STTR Phase I: Autonomous Landing of sUAS onto Moving Platforms

该项目的更广泛影响/商业潜力是将自主无人机系统（UAS或无人机）扩展到新的海上操作环境和商业市场。拟议的技术将使小型无人机能够在海上移动的船只上操作，而不需要专门的飞行员或安装硬件，即使在远离海岸和现有通信网络覆盖范围之外。小型无人机可以提供与有人驾驶直升机相同的空中视角，其尺寸、成本和风险都只有直升机的一小部分。来自UAS的实时空中图像将为海上操作员提供有关海上环境的宝贵信息，这是其他任何方式都无法获得的。这些信息对许多海事应用至关重要，包括捕鱼、海洋监测、科学探索、海上监视、搜索和救援。这一信息将通过大幅降低燃料成本，对全球98%的商业渔船（那些不携带载人直升机进行捕鱼的渔船）产生特别大而直接的影响；为行业提供净经济和环境收益。这项小型企业技术转让（STTR）第一阶段项目将开发算法和软件，使小型无人机能够自主、可靠地降落在海上移动平台上。商用小型无人机可以为海上运营商提供宝贵的实时航空图像。但是，由于技术壁垒，该技术目前尚未得到广泛应用。特别是，关键的使能技术是自主可靠地将小型无人机降落到移动平台上的能力。研究目标是开发算法和软件，使小型无人机能够在海上移动的船只上自主操作。计算机视觉算法自动检测主船和专用着陆区域。数据融合算法实时估计无人机与船的相对位置和方向，包括对船侧倾、俯仰和升沉的补偿。精密控制算法优化无人机？S弹道，节省，可靠，自主发射和着陆。将通过集成sttr开发的软件和商用硬件组件来构建原型系统。

The broader impact/commercial potential of this project is the expansion of autonomous unmanned aerial systems (UAS, or drones) to new maritime operational environments and commercial markets. The proposed technology will enable small UAS to operate from vessels moving at sea, without the need for a dedicated pilot or installed hardware, even while far from shore and beyond the reach of established communication networks. Small UAS can offer the same aerial perspective provided by manned helicopters at a fraction of the size, cost, and risk. Real-time aerial imagery from UAS will supply maritime operators with invaluable information about their surroundings at sea, which is not available by any other means. This information is critical for many maritime applications, including fishing, ocean monitoring, scientific exploration, maritime surveillance, and search, and rescue. This information will offer a particularly large and immediate impact for 98% of worldwide commercial fishing vessels (those that do not carry embarked manned helicopters for fish-finding) by dramatically reducing their fuel costs; providing net economic and environmental gains for the industry.This Small Business Technology Transfer (STTR) Phase I project will develop algorithms and software to enable small UAS autonomously and reliably land onto a moving platform at sea. Commercially-available small UAS can offer invaluable real-time aerial imagery for maritime operators. But, this technology is not currently in widespread use due to technological barriers. In particular, the key enabling technology is the ability to autonomously and reliably land a small UAS onto a moving platform. The research objective is to develop algorithms and software that enable small UAS to autonomously operate from moving vessels at sea. Computer vision algorithms automatically detect the host vessel and the dedicated landing area. Data fusion algorithms estimate the relative drone-boat position and orientation in real time, including compensation for vessel roll, pitch, & heave. Precision control algorithms optimize the drone?s trajectory for save, reliable, autonomous launch and landing. A prototype system will be built by integrating the STTR-developed software with commercially available hardware components.