Skydio is the leading US drone company and the world leader in autonomous flight. Our drones are used for everything from capturing amazing video, to inspecting bridges, to tracking progress on construction sites.
At the core of our products is a vision-based autonomy system with seven years of development at Skydio, drawing on decades of academic research. This system pushes the state of the art in deep learning, geometric computer vision, motion planning, and control with a particular focus on real-world robustness.
Drones encounter extreme visual scenarios not typically considered by academia nor encountered by cars, ground robots, or AR applications. They are commonly flown in scenes with few or no semantic priors and must deftly navigate thin objects, extreme lighting, camera artifacts, motion blur, textureless surfaces, and water. These challenges are daunting for classical vision because photometric signals are simply not consistent, and for learning-based methods because there is no ground truth for direct supervision of deep networks. In this talk we'll take a detailed look at our approaches to these problems.
We will also discuss new capabilities on top of our core navigation engine to autonomously map complex scenes and build high quality digital twins, by performing real-time 3D reconstruction across multiple flights. Our vision-based 3D Scan approach allows anyone to build millimeter-scale maps of the world.
Registration is required to attend. The talks will be presented via Zoom, and you will receive a Zoom meeting URL when you register for the presentation.
Bio: Hayk was the first engineering hire at Skydio and he leads the autonomy team. He is an experienced roboticist who develops robust approaches to computer vision, deep learning, nonlinear optimization, and motion planning to bring intelligent robots into the mainstream. His team's state-of-the-art work in UAV visual navigation of complex scenarios is at the core of every Skydio drone. He also has a deep interest in systems architecture and symbolic computation. His previous works include novel hexapedal robots, collaboration between robot arms, micro-robot factories, solar panel farms, and self-balancing motorcycles. Hayk is a graduate of Stanford University and Princeton University.