Software Architecture for Autonomous and Coordinated Navigation of UAV Swarms in Forest and Urban Firefighting
| العنوان: | Software Architecture for Autonomous and Coordinated Navigation of UAV Swarms in Forest and Urban Firefighting |
|---|---|
| المؤلفون: | Ángel Madridano, Arturo de la Escalera, David Martin, Abdulla Al-Kaff, Pablo Flores |
| المساهمون: | Comunidad de Madrid |
| المصدر: | e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid instname Applied Sciences Volume 11 Issue 3 Applied Sciences, Vol 11, Iss 1258, p 1258 (2021) e-Archivo: Repositorio Institucional de la Universidad Carlos III de Madrid Universidad Carlos III de Madrid (UC3M) |
| بيانات النشر: | MDPI, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Computer science, Distributed computing, Robótica e Informática Industrial, 02 engineering and technology, UAVs, lcsh:Technology, Field (computer science), autonomous, lcsh:Chemistry, Autonomous, Robustness (computer science), 0202 electrical engineering, electronic engineering, information engineering, Reinforcement learning, Swarm, General Materials Science, navigation, lcsh:QH301-705.5, Instrumentation, computer.programming_language, software architecture, Fluid Flow and Transfer Processes, lcsh:T, Process Chemistry and Technology, Software architecture, General Engineering, Swarm behaviour, 020206 networking & telecommunications, Planner, lcsh:QC1-999, Navigation, Computer Science Applications, lcsh:Biology (General), lcsh:QD1-999, lcsh:TA1-2040, swarm, Obstacle, Trajectory, 020201 artificial intelligence & image processing, lcsh:Engineering (General). Civil engineering (General), computer, lcsh:Physics |
| الوصف: | Advances in the field of unmanned aerial vehicles (UAVs) have led to an exponential increase in their market, thanks to the development of innovative technological solutions aimed at a wide range of applications and services, such as emergencies and those related to fires. In addition, the expansion of this market has been accompanied by the birth and growth of the so-called UAV swarms. Currently, the expansion of these systems is due to their properties in terms of robustness, versatility, and efficiency. Along with these properties there is an aspect, which is still a field of study, such as autonomous and cooperative navigation of these swarms. In this paper we present an architecture that includes a set of complementary methods that allow the establishment of different control layers to enable the autonomous and cooperative navigation of a swarm of UAVs. Among the different layers, there are a global trajectory planner based on sampling, algorithms for obstacle detection and avoidance, and methods for autonomous decision making based on deep reinforcement learning. The paper shows satisfactory results for a line-of-sight based algorithm for global path planner trajectory smoothing in 2D and 3D. In addition, a novel method for autonomous navigation of UAVs based on deep reinforcement learning is shown, which has been tested in 2 different simulation environments with promising results about the use of these techniques to achieve autonomous navigation of UAVs. This work was supported by the Comunidad de Madrid Government through the Industrial Doctorates Grants (GRANT IND2017/TIC-7834). |
| وصف الملف: | application/pdf |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8b90b7b399414a6e7d5fd73aee7de04 http://hdl.handle.net/10016/32840 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....b8b90b7b399414a6e7d5fd73aee7de04 |
| قاعدة البيانات: | OpenAIRE |
| الوصف غير متاح. |