Optic-Flow Based Slope Estimation for Autonomous Landing. Issue 4 (December 2013)

• Record Type: Journal Article
• Authors: de Croon, G.C.H.E.; Ho, H.W.; De Wagter, C.; van Kampen, E.; Remes, B.; Chu, Q.P.
• Is Part Of: International journal of micro air vehicles. Volume 5:Issue 4(2013)
• Page Start: 287
• Page End: 297
• Publication Date: 2013-12
• Subjects: Aerosonde (Drone aircraft) -- Periodicals; Aerospace engineering -- Periodicals; Aerosonde (Drone aircraft); Aerospace engineering; Periodicals; 623.746905
• DOI: 10.1260/1756-8293.5.4.287
• Languages: English
• ISSNs: 1756-8293

Abstract

Micro Air Vehicles need to have a robust landing capability, especially when they operate outside line-of-sight. Autonomous landing requires the identification of a relatively flat landing surface that does not have too large an inclination. In this article, a vision algorithm is introduced that fits a second-order approximation to the optic flow field underlying the optic flow vectors in images from a bottom camera. The flow field provides information on the ventral flow ( Vx /h ), the time-to-contact ( h/ – Vz ), the flatness of the landing surface, and the surface slope. The algorithm is computationally efficient and since it regards the flow field as a whole, it is suitable for use during relatively fast maneuvers. The algorithm is subsequently tested on artificial image sequences, hand-held videos, and on the images made by a Parrot AR drone. In a preliminary robotic experiment, the AR drone uses the vision algorithm to determine when to land in a scenario where it flies off a stairs onto the flat floor.