Monocular distance estimation from optic flow during active landing maneuvers

Floris van Breugel; Kristi Morgansen; Michael H Dickinson

doi:10.1088/1748-3182/9/2/025002

Bioinspiration & Biomimetics

Paper • The following article is Open access

Monocular distance estimation from optic flow during active landing maneuvers

Floris van Breugel¹, Kristi Morgansen² and Michael H Dickinson²

Published 22 May 2014 • © 2014 IOP Publishing Ltd
Bioinspiration & Biomimetics, Volume 9, Number 2 Citation Floris van Breugel et al 2014 Bioinspir. Biomim. 9 025002 DOI 10.1088/1748-3182/9/2/025002

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Supplementary data

Movie. Real time performance of the dynamic peering estimation algorithm. The video shows the data from figures 4 and 5 as an animation. Bottom left: Camera image sequence showing the visual target and region of interest (red box). Bottom right: Optic flow as a function of camera pixel calculated using the current and previous frames using OpenCV's Lucas Kanade algorithm. For the purposes of control, we calculated a linear fit of the data (red line) over the region of interest. Top row: Dynamic peering performance (red) compared with the ground-truth values (blue) for position, velocity, and optic flow estimates, as well as the applied control effort. After an initial period where the robot accelerates to the steady state optic flow rate of -0.1 1/s, the estimates lock on to the actual values. (23.7 MB MOV)

Monocular distance estimation from optic flow during active landing maneuvers

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