using perception for mobile robot. 2d ranging for mobile robot
TRANSCRIPT
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Using Perception for mobile
robot
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2D ranging for mobile robot
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Laser Measurement
distance angleLaser measurement is a series of pairs of distance and angle
r
x/r = cos
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For global frame
In general, we have to add noise
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Homework Exercise
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Bumper contact points
Centre of rotation = odometry origin
Bumper circle
Laser frame = SLAM origin
WALL
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Methods for scan (and map) matching
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• Our robot moves and rotates from t-1 to t• It takes scans
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Scan Matching
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Two Scan Matching Approaches
• Search in feature space• Look for corresponding features
and form transformation accordingly
• Search in pose space• Find a pose that provides the best
correlation
• Use translation invariant transformations
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Using odometry as an initial guess
rotation
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The method of ICP (Iterated Closest Point)
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The method of ICP (Iterated Closest Point)
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continued
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Correlation in pose space
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Correlation in pose space
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2D correlation
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Methods of searching
• Even space• Coarse to fine /iterative• Branch and bound
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Histogram• Assumption – angle histogram is the same in
both scans, it is only sifted by the amount of rotation.
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Some reading material• Sensors for Mobile Robots: Theory and Application – H.R Everett
• Where am I?" – Systems and Methods for Mobile Robot Positioning (J. Borenstein, H. R. Everett, and L. Feng)
• Probabilistic Robotics - Sebastian Thrun, Wolfram Burgard and Dieter Fox
• Mobile Robot Localisation and Mapping in Extensive Outdoor Environments – Tim Bailey
• A Sensor-Based Personal Navigation System and its Application for Incorporating Humans into a Human-Robot Team - Jari Saarinen
• Algorithms for Mobile Robot Localization and Mapping,Incorporating Detailed Noise Modeling and Multi-Scale Feature Extraction Samuel T. Pfister
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