IROS 2016poster17 citations
Self-supervised monocular distance learning on a lightweight micro air vehicle
Kevin Lamers, Sjoerd Tijmons, Christophe De Wagter, Guido de Croon
Abstract
Obstacle detection by monocular vision is challenging because a single camera does not provide a direct measure for absolute distances to objects. A self-supervised learning approach is proposed that combines a camera and a very small short-range proximity sensor to find the relation between the appearance of objects in camera images and their corresponding distances. The method is efficient enough to run real time on a small camera system that can be carried onboard a lightweight MAV of 19 g. The effectiveness of the method is demonstrated by computer simulations and by experiments with the real platform in flight.
BibTeX
@inproceedings{iros2016_selfsupervisedmo,
title = {Self-supervised monocular distance learning on a lightweight micro air vehicle},
author = {Kevin Lamers and Sjoerd Tijmons and Christophe De Wagter and Guido de Croon},
booktitle = {IROS 2016},
year = {2016}
}