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Methods for Calibration, Registration, and Change Detection in Robot Mapping Applications

Abstract Multi-sensor fusion is a fundamental problem in Robot Perception. For a robot to operate in a real world environment, multiple sensors are often needed. Thus, fusing data from various sensors accurately is vital for robot perception. In the first part of this thesis, the problem of fusing information from a LIDAR, a color camera and a thermal camera to build RGB-Depth-Thermal (RGBDT) maps is investigated. An algorithm that solves a non-linear optimization problem to compute the relative pose between the cameras and the LIDAR is presented. The relative pose estimate is then used to find the color and thermal texture of each LIDAR point. Next, the various sources of error that can cause the mis-coloring of a LIDAR point after the cross- calib... (more)
Created Date 2016
Contributor Krishnan, Aravindhan K. (Author) / Saripalli, Srikanth (Advisor) / Klesh, Andrew (Committee member) / Fainekos, Georgios (Committee member) / Thangavelautham, Jekan (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Subject Robotics / Computer engineering / Systems science / Change Detection / Cross-Calibration / Registration / Thermal cameras
Type Doctoral Dissertation
Extent 116 pages
Language English
Reuse Permissions All Rights Reserved
Note Doctoral Dissertation Engineering Science 2016
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis