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

  • Authors:

  • Farid Kendoul;Isabelle Fantoni;Kenzo Nonami

  • Affiliations:

  • Heudiasyc Lab., UMR CNRS-UTC 6599, University of Technology of Compiegne, 60200 Compiègne, France;Heudiasyc Lab., UMR CNRS-UTC 6599, University of Technology of Compiegne, 60200 Compiègne, France;Robotics and Control Lab., Electronics and Mechanical Engineering Department, Chiba University, 263-8522, Chiba City, Japan

  • Venue:
  • Robotics and Autonomous Systems
  • Year:
  • 2009

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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.