Magnetic-Field-Inspired Navigation for Quadcopter Robot in Unknown Environments

In this paper, a magnetic-field-inspired robot navigation is used to navigate an under-actuated quad-copter 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.