This paper proposes a low-level visual navigation algorithm to improve visual localization of a mobile robot. The algorithm, based on artificial potential fields, associates each feature in the current image frame with an attractive or neutral potential energy, with the objective of generating a control action that drives the vehicle towards the goal, while still favoring feature rich areas within a local scope, thus improving the localization performance. One key property of the proposed method is that it does not rely on mapping, and therefore it is a lightweight solution that can be deployed on miniaturized aerial robots, in which memory and computational power are major constraints. Simulations and real experimental results using a mini quadrotor equipped with a downward looking camera demonstrate that the proposed method can effectively drive the vehicle to a designated goal through a path that prevents localization failure.
@article{arxiv.1801.07249,
title = {Low-level Active Visual Navigation: Increasing robustness of vision-based localization using potential fields},
author = {Romulo T. Rodrigues and Meysam Basiri and A. Pedro Aguiar and Pedro Miraldo},
journal= {arXiv preprint arXiv:1801.07249},
year = {2018}
}
Comments
accepted for ICRA 2018. arXiv admin note: text overlap with arXiv:1709.04687