Robust Autonomous Landing of Multirotor Unmanned Aerial Vehicles on Static and Moving Platforms

自主无人机因其灵活性和快速部署在各个行业领域变得越来越受欢迎，并在搜索和救援、检查和测绘等应用中证明了其实用性。我们在自主无人机操作方面的新研究方向是在静态和移动的风平台上实现无人机与地面车辆（卡车）或船舶的集成。这将导致快递服务、农业、搜救、检查、边境控制和海上行动方面的科学突破和实践创新。目前，无人机不具备在足够小的着陆区域重复着陆的能力，无法实现稳健的卡车或舰载作战。该项目的目标是开发新的建模、状态估计和控制方法，以实现无人机的精确和一致着陆，特别是在风力条件下，最终实现在卡车货床和船舶等移动平台上的自动着陆。本项目包括四个研究支柱：(1)气动建模，建立精确的多旋翼无人机飞行数学模型，特别是在紊流风条件下；(2)状态估计，使无人机在飞行过程中能够估计风对无人机的影响；(3)运动规划，在考虑风影响和着陆平台任意运动的情况下，自动找到在移动平台上降落的最佳路径；(4)飞行控制，确保无人机对风条件和着陆平台运动的快速响应。密切跟踪无人机成功着陆的最佳着陆路径。算法的有效性将通过实际飞行实验进行评估。该项目将帮助加拿大保持其在该领域的关键作用，并将导致短程交付的创新。

Autonomous drones are becoming more and more popular in various industry sectors for their flexibility andfast deployment and have demonstrated usefulness in applications such as search and rescue, inspection, andmapping. Our new research direction in autonomous drone operations is robust autonomous landing on staticand moving platforms in wind to enable the integration of drones with ground vehicles (trucks) or ships. Thiswill lead to scientific breakthroughs and practical innovations in delivery services, agriculture, search andrescue, inspections, border control, and maritime operations.Presently, drones do not have the capability to land repeatably in a small-enough landing zone to enable robusttruck- or ship-based operations. This project's goal is to develop new modeling, state estimation, and controlmethods for the precise and consistent landing of drones particularly in wind, ultimately enabling automatedlanding on moving platforms such as truck cargo beds and ships.This project consists of four research pillars: (1) aerodynamic modeling to develop accurate mathematicalmodels of multi-rotor drone flight, especially in turbulent wind conditions, (2) state estimation to enableestimation of wind effects on the drone during flight, (3) motion planning to automatically find the optimalpath to land on a moving platform while considering wind effects and arbitrary motion of the landing platform,and (4) flight control to ensure drones' fast response to wind conditions and motion of landing platform, andclose following of the optimal landing path for successful drone landing.The effectiveness of the algorithms will be evaluated through real-world flight experiments. Thisproject will help Canada to maintain its key role in this sector and will lead to innovation in short-hop delivery.