2019/01/22 by Chanoh Park, Park, Chanoh, Soohwan Kim +9
Computer Science · Earth and Planetary Sciences · Engineering · #3D Surveying and Cultural Heritage #FOS: Computer and information sciences #Robotic Path Planning Algorithms #Robotics (cs.RO) #Robotics and Sensor-Based Localization #cs.RO
paper · pdf · doi:10.48550/arxiv.1901.07660
To Appear in IEEE ROBOTICS AND AUTOMATION LETTERS, ACCEPTED JANUARY 2019
openalex publication_date 2019/01/22 · arxiv created 2019/01/30 · arxiv updated 2019/01/31 · openalex created_date 2022/07/30 · openalex updated_date 2026/07/28
Map-centric 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 paper, 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 the proposed method is not only more accurate than the conventional global ICP methods but is also robust to incorrect initial pose guesses.