Software Architecture for Autonomous and Coordinated Navigation of UAV Swarms in Forest and Urban Firefighting

Applied Sciences

Pablo Flores¹  Ángel Madridano²  Abdulla Al-Kaff²  David Martín²  Arturo de la Escalera² 

[1] Drone Hopper S.L., Avenida Gregorio Peces-Barba, 28919 Leganés, Madrid, Spain;Intelligent Systems Lab (LSI), Universidad Carlos III de Madrid, Avenida Universidad 30, 28911 Leganés, Madrid, Spain;

关键词: UAVs;    swarm;    autonomous;    navigation;    software architecture;   

DOI  :  10.3390/app11031258

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown