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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.
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Networked Radar Systems for Cooperative Tracking of UAVs
To grant unmanned aerial vehicles (UAVs) greater access to the National Airspace System (NAS), a reliable system to detect and track them must be established. This paper combines multiple radar systems into a single network to provide tracking of UAVs across a wide area. Each radar detects the UAV’s path and those detections are combined using a recursive random sample consensus (R-RANSAC) algorithm. Outdoor flight experiments show the ability of the system
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- Award ID(s):
- 1727010
- PAR ID:
- 10110506
- Date Published:
- Journal Name:
- 2019 International Conference on Unmanned Aircraft Systems (ICUAS)
- Page Range / eLocation ID:
- 1 to 7
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ICUAS.2019.8797749
