Journal
IEEE ROBOTICS AND AUTOMATION LETTERS
Volume 4, Issue 2, Pages 625-632Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LRA.2019.2891989
Keywords
SLAM; localization
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Registering models is an essential building block of many robotic applications. In case of three-dimensional data, the models to be aligned usually consist of point clouds. In this letter, we propose a formalism to represent in a uniform manner scenes consisting of high-level geometric primitives, including lines and planes. Additionally, we derive both an iterative and a direct method to determine the transformation between heterogeneous scenes (solver). We analyzed the convergence behavior of this solver on synthetic data. Furthermore, we conducted comparative experiments on a full registration pipeline that operates on raw data, implemented on top of our solver. To this extent we used public benchmark datasets and we compared against state-of-the-art approaches. Finally, we provide an implementation of our solver together with scripts to ease the reproduction of the results presented in this letter.
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