Final Design & Considerations Embedded Motion Control 2012
Group 7:
Siddhi Imming Bart Moris Roger Pouls Patrick Vaes
Eindhoven, June 29, 2012
/ Department of Mechanical Engineering PAGE 1 29-6-2012
Overview of the program structure for Tremaux’s algorithm with arrow detection
PAGE 1 29-6-2012
Jazz
Hough Line
detection
Laser message
Line information
Odometry
map
Create dump map
Request Dump block
pose
SLAM Read dump
map
Visits front, back, left, right
Image_raw
Request arrow detection
Navigation
Detect arrows
velocity
velocity
Line detection
• Line detection based on laser data and Hough Transform
• Discretized parameter space with appropriate resolution
/ Department of Mechanical Engineering PAGE 2 29-6-2012
jazz 0 °
45° 90°
jazz 0 °
45°
90° Angle Point 1 Point 2 Point 3 0 ° 5 3 1 45° 7 7 7 90° 5 7 10
Line detection
• Line detection based on laser data and Hough Transform
• Discretized parameter space with appropriate resolution
• Filter to find lines as local maxima in parameter space
• Appoint points to corresponding line
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SLAM / Mapping
• Create map based on SLAM Gmapping • Mapping based on re-observing landmarks and
estimated positions based on laser and odometry data, weighted with Kalmann filter
• Proven that it works, and reuse of what is invented is the idea of ROS
• Overlay of original map • Containing blocks with an integer indicating number
of visits • Based on synchronized original map and pose
/ Department of Mechanical Engineering PAGE 4 29-6-2012
Dump Map
SLAM / Mapping
• Create map based on SLAM Gmapping • Mapping based on re-observing landmarks and
estimated positions based on laser and odometry data, weighted with Kalmann filter
• Proven that it works, and reuse of what is invented is the idea of ROS
• Overlay of original map • Containing blocks with an integer indicating number
of visits • Based on synchronized original map and pose
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Dump Map
Arrow detection
• Overview
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Image node
Convert HSV
Blowup 2x Correct Image
Convert BW
Watershed segmentation Left, Right or
no Arrow found
Match shapes
Corner detection
Use biggest contour as
mask
Arrow detection
/ Department of Mechanical Engineering PAGE 7 29-6-2012
Image pico Correct Image
Arrow detection
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Convert HSV Blowup 2x
Arrow detection
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Blowup 2x Correct Image
Arrow detection
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Convert HSV
Convert BW
Arrow detection
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Convert BW
Watershed Segmentation
color
Watershed Segmentation
BW
Arrow detection
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Watershed segmentation
Left, Right or no Arrow found
Match shapes
Corner detection
• Check first distance to parallel lines • Check for line at 90 degrees to parallel lines and if
we are close enough, half forward speed, determine exit 3 times, put dump, else drive parallel between lines
• Exit detection and handling • Detection of type via distance between points on line
and position of the line relative to Jazz • If necessary, check for arrow • Request number of visits at each exit • Take decision, according to algorithm
Navigation node
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Navigation node
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• Parallel driving •Corridor divided in several zones, with different correction speeds to enlarge safety
Robustness measures
• Several drive strategies implemented: • Left hand rule, right hand rule, Tremaux’s rule with
random and fixed order of preference, influenced by detected arrow
• Forward speed is maximal at the center of the corridor and is lower near a wall
• Angular corrections in a corridor are with a low angular speed to prevent ‘overshoot’
• Initialization after startup and when no lines are detect for some time
• Entrance is blocked, using the dump map
/ Department of Mechanical Engineering PAGE 15 29-6-2012
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