Skydio, the leading U.S. drone manufacturer and world leader in autonomous flight technology, today announced the expansion of its world-class autonomy team with the hiring of four top PhD graduates from the Robotics and Perception Group led by Prof. Davide Scaramuzza at the University of Zurich, and the High Performance Robotics Lab led by Prof. Mark Mueller at UC Berkeley.

Together, Davide FalangaNathan BuckiPhilip Foehn, and Elia Kaufmann bring an incredible wealth of experience building cutting-edge flying robots that push the limits of agile maneuvering, tightly couple perception and planning, and physically interact with their environment. Davide, Nathan, Philipp, and Elia will augment Skydio’s world-class motion planning team, led by Jack Zhu.

“We are thrilled to welcome these excellent researchers and engineers to the Motion Planning team! Our group builds and maintains the systems that generate and execute collision-free drone motions through complex environments. To do this, we use a carefully selected arrangement of numerical optimization methods, fast code, and accurate physics models,” said Zhu. “Our team has strong roots in the academia of flying robots, which puts us in a unique position to apply novel ideas from the forefront of robotics research directly into robust, real-world products. We are looking forward to working with these four talented team members to push our vehicles’ performance to their full capabilities — and have a ton of fun while doing it.”

Davide Falanga

Davide Falanga completed his PhD at the Robotics and Perception Group, developing techniques to exploit motion planning and control to cope with the limitations of onboard sensors for high-speed, agile flight with small-scale, lightweight, vision-based autonomous quadrotors.

“I decided to join Skydio to make robots as impactful as possible on our world and the society we live in,” said Falanga. “I want to solve challenging problems that push the boundaries of the state of the art and contribute to maximizing the impact that autonomous robots can have on everyone’s life, starting from today, in a meaningful way.”

Nathan Bucki

Nathan Bucki graduated with a PhD from the High Performance Robotics Lab, focused on novel quadcopter designs, computationally efficient planning algorithms, and efficient online model learning.

“I joined Skydio for two main reasons: their incredibly bright engineering team and their commitment to advancing the capabilities of autonomous robots,” said Bucki. “As a graduate student I was amazed by what Skydio has been able to achieve in the domains of perception, planning, and control, and am incredibly excited to push the innovation in these areas even further.”

Philipp Foehn

Philipp Foehn joins Skydio after completing a PhD at the Robotics and Perception Group focused on autonomous drone racing, where he has demonstrated autonomous drone performance that exceeds expert drone pilots.

“I encountered Skydio for the first time when I was attending a conference on robotics during my PhD, and I was stunned by their team, knowledge, and product. I felt like I found people who share my passion for technology and elegant solutions,” said Foehn. “As a person working in research on similar topics, I was time and time amazed by the autonomy Skydio’s drones achieve and the level of robustness at which they do so.”

Elia Kaufmann

Elia Kaufmann is a PhD candidate at the Robotics and Perception Group working at the intersection of control, machine learning, and computer vision for robotics applications. He demonstrated end-to-end learned policies for high-speed autonomous flight through challenging environments and aerial acrobatics. “At Skydio, I can work at the forefront of aerial robotics and develop algorithms for the next generation of drones”, notes Kaufmann. “I’m proud to become a member of a world-class team of researchers and engineers and change the future of aerial robotics.”

To learn more:

AI Drone faster than Humans? Time-Optimal Planning for Quadrotor Waypoint Flight

AlphaPilot: Autonomous Drone Racing (RSS 2020)

Learning High-Speed Flight in the Wild (Science Robotics, 2021)

Deep Drone Acrobatics (RSS 2020)

Dynamic Obstacle Avoidance for Quadrotors with Event Cameras (Science Robotics 2020)

The Foldable Drone: A Morphing Quadrotor that can Squeeze and Fly

PAMPC: Perception-Aware Model Predictive Control for Quadrotors

Design and Control of a Midair Reconfigurable Quadcopter using Unactuated Hinges

Agile Drone Flight through Narrow Gaps with Onboard Sensing and Computing

RAPPIDS: A Fast Planner for Multicopter Navigation

By Press