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A general optical flow based terrainfollowing strategy for a VTOL UAV using multiple views
Bruno Hérissé
Sophie Oustrières
Tarek Hamel
Robert Mahony
François-Xavier Russotto
CEA LIST Fontenay-Aux-Roses, France
[email protected]
CEA LIST Fontenay-Aux-Roses, France
I3S - CNRS Nice-Sophia Antipolis, France
[email protected]
Dep. of Eng., Australian Nat. Univ. ACT, 0200, Australia
[email protected]
CEA LIST Fontenay-Aux-Roses, France
[email protected]
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Introduction •
Purpose : Design of a controller for a VTOL UAV using inertial data, barometric altimeter and visual optical flow measurments.
IMU
Barometric altimeter
(Inertial Measurments Unit)
Camera (OF Measurments)
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State Model of the quadrotor UAV T
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The system is nonlinear and under actuated. Definition of the used reference frames. I : Inertial frame attached to the earth B : body-fixed frame attached to the vehicle at the center of mass. Vehicle state: ξ : position of the center of mass in I v : speed of the center of mass in I R : orientation matrix from B to I Ω : rotational velocity in B Inputs: T : Global thrust in B Γ : Control torque in B
Γ
Translational dynamics
Rotational Dynamics Already controlled
High gain controller
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Average optical Flow •
Average optical flow is computed from the integral of all observed optical flow around a specified direction
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The forward optical flow Impossible d’afficher l’image.
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T Γ
The normal optical flow T Γ
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Terrain following with 1 aperture (ICRA'09)
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The control law
ensures the asymptotic convergence of
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The UAV does not collide the obstacle
to
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Robustness ?
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The forward velocity
may vary with time
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The optical flow is noisy
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The surface may be sloped
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The target surface may be non-planar
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Terrain following: sloped target
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Computation of the OF in any directions
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Corner avoidance ?
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Controller for terrain following
UAV dynamics
Average optical flow in any directions + "derotation"
State:
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Corner avoidance !
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Improvement for terrain following !
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Disturbed dynamics
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Attractor
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Experimental setup
Camera: - Focus: 2.1mm
Drone: - Embeded attitude control -running at 166Hz
Numerical transmission: - Attitude - IMU data - 70 ms required
Textured terrain
Analogical transmission: - 2.4GHz - Image Frequency 20Hz
Ground station: - OF Processing - 15Hz
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Experiments
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Conclusion •
Possible extensions 3-D Corner avoidance Wall following (cameras looking forward and sideways) Corridor following (2 cameras looking on the left side and the right side)
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The approach is robust but… We need velocity measurements for the forward velocity regulation (particularly for indoor applications) We need textured terrains (indoor?)
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Future work Full 3-D motion Outdoor experiments Full embedded system (image processing) with more efficient cameras (mouse sensors, VLSI)
