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Magnetic-field-inspired Navigation for Quadcopter Robot in Unknown Environments

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Ahmad Ataka, Hak-Keung Lam, Kaspar Althoefer

Original languageEnglish
Title of host publicationIEEE International Conference on Robotics and Automation 2019
PublisherIEEE
Accepted/In press28 Feb 2019

Documents

  • ICRA_2019_Final

    ICRA_2019_Final.pdf, 1.22 MB, application/pdf

    Uploaded date:05 Mar 2019

    Version:Accepted author manuscript

King's Authors

Abstract

In this paper, a magnetic-field-inspired robot navigation is used to navigate an under-actuated quadcopter towards the desired position amidst previously-unknown arbitrary-shaped convex obstacles. Taking inspiration from the phenomena of magnetic field interaction with charged particles observed in nature, the algorithm outperforms previous reactive navigation algorithms for flying robots found in the literature as it is able to reactively generate motion commands relying only on a local sensory information without prior knowledge of
the obstacles’ shape or location and without getting trapped in local minima configurations. The application of the algorithm in a dynamic model of quadcopter system and in the realistic model of the commercial AscTec Pelican micro-aerial vehicle confirm the superior performance of the algorithm.

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