التفاصيل البيبلوغرافية
| العنوان: |
Framework for Autonomous UAV Navigation and Target Detection in Global-Navigation-Satellite-System-Denied and Visually Degraded Environments |
| المؤلفون: |
Boiteau, Sebastien, Vanegas, Fernando, Gonzalez, Felipe |
| المصدر: |
Remote Sensing |
| بيانات النشر: |
Multidisciplinary Digital Publishing Institute |
| سنة النشر: |
2024 |
| المجموعة: |
Queensland University of Technology: QUT ePrints |
| مصطلحات موضوعية: |
embedded systems, low visibility, motion planner, partially observable Markov decision process, remote sensing, search and rescue, unmanned aerial vehicles |
| الوصف: |
Autonomous Unmanned Aerial Vehicles (UAVs) have possible applications in wildlife monitoring, disaster monitoring, and emergency Search and Rescue (SAR). Autonomous capabilities such as waypoint flight modes and obstacle avoidance, as well as their ability to survey large areas, make UAVs the prime choice for these critical applications. However, autonomous UAVs usually rely on the Global Navigation Satellite System (GNSS) for navigation and normal visibility conditions to obtain observations and data on their surrounding environment. These two parameters are often lacking due to the challenging conditions in which these critical applications can take place, limiting the range of utilisation of autonomous UAVs. This paper presents a framework enabling a UAV to autonomously navigate and detect targets in GNSS-denied and visually degraded environments. The navigation and target detection problem is formulated as an autonomous Sequential Decision Problem (SDP) with uncertainty caused by the lack of the GNSS and low visibility. The SDP is modelled as a Partially Observable Markov Decision Process (POMDP) and tested using the Adaptive Belief Tree (ABT) algorithm. The framework is tested in simulations and real life using a navigation task based on a classic SAR operation in a cluttered indoor environment with different visibility conditions. The framework is composed of a small UAV with a weight of 5 kg, a thermal camera used for target detection, and an onboard computer running all the computationally intensive tasks. The results of this study show the robustness of the proposed framework to autonomously explore and detect targets using thermal imagery under different visibility conditions. Devising UAVs that are capable of navigating in challenging environments with degraded visibility can encourage authorities and public institutions to consider the use of autonomous remote platforms to locate stranded people in disaster scenarios. |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
unknown |
| Relation: |
Boiteau, Sebastien, Vanegas, Fernando, & Gonzalez, Felipe (2024) Framework for Autonomous UAV Navigation and Target Detection in Global-Navigation-Satellite-System-Denied and Visually Degraded Environments. Remote Sensing, 16(3), Article number: 471.; http://purl.org/au-research/grants/arc/DP200101640; https://eprints.qut.edu.au/247033/; Centre for Robotics; Faculty of Engineering; School of Electrical Engineering & Robotics |
| الاتاحة: |
https://eprints.qut.edu.au/247033/ |
| Rights: |
© 2024 by the authors. ; This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au |
| رقم الانضمام: |
edsbas.8229FFCA |
| قاعدة البيانات: |
BASE |