5 citations · 7 across the 9 of their papers we have counts for
9 papers
High-Precision Climbing Robot Localization Using Planar Array UWB/GPS/IMU/Barometer Integration
Shuning Zhang, Zhanchen Zhu, Xiangyu Chen +4
To address the need for high-precision localization of climbing robots in complex high-altitude environments, this paper proposes a multi-sensor fusion system that overcomes the li…
Taming VR Teleoperation and Learning from Demonstration for Multi-Task Bimanual Table Service Manipulation
Weize Li, Zhengxiao Han, Lixin Xu +4
This technical report presents the champion solution of the Table Service Track in the ICRA 2025 What Bimanuals Can Do (WBCD) competition. We tackled a series of demanding tasks un…
CornerPoint3D: Look at the Nearest Corner Instead of the Center
Ruixiao Zhang, Runwei Guan, Xiangyu Chen +2
3D object detection aims to predict object centers, dimensions, and rotations from LiDAR point clouds. Despite its simplicity, LiDAR captures only the near side of objects, making…
Learning 3D Perception from Others' Predictions
Jinsu Yoo, Zhenyang Feng, Tai-Yu Pan +7
Accurate 3D object detection in real-world environments requires a huge amount of annotated data with high quality. Acquiring such data is tedious and expensive, and often needs re…
GlobalMapNet: An Online Framework for Vectorized Global HD Map Construction
Anqi Shi, Yuze Cai, Xiangyu Chen +3
High-definition (HD) maps are essential for autonomous driving systems. Traditionally, an expensive and labor-intensive pipeline is implemented to construct HD maps, which is limit…
DiffuBox: Refining 3D Object Detection with Point Diffusion
Xiangyu Chen, Zhenzhen Liu, Katie Z Luo +10
Ensuring robust 3D object detection and localization is crucial for many applications in robotics and autonomous driving. Recent models, however, face difficulties in maintaining h…
Block-Map-Based Localization in Large-Scale Environment
Yixiao Feng, Zhou Jiang, Yongliang Shi +4
Accurate localization is an essential technology for the flexible navigation of robots in large-scale environments. Both SLAM-based and map-based localization will increase the com…
Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery
Katie Z Luo, Zhenzhen Liu, Xiangyu Chen +7
Recent advances in machine learning have shown that Reinforcement Learning from Human Feedback (RLHF) can improve machine learning models and align them with human preferences. Alt…
Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception
Yurong You, Katie Z Luo, Xiangyu Chen +6
Self-driving cars must detect vehicles, pedestrians, and other traffic participants accurately to operate safely. Small, far-away, or highly occluded objects are particularly chall…