  A collision avoidance system based on simple digital cameras would help
enable the safe integration of small UAVs into crowded, low-altitude
environments. In this work, we present an obstacle avoidance system for small
UAVs that uses a monocular camera with a hybrid neural network and path planner
controller. The system is comprised of a vision network for estimating depth
from camera images, a high-level control network, a collision prediction
network, and a contingency policy. This system is evaluated on a simulated UAV
navigating an obstacle course in a constrained flight pattern. Results show the
proposed system achieves low collision rates while maintaining operationally
relevant flight speeds.
