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Vision-based Landing of an Unmanned Air Vehicle
Omid ShakerniaDepartment of EECS, UC Berkeley
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Applications of Vision-based Control
Fire Scout
Global HawkPredator
SR/71
UCAV X-45
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Goal: Autonomous landing on a ship deck
Challenges Hostile environments
Ground effect Pitching deck High winds, etc
Why vision? Passive sensor Observes relative
motion
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Simulation: Vision in the loop
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Vision-Based Landing of a UAV
Motion estimation algorithms Linear, nonlinear, multiple-view Error: 5cm translation, 4° rotation
Real-time vision system Customized software Off-the-shelf hardware
Vision in Control Loop Landing on stationary deck Tracking of pitching deck
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Vision-based Motion Estimation
Pinhole Camera
Landing target
Image plane
Feature Points
Current pose
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Pose Estimation: Linear Optimization
Pinhole Camera: Epipolar Constraint: Planar constraint:
More than 4 feature points Solve linearly for Project onto to recover
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Pose Estimation: Nonlinear Refinement
Objective: minimize error
Parameterize rotation by Euler angles
Minimize by Newton-Raphson iteration
Initialize with linear algorithm
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Multiple-View Motion Estimation
Multiple View Matrix
Rank deficiency constraint
Pinhole Camera
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Multiple-View Motion Estimation n points in m views
Equivalent to finding s.t.
Initialize with two-view linear solution
Least squared solution:
Use to linearly solve for Iterate until converge
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Real-time Vision System Ampro embedded Little Board PC
Pentium 233MHz running LINUX 440 MB flashdisk HD robust to vibration Runs motion estimation algorithm Controls Pan/Tilt/Zoom camera
Motion estimation algorithms Written and optimized in C++ using LAPACK Estimate relative position and orientation at
30 Hz
UAV Pan/Tilt Camera Onboard Computer
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Hardware Configuration
On-board UAVVision System
Vision Computer
RS232
RS232
Vision Algorithm
Frame Grabber
Camera
WaveLAN to Ground
Navigation SystemNavigation Computer
RS232 RS232
Control & Navigatio
n
INS/GPS
WaveLAN to Ground
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Feature Extraction
Acquire Image Threshold Histogram Segmentation Target Detection Corner Detection Correspondence
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Pan/Tilt to keep features in image center Prevent features from leaving field of view Increased Field of View Increased range of motion of UAV
Camera Control
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Ground Station
Comparing Vision with INS/GPS
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Motion Estimation in Real Flight Tests
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Landing on Stationary Target
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Tracking Pitching Target
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Conclusions Contributions
Vision-based motion estimation (5cm accuracy)
Real-time vision system in control loop Demonstrated proof of concept prototype:
first vision-based UAV landing Extensions
Dynamic vision: Filtering motion estimates Symmetry-based motion estimation Fixed-wing UAVs: Vision-based landing on
runways Modeling and prediction of ship deck motion Landing gear that grabs ship deck Unstructured environments: Recognizing good
landing spots (grassy field, roof top etc)