BatMobility: Towards Flying Without Seeing for Autonomous Drones
Emerson Sie Zikun Liu Deepak Vasisht
Unmanned aerial vehicles (UAVs) rely on optical sensors such as cameras and
lidar for autonomous operation. However, such optical sensors are error-prone
in bad lighting, inclement weather conditions including fog and smoke, and
around textureless or transparent surfaces. In this paper, we ask: is it
possible to fly UAVs without relying on optical sensors, i.e., can UAVs fly
without seeing? We present BatMobility, a lightweight mmWave radar-only
perception system for UAVs that eliminates the need for optical sensors.
BatMobility enables two core functionalities for UAVs -- radio flow estimation
(a novel FMCW radar-based alternative for optical flow based on
surface-parallel doppler shift) and radar-based collision avoidance. We build
BatMobility using commodity sensors and deploy it as a real-time system on a
small off-the-shelf quadcopter running an unmodified flight controller. Our
evaluation shows that BatMobility achieves comparable or better performance
than commercial-grade optical sensors across a wide range of scenarios.