical Intelligence, Sant’Anna School of Advanced Studies, 56127 Pisa, ItalyNowadays, multirotors are versatile systems that can be employed in several scenarios, where their increasing autonomy allows them to achieve complex missions without human intervention. This paper presents a framework for autonomous missions with low-cost Unmanned Aerial Vehicles (UAVs) in Global Navigation Satellite System-denied (GNSS-denied) environments. This paper presents hardware choices and software modules for localization, perception, global planning, local re-planning for obstacle avoidance, and a state machine to dictate the overall mission sequence. The entire software stack has been designed exploiting the Robot Operating System (ROS) middleware and has been extensively validated in both simulation and real environment tests. The proposed solution can run both in simulation and in real-world scenarios without modification thanks to a small sim-to-real gap with PX4 software-in-the-loop functionality. The overall system has competed successfully in the Leonardo Drone Contest, an annual competition between Italian Universities with a focus on low-level, resilient, and fully autonomous tasks for vision-based UAVs, proving the robustness of the entire system design.https://www.mdpi.com/2504-446X/7/7/471UAVMAVmission planningcollision avoidancenavigation in partially-known environmentsvisual-based navigation |
| spellingShingle | Michael Mugnai Massimo Teppati Losé Edwin Paúl Herrera-Alarcón Gabriele Baris Massimo Satler Carlo Alberto Avizzano An Efficient Framework for Autonomous UAV Missions in Partially-Unknown GNSS-Denied Environments Drones UAV MAV mission planning collision avoidance navigation in partially-known environments visual-based navigation |
| title | An Efficient Framework for Autonomous UAV Missions in Partially-Unknown GNSS-Denied Environments |
| title_full | An Efficient Framework for Autonomous UAV Missions in Partially-Unknown GNSS-Denied Environments |
| title_fullStr | An Efficient Framework for Autonomous UAV Missions in Partially-Unknown GNSS-Denied Environments |
| title_full_unstemmed | An Efficient Framework for Autonomous UAV Missions in Partially-Unknown GNSS-Denied Environments |
| title_short | An Efficient Framework for Autonomous UAV Missions in Partially-Unknown GNSS-Denied Environments |
| title_sort | efficient framework for autonomous uav missions in partially unknown gnss denied environments |
| topic | UAV MAV mission planning collision avoidance navigation in partially-known environments visual-based navigation |
| url | https://www.mdpi.com/2504-446X/7/7/471 |
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