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Autonomous Flight of a Quadrotor Using Multi-Camera Visual SLAM

Mingfeng Zhang, Adam Harmat, Inna Sharf


This paper presents the development and validation of a vision-based navigation and control system for a small unmanned quadrotor. The core of this system is a state estimator based on the so-called multi-camera parallel tracking and mapping algorithm, which provides accurate pose estimation for the quadrotor using multiple cameras. Built on cascaded proportional-integral-derivative control loops, a motion controller is designed to provide altitude,
horizontal position, and yaw regulation. The performance of the proposed system is successfully demonstrated in fully autonomous flights in a variety of indoor and outdoor scenarios.

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