State Estimation for Agile Quadrotors in the Wild

In this extended abstract, we present our latest research in robust state estimation for agile quadrotor flight. We discuss the differences between discrete- and continuous- time trajectory representations in visual-inertial odometry (VIO). Then, we present a novel VIO algorithm that combines events and standard frames to estimate the pose of a quadrotor subject to a rotor failure. Finally, we discuss our recent progress in learned inertial odometry for quadrotor flight. We conclude with the next research directions that have the potential to improve the robustness of onboard state estimation systems for autonomous drones.