Pooley Adam, Gao Max, Sharma Arushi, Barnaby Sachi, Gu Yu, Gross Jason
Department of Mechanical and Aerospace Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL 32611, USA.
Engineering (Robotics), Ira A. Fulton Schools of Engineering, Arizona State University, Tempe, AZ 85287, USA.
Biomimetics (Basel). 2023 Mar 17;8(1):124. doi: 10.3390/biomimetics8010124.
A swarm of unmanned aerial vehicles (UAVs) can be used for many applications, including disaster relief, search and rescue, and establishing communication networks, due to its mobility, scalability, and robustness to failure. However, a UAV swarm's performance is typically limited by each agent's stored energy. Recent works have considered the usage of thermals, or vertical updrafts of warm air, to address this issue. One challenge lies in a swarm of UAVs detecting and taking advantage of these thermals. Inspired by hawks, a swarm could take advantage of thermals better than individuals due to the swarm's distributed sensing abilities. To determine which emergent behaviors increase survival time, simulation software was created to test the behavioral models of UAV gliders around thermals. For simplicity and robustness, agents operate with limited information about other agents. The UAVs' motion was implemented as a Boids model, replicating the behavior of flocking birds through cohesion, separation, and alignment forces. Agents equipped with a modified behavioral model exhibit dynamic flocking behavior, including relative ascension-based cohesion and relative height-based separation and alignment. The simulation results show the agents flocking to thermals and improving swarm survival. These findings present a promising method to extend the flight time of autonomous UAV swarms.
一群无人驾驶飞行器（UAV）由于其机动性、可扩展性和对故障的鲁棒性，可用于许多应用，包括救灾、搜索和救援以及建立通信网络。然而，无人机群的性能通常受到每个个体存储能量的限制。最近的研究考虑利用热气流，即暖空气的垂直上升气流，来解决这个问题。一个挑战在于一群无人机要检测并利用这些热气流。受鹰的启发，由于群体的分布式感知能力，一群无人机比个体能更好地利用热气流。为了确定哪些涌现行为能延长生存时间，创建了模拟软件来测试无人机滑翔机围绕热气流的行为模型。为了简单和稳健起见，个体在关于其他个体的信息有限的情况下运行。无人机的运动被实现为一个Boids模型，通过凝聚、分离和对齐力来复制鸟群的行为。配备了改进行为模型的个体表现出动态的群聚行为，包括基于相对上升的凝聚以及基于相对高度的分离和对齐。模拟结果表明个体聚集到热气流处并提高了群体的生存能力。这些发现提出了一种有前景的方法来延长自主无人机群的飞行时间。
