Abstract
In this work, a Detect and Avoid system is presented for the autonomous navigation of Unmanned Aerial Vehicles (UAVs) in Urban Air Mobility (UAM) applications. The current implementation is designed for the operation of multirotor UAVs in UAM corridors. During the operations, unauthorized flying objects may penetrate the corridor airspace posing a risk to the aircraft. In this article, the feasibility of using a solid-state LiDAR (Light Detecting and Ranging) sensor for detecting and positioning these objects was evaluated. For that purpose, a commercial model was simulated using the specifications of the manufacturer along with empirical measurements to determine the scanning pattern of the device. With the point clouds generated by the sensor, the system detects the presence of intruders and estimates their motion to finally compute avoidance trajectories using a Second Order Cone Program (SOCP) in real time. The method was tested in different scenarios, offering robust results. Execution times were of the order of 50 milliseconds, allowing the implementation in real time on modern onboard computers.
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