Local histogram matching for efficient optical flow computation applied to velocity estimation on pocket drones
Kimberly McGuire (TU Delft - Control & Simulation)
Guido C.H.E.de de Croon (TU Delft - Control & Simulation)
Christophe De de Wagter (TU Delft - Control & Simulation)
BDW Remes (TU Delft - Control & Simulation)
K. Tuyls (University of Liverpool)
H. Kappen (Radboud Universiteit Nijmegen)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
Autonomous flight of pocket drones is challenging due to the severe limitations on on-board energy, sensing, and processing power. However, tiny drones have great potential as their small size allows maneuvering through narrow spaces while their small weight provides significant safety advantages. This paper presents a computationally efficient algorithm for determining optical flow, which can be run on an STM32F4 microprocessor (168 MHz) of a 4 gram stereo-camera. The optical flow algorithm is based on edge histograms. We propose a matching scheme to determine local optical flow. Moreover, the method allows for sub-pixel flow determination based on time horizon adaptation. We demonstrate velocity measurements in flight and use it within a velocity control-loop on a pocket drone.