A keyframe based inertial-visual navigation system for a commercial UAS autopilot

无人驾驶飞行器(UAV)或无人驾驶航空系统(UAS)在自然资源监测、基础设施检查(管道、铁路)、农业、矿产勘探、新闻和搜救行动等领域有着巨大的应用前景。这是航空航天行业中最具活力的领域，增长速度比其他任何领域都要快。在许多潜在的应用中，小型无人机具有机动性、通用性和便携性的优势，但面临着功率和有效载荷有限的挑战。此外，许多系统在自主运行时依赖全球导航卫星系统(GNSS)进行制导、导航和控制，但这给GNCC覆盖不可靠甚至不可用的地区带来了限制。另一方面，小巧节能的数码相机 它们正被广泛用作主要传感器，因为它们非常适合这些小型车辆施加的严格功率和有效载荷限制。探索基于视觉的导航作为替代解决方案是很自然的。 在与MicroPilot公司的这项拟议的Engage项目中，我们的目标是开发一种与MicroPilot的商业自动驾驶仪集成的惯性视觉辅助导航系统。它实现了一种基于关键帧的同步定位与映射(SLAM)算法，该算法具有万向架控制摄像机的新特性。 综上所述，提出的基于图像和万向节控制摄像机的视觉算法提供了一种新颖的、计算高效的系统，使无人机飞行任务中能够实现自主导航。该技术将与MicroPilot自动驾驶仪集成，并实施到MicroPilot直升机无人机上进行技术演示。

Unmanned aerial vehicles (UAVs) or unmanned aerial systems (UAS) hold great promise for applications as diverse as natural resource monitoring, infrastructure inspection (pipeline, railways), agriculture, mineral exploration, journalism, and search & rescue operations. This is the most vibrant sector of the aerospace industry, growing more quickly than any other segment. In many potential applications, small scaled UAVs or UAS have the advantage of maneuverability, versatility and portability but face the challenge of limited power and payload. In addition, many systems rely on global navigation satellite systems (GNSS) for guidance, navigation and control in their autonomous operation, however it brings restrictions to regions where GNCC coverage is unreliable or even not available. On the other hand, compact and energy-efficient digital cameras are becoming widely used as the primary sensor as they are well suited to the stringent power and payload restrictions imposed by these small vehicles. It is natural to explore vision-based navigation as an alternative solution. In this proposed Engage project with Micropilot Inc., we aim at developing an inertial-visual assisted navigation system integrated with Micropilot's commercial autopilot. It implements a promising keyframe based simultaneous localization and mapping (SLAM) algorithm with a novel feature of gimbal controlled camera. In summary, the proposed image-based visual algorithm with gimbal controlled camera provides a novel and computationally efficient system that enables autonomous navigation in UAV flight missions. The technique will be integrated with the Micropilot autopilot and implemented to a Micropilot Helicopter UAV for technical demonstration.