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.

Survey of approaches for emergency landing spot detection with unmanned aerial vehicles

“…A navigation system proposed by Chamberlain et al 19 allows a full-scale unmanned helicopter to fly through unmapped terrain, detect and perform a safe landing without human control or input. Their algorithm is described in Scherer et al [20][21][22] and consists of two evaluation steps based on geometrical features. The first step, labeled coarse evaluation, takes a 3-D point cloud registered in global coordinates as input to build a grid map in which each cell contains points and statistical information, such as mean, minimum and maximum height, number of points.…”

Emergency Landing Spot Detection for Unmanned Aerial Vehicle

“…This approach is extended in [24,25,26] by applying a plane fit and presenting experimental results in urban and natural environments. The algorithm applies two evaluation based on geometrical features: a coarse evaluation to identify potential landing sites and a fine evaluation to choose the optimum spot.…”

Infrastructure-free shipdeck tracking for autonomous landing

“…Systems to detect and track a landing pattern have been developed before [9], our particular approach is different in that it can be adapted to any particular pattern because the image and lidar based algorithms are generic in nature, just needing a template as input. The presented solution facilitates autonomous operation on land with visual and range sensing providing with the necessary data for finding [8] and evaluating landing sites [10] while avoiding obstacles.…”