Paper Info
Title
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.
Year
DOI
Venue
2009
10.1016/j.robot.2009.02.001
Robotics and Autonomous Systems
Keywords
Field
DocType
UAV,Autonomous localization,Optic flow,Structure-From-Motion (SFM),Flight guidance and control,Visual SLAM
Computer vision,Machine vision,Computer science,Simulation,Nonlinear control,Flow (psychology),Kalman filter,Onboard camera,Inertial measurement unit,Artificial intelligence,Autopilot,Depth map
Journal
Volume
Issue
ISSN
57
6-7
Robotics and Autonomous Systems
Citations 
PageRank 
References 
67
3.22
19
Authors
3
Name
Order
Citations
PageRank
Farid Kendoul121213.78
Isabelle Fantoni227927.65
Kenzo Nonami325831.91