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arXiv · 1801.07249

Low-level Active Visual Navigation: Increasing robustness of vision-based localization using potential fields

Romulo T. Rodrigues·Meysam Basiri·A. Pedro Aguiar·Pedro Miraldo
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Abstract

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.

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Romulo T. Rodrigues, Meysam Basiri, A. Pedro Aguiar, Pedro Miraldo. 2018-01-21. Low-level Active Visual Navigation: Increasing robustness of vision-based localization using potential fields. https://arxiv.org/abs/1801.07249

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