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arXiv · 1809.08881

Vision-based Control of a Quadrotor in User Proximity: Mediated vs End-to-End Learning Approaches

Dario Mantegazza·Jérôme Guzzi·Luca M. Gambardella·Alessandro Giusti
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Abstract

We consider the task of controlling a quadrotor to hover in front of a freely moving user, using input data from an onboard camera. On this specific task we compare two widespread learning paradigms: a mediated approach, which learns an high-level state from the input and then uses it for deriving control signals; and an end-to-end approach, which skips high-level state estimation altogether. We show that despite their fundamental difference, both approaches yield equivalent performance on this task. We finally qualitatively analyze the behavior of a quadrotor implementing such approaches.

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Dario Mantegazza, Jérôme Guzzi, Luca M. Gambardella, Alessandro Giusti. 2018-09-24. Vision-based Control of a Quadrotor in User Proximity: Mediated vs End-to-End Learning Approaches. https://arxiv.org/abs/1809.08881

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