Evaluation of Safe Landing Area Determination Algorithms for Autonomous Rotorcraft Using Site Benchmarking

Abstract

An important element of rotorcraft UAV operations is safe landing area determination (SLAD), which is the ability to select desirable landing or load placement areas at unprepared sites. Effectively and reliably accomplishing this task would greatly enhance high-level autonomous capabilities in many operations such as search and rescue and resupply. This paper presents the results of quantitatively evaluating two SLAD algorithms using a new test method that incorporates a detailed survey of the test sites. These survey sites act as benchmarks against which the SLAD methods are compared. One SLAD algorithm is a new approach that uses laser range data to detect a set of potential landing points and uses fuzzy logic to rank them based on surface roughness, size, and terrain slope metrics. The second algorithm uses laser range data to optimize a performance index, based on sliding window statistics of surface slope and roughness over the landing zone, to select potential landing points. Flight-test data were collected at six sites ranging from simple to complex with multiple runs at each site. Both methods are evaluated based on their true-positive and false-positive rates and the consistency of their landing site selection.

Rotorcraft Hard Landing Mitigation Using Robotic Landing Gear

“…Hard landings can occur due to several factors, including poor weather conditions, poor visibility, over-loaded aircraft, mechanical/electrical failures, and pilot error. Research has been performed to mitigate the effects of restricted visibility on the pilot's ability to operate the aircraft [1][2][3][4][5]. Coltman, Bolukbasi, and Laananen examined the causes of over 1000 rotorcraft crashes within a 5-yr period [6].…”

Real-time landing place assessment in man-made environments

“…Many methods have been proposed for the assessment of 3D surface geometry from active range sensors [23,27,40,47]. Johnson et al [27] propose a hazard map estimation framework using estimates of surface slope and roughness from laser scanner range measurements.…”

“…They typically have a restricted operational range of 1km or less, require additional safety considerations in populated areas, and often involve a costly, time consuming acquisition process making them unsuitable for the applications we target [40,47].…”

“…Active sensors have been widely used for this purpose [23,41,26,47,40] but have severe drawbacks. They are expensive, power-hungry, and often heavy.…”

Simulation Experiment on Landing Site Selection Using a Simple Geometric Approach

“…For the ultimately quantitatively evaluating the most suitable landing site, a performance index (Takahashi et al, 2013) incorporating slope index, roughness index and the radius of the inscribed circle on each candidate site will be computed. Finally, the site with the lowest performance index is the recommend landing point.…”