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Optic flow-based vision system for autonomous 3D localization and control of small aerial vehicles

Abstract : The problem considered in this paper involves the design of a vision-based autopilot for small and micro Unmanned Aerial Vehicles (UAVs). The proposed autopilot is based on an optic flow-based vision system for autonomous localization and scene mapping, and a nonlinear control system for flight control and guidance. This paper focusses on the development of a real-time 3D vision algorithm for estimating optic flow, aircraft self-motion and depth map, using a low-resolution onboard camera and a low-cost Inertial Measurement Unit (IMU). Our implementation is based on 3 Nested Kalman Filters (3NKF) and results in an efficient and robust estimation process. The vision and control algorithms have been implemented on a quadrotor UAV, and demonstrated in real-time flight tests. Experimental results show that the proposed vision-based autopilot enabled a small rotorcraft to achieve fully-autonomous flight using information extracted from optic flow.
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https://hal.archives-ouvertes.fr/hal-00445972
Contributor : Isabelle Fantoni <>
Submitted on : Monday, January 11, 2010 - 4:19:58 PM
Last modification on : Wednesday, July 4, 2018 - 4:44:02 PM
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Farid Kendoul, Isabelle Fantoni, Kenzo Nonami. Optic flow-based vision system for autonomous 3D localization and control of small aerial vehicles. Robotics and Autonomous Systems, Elsevier, 2009, 57 (6-7), pp.591-602. ⟨10.1016/j.robot.2009.02.001⟩. ⟨hal-00445972⟩

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