I-Corps: Flow-aided aerial vehicle navigation and control

这个i-Corps项目的更广泛影响是开发了延长无人机(UAV)电池寿命的技术。小型无人机已被广泛应用于包括航空摄影、运送、测量和受限空间监视在内的广泛领域。然而，小型无人机的利用率和飞行时间往往受到机载电池容量的限制，特别是在极端多风的条件下，无人机需要付出额外的努力来抑制干扰并保持健壮。该技术以最少的时间和能量穿越湍流，解决了无人机在湍流中的导航和控制问题。这项新技术可能会使更多的无人机在超出其当前能力的条件下运行，并可能使无人机在商业上更具可行性。此外，这款新产品很好地契合了目前方便、非接触、自主的无人机送货服务的趋势。开发高效的无人机在风中的导航和控制策略可能会使未来的无人机递送行业受益。这个i-Corps项目基于能量收集控制算法的开发，以延长无人机(UAV)的电池寿命。受流体力学中粒子传输理论原理的启发，拟议的技术提供了智能控制算法，使飞行器能够利用有利的流动结构，如湍流涡流、上升热流和顺风，并在高度湍流的环境中导航，而花费的时间和精力要少得多。提出了一种隐式模型跟踪(IMF)控制器，以使飞行器跟踪具有快跟踪效应的惯性粒子的动态行为，并从湍流中提取能量。给出机载流量测量，受控飞行器往往更频繁地在有利的顺风下飞行，同时自动避开不利的逆风。与现有的控制技术相比，这项技术的创新之处在于不需要事先了解准确的流动参数模型，受控飞行器可以从阵风中获取能量，而不是使用电池功率来补偿外部风干扰。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact of this I-Corps project is the development of technology to extend battery life in unmanned aerial vehicles (UAVs). Small unmanned aerial vehicles have been utilized in a wide range of fields, including aerophotography, delivery, surveying, and surveillance in confined spaces. However, the utilization and duration of flight of small UAVs is often limited by the allowed on-board battery capacity, especially in extreme windy conditions when UAVs need to make extra effort to reject disturbances and remain robust. The proposed technology solves the UAV navigation and control problems in turbulence by traversing turbulent flows using minimal time and energy. The new technology may enable more UAVs to operate in conditions beyond their current capabilities and could make UAVs more commercially viable. In addition, the new product fits well with the current trend towards convenient, contact-free, autonomous drone delivery services. The development of efficient UAV navigation and control strategies in wind may benefit the drone delivery industry in the future.This I-Corps project is based on the development of energy-harvesting control algorithms to extend battery life in unmanned aerial vehicles (UAVs). Inspired by principles from particle transport theory in fluid dynamics, the proposed technology provides intelligent control algorithms that enable the aerial vehicle to leverage beneficial flow structures, such as turbulent eddies, rising thermals, and tailwinds, and navigate in highly turbulent environments with significantly less expenditure of time and energy. An implicit model following (IMF) controller was developed to make the aerial vehicle follow the dynamic behavior of settling inertial particles undergoing the fast-tracking effect and extract energy from turbulent flows. Given on-board flow measurements, the controlled aerial vehicle tends to travel under advantageous tailwinds more often, while avoiding adverse headwinds autonomously. Compared to existing control techniques, the innovation of this technology is that prior knowledge of the exact flow parametric model is not required, and controlled aerial vehicles may harvest energy from wind gusts instead of using battery power to compensate for external wind disturbances.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.