Towards More Autonomous and Safer Unmanned Aerial Vehicle Systems

迈向更自主、更安全的无人机系统

• 批准号: RGPIN-2020-06608
• 负责人: Saussié, David
• 金额: $ 2.33万
• 依托单位: École Polytechnique de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=754028
• 关键词: Towards; More; Autonomous; Safer; Unmanned

Over the past decade, unmanned aerial vehicles (UAVs) have experienced a real boom with a multiplication of their applications in everyday life: aerial photography, infrastructure inspection, agricultural land monitoring and probably automated parcel delivery in the near future. Even if these UAVs have a certain appeal, their level of autonomy is still limited, and the presence of an operator to perform certain manoeuvres is often necessary. A particularly interesting area for many applications is then the completely autonomous take-off and landing, especially on mobile vehicles travelling at high speed. In this vein, our research group's participation in the DJI Challenge 2016 led to the autonomous landing of a drone on a vehicle at speeds of up to 50 km/h, which remains a record to date. The long-term objective of this research program is to make drones safer and more autonomous in order to diversify their applications. To this end, this discovery grant focuses in particular on the take-off and landing phases of drones, and their complete automation. Thanks to the experience acquired by my group, we wish to expand our knowledge in the field and improve the guidance, navigation and control algorithms currently available. For the short-term objectives, we will study the following three themes: (1) high-fidelity modelling of a drone moving at high speed and its behaviour in the wake of a mobile vehicle; (2) the use of bidirectional thrust to increase the agility of multicopters and make the most of their flight envelope; and (3) means for estimating the relative position of the drone in relation to the mobile vehicle, and the take-off, approach and landing algorithms that will use bidirectional thrust. Advances in these three themes will expand the capabilities of drones and improve their autonomy. The research conducted will have a significant impact on the scientific community and the UAV industry, which will be able to offer more efficient solutions or use these results in their own applications. At present, the training of highly qualified personnel in this field is essential. With a growing market, the sector needs more and more experts: this research program will train people with advanced theoretical knowledge and practical experience acquired in our laboratory.

在过去的十年中，无人驾驶飞行器（uav）经历了真正的繁荣，它们在日常生活中的应用成倍增加：航空摄影，基础设施检查，农业用地监测，可能在不久的将来自动包裹递送。即使这些无人机具有一定的吸引力，它们的自主水平仍然有限，并且操作员的存在执行某些操作通常是必要的。对于许多应用来说，一个特别有趣的领域是完全自主的起飞和降落，特别是在高速行驶的移动车辆上。本着这种精神，我们的研究小组参加了2016年大疆挑战赛，使无人机以高达50公里/小时的速度自动降落在车辆上，这是迄今为止的记录。这项研究计划的长期目标是使无人机更安全，更自主，以使其应用多样化。为此，这项发现拨款特别侧重于无人机的起飞和降落阶段，以及它们的完全自动化。由于我们小组获得的经验，我们希望扩大我们在该领域的知识，并改进现有的制导，导航和控制算法。对于短期目标，我们将研究以下三个主题：(1)高速移动的无人机的高保真建模及其在移动车辆后的行为；(2)利用双向推力增加多旋翼机的敏捷性，充分利用其飞行包线；(3)估计无人机相对于移动车辆的相对位置的方法，以及使用双向推力的起飞、进近和着陆算法。这三个主题的进展将扩大无人机的能力并提高其自主性。所进行的研究将对科学界和无人机行业产生重大影响，他们将能够提供更有效的解决方案或将这些结果用于自己的应用。目前，培训这一领域的高素质人员是必不可少的。随着市场的不断发展，该领域需要越来越多的专家：这个研究项目将培养具有先进理论知识和在我们实验室获得的实践经验的人才。