控制自主飞行器运输医疗用品

Ricardo Yauri, Santiago Fernandez, Anyela Aquino
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引用次数: 0

摘要

公共卫生监控必须通过限制人的流动来保证人们的安全,在隔离的情况下,通过产品交付,有必要使用无人机来保证安全,因为无人机在多个领域发挥着至关重要的作用。文献综述强调了使用无人机进行家庭自动化送货的益处,重点是时间效率和各行业的竞争力,并提供了关键的设计参数,以确保在城市地区使用不同的控制技术来实施。该方案旨在实现无人机在飞行过程中形成的蜂窝状设计,由模拟环境中的飞行和交付算法控制,采用迭代方法和连续运输测试。结果表明,在成功创建模拟地形方面取得了质的飞跃,但由于缺乏有关起飞和着陆的数字数据,因此需要进行更多的定量测量。目前的结果支持无人机在路线规划、精确管理医疗货物和缩短运送时间方面的效率,这些数字证据加强了该解决方案的稳健性。总之,本研究开发了一个功能原型,利用飞行规划算法和蜂群编队系统控制无人机,用于在城市环境中运输医疗用品。
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Control of Autonomous Aerial Vehicles to Transport a Medical Supplies
Public health surveillance must guarantee the safety of people by limiting human mobility, in cases of isolation, through product deliveries, making it necessary to use drones to guarantee safety because they play a crucial role in several sectors. The literature review highlights the benefits of automation in-home delivery using drones, focusing on time efficiency and competitiveness in various sectors, and provides crucial design parameters to ensure its implementation in urban areas using different control techniques. A contribution was proposed to a solution that aims to realize the honeycomb design, which drones create during flight, controlled by a flight and delivery algorithm in a simulation environment applying an iterative methodology and continuous transport tests. medical burden. The results indicate a qualitative advance in the successful creation of simulated terrain, although the lack of numerical data on takeoffs and landings suggests the need for additional quantitative measurements. The current results support the efficiency of drones in route planning, precise management of medical cargo, and reduction of delivery time is numerical evidence that reinforces the robustness of the solution. In conclusion, this study developed a functional prototype to control drones with a flight planning algorithm and a swarm formation system for the transport of medical supplies in urban environments, although the need for future research to implement artificial intelligence technologies is noted. that improve transportation efficiency.
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