Online Assessment of Landing Sites

Abstract

Assessing a landing zone (LZ) reliably is essential for safe operation of vertical takeoff and landing (VTOL) aerial vehicles that land at unimproved locations. Currently an operator has to rely on visual assessment to make an approach decision; however. visual information from afar is insufficient to judge slope and detect small obstacles. Prior work has modeled LZ quality based on plane fitting, which only partly represents the interaction between vehicle and ground. Our approach consists of a coarse evaluation based on slope and roughness criteria, a fine evaluation for skid contact, and body clearance of a location. We investigated whether the evaluation is correct for using terrain maps collected from a helicopter. This paper defines the problem of evaluation, describes our incremental real-time algorithm, and discusses the effectiveness of our approach. In results from urban and natural environments, we were able to successfully classify LZs from point cloud maps collected on a helicopter. The presented method enables detailed assessment of LZs without an landing approach, thereby improving safety. Still, the method assumes low-noise point cloud data. We intend to increase robustness to outliers while still detecting small obstacles in future work.