Autonomous Quadrotor Landing on Inclined Surfaces using Perception-Guided Active Asymmetric Skids

Mark C. Lesak, United States Military Academy
Jinho Kim, United States Military Academy
Dylan Taylor, United States Military Academy
Daniel J. Gonzalez, United States Military Academy
Christopher Korpela, United States Military Academy


In this work, we present an autonomous quadrotor capable of safely landing on sloped surfaces up to 40 degrees, intended for emergency scenarios where the terrain available for landing may be sloped. This system uses a downward-facing depth perception system to determine the direction, angle, and flatness of the slope and two robotic landing skids of different lengths, that actively conform to the slope to maintain level aircraft attitude upon landing. We developed an analytical model to conform to the slope surface angle and ensure clearance of the propellers from the surface. The selection of skid angles is framed as an optimization to match the slope angle while maximizing the buffer between the propellers and the surface. An eigenvalue decomposition of the point cloud covariance matrix provides a surface normal vector, which is used to determine the proper skid angle and heading of the quadrotor. The ratio of the eigenvalues is used to determine whether the surface is sufficiently flat for safe landing. The proposed system and method were validated in a motion capture environment by conducting five autonomous takeoff and land missions over different sloped surfaces ranging from 0 to 40 degrees.The detected slope angle and direction of all trials are within 1 and 3.3 degrees, respectively of ground truth and no failures or crashes occurred during testing, which demonstrates the viability and robustness of this system to be used in real-world scenarios.