Title: Autonomous drone cinematographer: Using artistic principles to create smooth, safe, occlusion-free trajectories for aerial filming,
Abstract: Autonomous aerial cinematography has the potential to enable automatic
capture of aesthetically pleasing videos without requiring human intervention,
empowering individuals with the capability of high-end film studios. Current
approaches either only handle off-line trajectory generation, or offer
strategies that reason over short time horizons and simplistic representations
for obstacles, which result in jerky movement and low real-life applicability.
In this work we develop a method for aerial filming that is able to trade off
shot smoothness, occlusion, and cinematography guidelines in a principled
manner, even under noisy actor predictions. We present a novel algorithm for
real-time covariant gradient descent that we use to efficiently find the
desired trajectories by optimizing a set of cost functions. Experimental
results show that our approach creates attractive shots, avoiding obstacles and
occlusion 65 times over 1.25 hours of flight time, re-planning at 5 Hz with a
10 s time horizon. We robustly film human actors, cars and bicycles performing
different motion among obstacles, using various shot types.