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Yiyao Liu

4 accepted papers

2025

LCSPose: Efficient, Accurate and Scalable Markerless 6-DoF Pose Estimation of a Quay Crane Spreader Based on LiDAR and Camera

ICRA 2025

Accurate Six Degrees of Freedom (6-DoF) pose estimation of Ship-To-Shore (STS) quay crane spreaders is crucial for ensuring safe and efficient container handling in port automation. However, existing pose estimation techniques face significant challenges, as camera-based systems either rely on marke

Cited by 0SourceScholar
2025

Overlapping Free: Anchorless UWB-Assisted Relative Pose Estimation for Multi-Robot Systems

ICRA 2025

Accurate Relative Pose Estimation (RPE) is critical for effective collaboration of multi-robot systems. Traditional methods using cameras or LiDARs heavily rely on overlapping Fields of View (FoV) between robots, which is highly demanding in practical applications and may hinder collaboration effici

Cited by 2SourceScholar
2024

LB-R2R-Calib: Accurate and Robust Extrinsic Calibration of Multiple Long Baseline 4D Imaging Radars for V2X

ICRA 2024poster

As a new sensor, 4D radar (x, y, z, velocity) has great potential for V2X, due to its 3D point cloud, direct doppler velocity output, long distance ranging, low-cost, and more importantly, robust perception in all weathers. However, the extrinsic calibration of multiple long baseline 4D radars is ra…

Cited by 1SourceScholar
2023

4DRadarSLAM: A 4D Imaging Radar SLAM System for Large-scale Environments based on Pose Graph Optimization

ICRA 2023poster

LiDAR-based SLAM may easily fail in adverse weathers (e.g., rain, snow, smoke, fog), while mmWave Radar remains unaffected. However, current researches are primarily focused on 2D (x,y)(x,y) or 3D (x, yx, y, doppler) Radar and 3D LiDAR, while limited work can be found for 4D Radar (x, y, zx, y, z, d…

Cited by 80SourcecodeScholar