SGBA: semantic gaussian mixture model-based LiDAR bundle adjustment

• Main Authors: Ji, Xingyu, Yuan, Shenghai, Li, Jianping, Yin, Pengyu, Cao, Haozhi, Xie, Lihua
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2025
• Subjects: Computer and Information Science; Localization; Mapping; Bundle adjustment
• Online Access: https://hdl.handle.net/10356/182120
• Institution: Nanyang Technological University

LiDAR bundle adjustment (BA) is an effective approach to reduce the drifts in pose estimation from the front-end. Existing works on LiDAR BA usually rely on predefined geometric features for landmark representation. This reliance restricts generalizability, as the system will inevitably deteriorate...