Journal
IEEE ROBOTICS AND AUTOMATION LETTERS
Volume 4, Issue 2, Pages 1768-1775Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LRA.2019.2895262
Keywords
Loop closure; SLAM; sensor fusion; metric localization; mapping
Categories
Funding
- Commonwealth Scientific and Industrial Research Organisation
- Queensland University of Technology
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Map-centric Simultaneous Localization And Mapping (SLAM) is emerging as an alternative of conventional graph-based SLAM for its accuracy and efficiency in long-term mapping problems. However, in map-centric SLAM, the process of loop closure differs from that of conventional SLAM and the result of incorrect loop closure is more destructive and is not reversible. In this letter, we present a tightly coupled photogeometric metric localization for the loop closure problem in map-centric SLAM. In particular, our method combines complementary constraints from LiDAR and camera sensors, and validates loop closure candidates with sequential observations. The proposed method provides a visual evidence-based outlier rejection where failures caused by either place recognition or localization outliers can be effectively removed. We demonstrate that the proposed method is not only more accurate than the conventional global ICP methods but is also robust to incorrect initial pose guesses.
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