LiDAR Based Detect and Avoid System for UAV Navigation in UAM Corridors

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.

Enabling Technologies for the Navigation and Communication of UAS Operating in the Context of BVLOS

“…The realization of efficient and cost-effective drone delivery applications can be facilitated by a combination of Commercial Off-The-Shelf (COTS) technologies and systems, possibly sourced from other industries. Moreover, integration with existing planning and flight management infrastructures in the concept of Urban Air Mobility (UAM) [12] and incorporating established aviation technologies such as the integration of the ADS-B (Automatic Dependent Surveillance-Broadcast) surveillance protocol ensures compatibility with existing airspace users and the safety of operations [13]. BVLOS demands levels of autonomy and collaboration that have hither to only been seen in the autonomous vehicle market.…”

“…Such systems are based on the use of sensors to detect and position obstacles to subsequently establish maneuvers to guarantee the safety of the aircraft. Many recent works implement LiDAR (Light Detecting And Ranging), vision cameras, or thermal or infrared cameras for collision avoidance of UAS [13,22].…”

Securing Your Airspace: Detection of Drones Trespassing Protected Areas

“…Furthermore, in another study [132] proposed by Aldao et al, a detect and avoid system for UAV navigation in Urban Air Mobility (UAM) corridors is introduced, utilizing a solid-state LiDAR sensor for detecting and positioning unauthorized flying objects within corridor airspace. Their proposed system, leveraging point clouds generated by the sensor and a Second Order Cone Program (SOCP), computes real-time avoidance trajectories.…”

Optimal Multi-Sensor Obstacle Detection System for Small Fixed-Wing UAVs

“…It is important to note that most research in this field focuses on multirotor UAVs. Among these, solutions typically include cameras [15], LIDAR technology [16], or both [17]. That was not the case for the solution presented in [18], where the solution was specifically designed to map indoor spaces with planar structures through graph optimization.…”