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Laser Line Extraction

Laser Line Extraction is a Robot Operating System (ROS) package that extracts line segments form LaserScan messages. Created by Marc Gallant, originally for use in the Mining Systems Laboratory. Here is what the Laser Line Extraction package looks like in action:

Laser line extraction

In the above image, the white dots are points in a LaserScan message, and the red lines are what is extracted by Laser Line Extraction. This data was collected by driving a robot through Beamish-Munro Hall at Queen's University. A SICK LMS111 laser scanner was mounted to the robot. The extraction algorithm is very configurable; the above image used the parameters configured in the example.launch launch file.

After applying some filters to remove outlying points, Laser Line Extraction implements a split-and-merge algorithm to determine which points belong to lines. Next, it implements the weighted line fitting algorithm by Pfister et al. [1] to find the best fit lines and their respective covariance matrices.

Usage

I recommend making a copy of example.launch in the launch directory and configuring the parameters until you reach a desirable outcome. The parameters in example.launch are a good starting point. Then simply use roslaunch, e.g.,

roslaunch laser_line_extraction example.launch

Messages

Laser Line Extraction has two messages types:

LineSegment.msg

float32 radius
float32 angle
float32[4] covariance
float32[2] start
float32[2] end

radius (m) and angle (rad) are the polar parameterization of the line segment. covariance is the 2x2 covariance matrix of radius and angle (listed in row-major order). Finally start and end are the (x, y) coordinates of the start and end of the line segment.

LineSegmentList.msg

Header header
LineSegment[] line_segments

An array of LineSegment.msg with a header.

Topics

Laser Line Extraction subscribes to a single topic and publishes one or two topics.

Subscribed topics

Published topics

Parameters

The parameters are listed in alphabetical order.

References

[1] S. T. Pfister, S. I. Roumeliotis, and J. W. Burdick, "Weighted line fitting algorithms for mobile robot map building and efficient data representation" in Proc. IEEE Intl. Conf. on Robotics and Automation (ICRA), Taipei, Taiwan, 14-19 Sept., 2003.