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Volume 2 Issue 1
Jan.  2015

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2015  >  2(1): 33-44
Wei Zheng, Fan Zhou and Zengfu Wang, "Robust and Accurate Monocular Visual Navigation Combining IMU for a Quadrotor," IEEE/CAA J. of Autom. Sinica, vol. 2, no. 1, pp. 33-44, 2015.
Citation: Wei Zheng, Fan Zhou and Zengfu Wang, "Robust and Accurate Monocular Visual Navigation Combining IMU for a Quadrotor," IEEE/CAA J. of Autom. Sinica, vol. 2, no. 1, pp. 33-44, 2015.
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Robust and Accurate Monocular Visual Navigation Combining IMU for a Quadrotor

  • 1. Department of Automation, University of Science and Technology of China, Hefei 230027, China;

  • 2. Department of Automation, University of Science and Technology of China, Hefei 230027, China;

  • 3. Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China

Funds:

This work was supported by National Science and Technology Major Project of the Ministry of Science and Technology of China (2012GB102007).

    Abstract
  • In this paper, we present a multi-sensor fusion based monocular visual navigation system for a quadrotor with limited payload, power and computational resources. Our system is equipped with an inertial measurement unit (IMU), a sonar and a monocular down-looking camera. It is able to work well in GPS-denied and markerless environments. Different from most of the keyframe-based visual navigation systems, our system uses the information from both keyframes and keypoints in each frame. The GPU-based speeded up robust feature (SURF) is employed for feature detection and feature matching. Based on the flight characteristics of quadrotor, we propose a refined preliminary motion estimation algorithm combining IMU data. A multi-level judgment rule is then presented which is beneficial to hovering conditions and reduces the error accumulation effectively. By using the sonar sensor, the metric scale estimation problem has been solved. We also present the novel IMU+3P (IMU with three point correspondences) algorithm for accurate pose estimation. This algorithm transforms the 6-DOF pose estimation problem into a 4-DOF problem and can obtain more accurate results with less computation time. We perform the experiments of monocular visual navigation system in real indoor and outdoor environments. The results demonstrate that the monocular visual navigation system performing in real-time has robust and accurate navigation results of the quadrotor.

     

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