Scan registration method that employs additional channels of information like color, intensity. Integrates new channels into point covariance weights used in registration optimization. Improves registration in regions with limited geometric scan into multi-page pdf for free, without computation penalty.
Demonstrated on Ford, Freiburg, and Waterloo hallway datasets. Current state of the art scan registration algorithms which use only position information often fall victim to correspondence ambiguity and degeneracy in the optimization solutions. Other methods which use additional channels, such as color or intensity, often use only a small fraction of the available information and ignore the underlying structural information of the added channels. The proposed method incorporates the additional channels directly into the scan registration formulation to provide information within the plane of the surface. This is achieved by calculating the uncertainty both along and perpendicular to the local surface at each point and calculating nearest neighbor correspondences in the higher dimensional space. The proposed method reduces instances of degenerate transformation estimates and improves both registration accuracy and convergence rate.
The method is tested on the Ford Vision and Lidar dataset using both color and intensity channels, as well as with Microsoft Kinect data from the Freiburg RGBD Office dataset and data obtained from the University of Waterloo campus. 2014 from the University of Waterloo in the department of Mechanical and Mechatronics Engineering. He is currently employed by Clearpath Robotics as an Autonomy Engineer, and is actively involved in the deployment of SLAM and scan registration methods for both research and industrial applications. 1998 from Queen’s University, his M. 2007, both from Stanford University in Aeronautics and Astronautics. Whitney Canada from 1998 to 2001.
In 2008, he joined the Department of Mechanical and Mechatronics Engineering at the University of Waterloo in Waterloo, ON, Canada where he is now an associate professor. His research interests are in the areas of autonomous aerial and ground vehicles, simultaneous localization and mapping, nonlinear estimation and control, and multi-vehicle systems. Convert paper contracts, agreements and other images like JPG, GIF, PNG, BMP, etc. PDF files with a streamline workflow. Scan your documentation to PDF files! Revolutionary freeware for digitizing and sending of paper documents over the internet. Now, scan a paper document and pictures that contains text to PDF form that can be easily distributed, tracked, and analyzed.
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