Fusion of Monocular Visual-Inertial Measurements for Three Dimensional Pose Estimation

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• 关键词：Sensor fusion ; Visual odometry ; Inertial sensors ; Pose estimation ; UAV ; Kalman filter
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9991
• 期：1
• 页码：242-260
• 全文大小：2,192 KB
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  2.Araguás, G., Paz, C., Gaydou, D., Perez Paina, G.: Quaternion-based orientation estimation fusing a camera and inertial sensors for a hovering UAV. J. Intell. Robot. Syst. 77(1), 37–53 (2015). doi:10.​1007/​s10846-014-0092-z CrossRef
  3.Araguás, G., Paz, C., Perez Paina, G., Canali, L.: Visual homography-based pose estimation of a quadrotor using spectral features. In: Designing with Computational Intelligence. Studies in Computational Intelligence (in press)
  4.Bloesch, M., Omari, S., Fankhauser, P., Sommer, H., Gehring, C., Hwangbo, J., Hoepflinger, M., Hutter, M., Siegwart, R.: Fusion of optical flow and inertial measurements for robust egomotion estimation. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS ), pp. 3102–3107, September 2014
  5.Camposeco, F., Pollefeys, M.: Using vanishing points to improve visual-inertial odometry. In: 2015 IEEE International Conference on Robotics and Automation (ICRA), pp. 5219–5225, May 2015
  6.Chudoba, J., Kulich, M., Saska, M., Báča, T., Přeučil, L.: Exploration and mapping technique suited for visual-features based localization of MAVS. J. Intell. Robot. Syst. 1–19 (2016). http://​dx.​doi.​org/​10.​1007/​s10846-016-0358-8
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  14.Roumeliotis, S., Burdick, J.: Stochastic cloning: a generalized framework for processing relative state measurements. In: Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2002, vol. 2, pp. 1788–1795 (2002)
  15.Shen, S., Michael, N., Kumar, V.: Tightly-coupled monocular visual-inertial fusion for autonomous flight of rotorcraft MAVS. In: 2015 IEEE International Conference on Robotics and Automation (ICRA), pp. 5303–5310, May 2015
  16.Shen, S., Mulgaonkar, Y., Michael, N., Kumar, V.: Multi-sensor fusion for robust autonomous flight in indoor and outdoor environments with a rotorcraft MAV. In: 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 4974–4981, May 2014
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  19.Trawny, N., Roumeliotis, S.I.: Indirect Kalman filter for 3D attitude estimation. Technical report 2005–002, University of Minnesota, Department of Computer Science and Engineering, March 2005
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• 作者单位：Gonzalo Perez-Paina (14)
  Claudio Paz (14)
  Miroslav Kulich (15)
  Martin Saska (16)
  Gastón Araguás (14)
  
  14. Center for IT Research, National Technological University, Córdoba, Argentina
  15. Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University in Prague, Prague, Czech Republic
  16. Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
  
• 丛书名：Modelling and Simulation for Autonomous Systems
• ISBN：978-3-319-47605-6
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9991

文摘

This work describes a novel fusion schema to estimate the pose of a UAV using inertial sensors and a monocular camera. The visual motion algorithm is based on the plane induced homography using so called spectral features. The algorithm is able to operate with images presenting small amount of corner-like features, which gives more robustness to the state estimation. The key contribution of the paper is the use of this visual algorithm in a fusion schema with inertial sensors, exploiting the complementary properties of these two sensors. Results are presented in simulation with six degrees of freedom motion that satisfies dynamic constraints of a quadcopter. Virtual views are generated from this simulated motion cropped from a real floor image. Simulation results show that the presented algorithm would have enough precision to be used in an on-board algorithm to control the UAV in hovering operations.