Paper
17 May 2016 Automatic construction of aerial corridor for navigation of unmanned aircraft systems in class G airspace using LiDAR
Dengchao Feng, Xiaohui Yuan
Author Affiliations +
Abstract
According to the airspace classification by the Federal Aviation Agency, Class G airspace is the airspace at 1,200 feet or less to the ground, which is beneath class E airspace and between classes B-D cylinders around towered airstrips. However, the lack of flight supervision mechanism in this airspace, unmanned aerial system (UAS) missions pose many safety issues. Collision avoidance and route planning for UASs in class G airspace is critical for broad deployment of UASs in commercial and security applications. Yet, unlike road network, there is no stationary marker in airspace to identify corridors that are available and safe for UASs to navigate. In this paper, we present an automatic LiDAR-based airspace corridor construction method for navigation in class G airspace and a method for route planning to minimize collision and intrusion. Our idea is to combine LiDAR to automatically identify ground objects that pose navigation restrictions such as airports and high-rises. Digital terrain model (DTM) is derived from LiDAR point cloud to provide an altitude-based class G airspace description. Following the FAA Aeronautical Information Manual, the ground objects that define the restricted airspaces are used together with digital surface model derived from LiDAR data to construct the aerial corridor for navigation of UASs. Preliminary results demonstrate competitive performance and the construction of aerial corridor can be automated with much great efficiency.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dengchao Feng and Xiaohui Yuan "Automatic construction of aerial corridor for navigation of unmanned aircraft systems in class G airspace using LiDAR", Proc. SPIE 9828, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications XIII, 98280I (17 May 2016); https://doi.org/10.1117/12.2224359
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CITATIONS
Cited by 9 scholarly publications.
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KEYWORDS
LIDAR

Safety

Data modeling

Navigation systems

Visualization

Image filtering

Clouds

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