5 papers
SEF-MAP: Subspace-Decomposed Expert Fusion for Robust Multimodal HD Map Prediction
Haoxiang Fu, Lingfeng Zhang, Hao Li +7
High-definition (HD) maps are essential for autonomous driving, yet multi-modal fusion often suffers from inconsistency between camera and LiDAR modalities, leading to performance…
Visual SLAMMOT Considering Multiple Motion Models
Peilin Tian, Hao Li
Simultaneous Localization and Mapping (SLAM) and Multi-Object Tracking (MOT) are pivotal tasks in the realm of autonomous driving, attracting considerable research attention. While…
Split Covariance Intersection Filter Based Visual Localization With Accurate AprilTag Map For Warehouse Robot Navigation
Susu Fang, Yanhao Li, Hao Li
Accurate and efficient localization with conveniently-established map is the fundamental requirement for mobile robot operation in warehouse environments. An accurate AprilTag map…
LiDAR SLAMMOT based on Confidence-guided Data Association
Susu Fang, Hao Li
In the field of autonomous driving or robotics, simultaneous localization and mapping (SLAM) and multi-object tracking (MOT) are two fundamental problems and are generally applied…
Communication-Efficient Cooperative SLAMMOT via Determining the Number of Collaboration Vehicles
Susu Fang, Hao Li
The SLAMMOT, i.e. simultaneous localization, mapping, and moving object (detection and) tracking, represents an emerging technology for autonomous vehicles in dynamic environments.…