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

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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.