activity
20242026
collaborators

10 papers

cs.RO2026

4D-CAAL: 4D Radar-Camera Calibration and Auto-Labeling for Autonomous Driving

Shanliang Yao, Zhuoxiao Li, Runwei Guan +8

4D radar has emerged as a critical sensor for autonomous driving, primarily due to its enhanced capabilities in elevation measurement and higher resolution compared to traditional…

cs.HC2025

The Evaluation for Usability Methods of Unmanned Surface Vehicles: Are Current Usability Methods Viable for Unmanned Surface Vehicles? Insights from a Multiple Case Study Approach to Human-Robot Interaction

Zitian Peng, Shiyao Zhang, Shanliang Yao +4

Unmanned Surface Vehicles (USVs) are increasingly utilised for diverse applications, ranging from environmental monitoring to security patrols. While USV technology is progressing,…

cs.RO2025

VMGNet: A Low Computational Complexity Robotic Grasping Network Based on VMamba with Multi-Scale Feature Fusion

Yuhao Jin, Qizhong Gao, Xiaohui Zhu +5

While deep learning-based robotic grasping technology has demonstrated strong adaptability, its computational complexity has also significantly increased, making it unsuitable for…

cs.CV2025

ULSR-GS: Ultra Large-scale Surface Reconstruction Gaussian Splatting with Multi-View Geometric Consistency

Zhuoxiao Li, Shanliang Yao, Taoyu Wu +6

While Gaussian Splatting (GS) demonstrates efficient and high-quality scene rendering and small area surface extraction ability, it falls short in handling large-scale aerial image…

cs.CV2025

USVTrack: USV-Based 4D Radar-Camera Tracking Dataset for Autonomous Driving in Inland Waterways

Shanliang Yao, Runwei Guan, Yi Ni +4

Object tracking in inland waterways plays a crucial role in safe and cost-effective applications, including waterborne transportation, sightseeing tours, environmental monitoring a…

cs.CV2025

Exploring Radar Data Representations in Autonomous Driving: A Comprehensive Review

Shanliang Yao, Runwei Guan, Zitian Peng +10

With the rapid advancements of sensor technology and deep learning, autonomous driving systems are providing safe and efficient access to intelligent vehicles as well as intelligen…