ABSTRACT
At Skydio, we ship autonomous robots that are flown at scale in complex, unknown environments every day by our customers to capture incredible video, automate dangerous inspections, build digital twins, and save lives of first responders. These robots operate intelligently and make decisions at high speed using just their onboard cameras and algorithms on consumer-grade hardware.
We’ve invested six years of R&D into handling extreme visual scenarios not typically considered by academia nor encountered by cars, ground robots, or AR applications. Drones are commonly in scenes with few or no semantic priors on the environment and must deftly navigate thin objects, extreme lighting, camera artifacts, motion blur, textureless surfaces, vibrations, dirt, smudges, and fog. These challenges are daunting for classical vision, because photometric signals are simply inconsistent. And yet, there is no ground truth for direct supervision of deep networks. We’ll take a detailed look at these issues and how we’ve tackled them to push the state of the art in visual inertial navigation, obstacle avoidance, rapid trajectory planning.
We will also cover the new capabilities on top of our core navigation engine to autonomously map complex scenes and capture all surfaces, by performing real-time 3D reconstruction across multiple flights.