87 citations · 127 across the 12 of their papers we have counts for
13 papers
Arm-Aware Guided Dexterous Grasp Generation with Arm-Agnostic Grasp Models
Yongyi Jia, Yongpeng Jiang, Kangchen Lv +3
Dexterous grasp generation that considers arm-related constraints is crucial in real-world scenarios involving arm environment collision avoidance, workspace boundary grasps, and c…
HUGS: Guiding Unified Dexterous Grasp Synthesis Across Modes and Scales via Learned Human Priors
Mingrui Yu, Yongpeng Jiang, Yongyi Jia +4
Dexterous grasping across diverse object scales requires contact modes ranging from two-finger pinches to bimanual grasps. Existing dexterous grasp synthesis methods reduce the hig…
EmbodiSteer: Steering Embodiment-Agnostic Visuomotor Policies with Joint-Space Guidance for Zero-Shot Cross-Embodiment Deployment
Shihefeng Wang, Kangchen Lv, Mingrui Yu +1
Scalable robot imitation learning relies on large-scale heterogeneous data from diverse robots or body-free data, making Cartesian end-effector actions a key interface for embodime…
UniStateDLO: Unified Generative State Estimation and Tracking of Deformable Linear Objects Under Occlusion for Constrained Manipulation
Kangchen Lv, Mingrui Yu, Shihefeng Wang +2
Perception of deformable linear objects (DLOs), such as cables, ropes, and wires, is the cornerstone for successful downstream manipulation. Although vision-based methods have been…
Kinematics-Aware Diffusion Policy with Consistent 3D Observation and Action Space for Whole-Arm Robotic Manipulation
Kangchen Lv, Mingrui Yu, Yongyi Jia +2
Whole-body control of robotic manipulators with awareness of full-arm kinematics is crucial for many manipulation scenarios involving body collision avoidance or body-object intera…
UltraDP: Generalizable Carotid Ultrasound Scanning with Force-Aware Diffusion Policy
Ruoqu Chen, Xiangjie Yan, Kangchen Lv +3
Ultrasound scanning is a critical imaging technique for real-time, non-invasive diagnostics. However, variations in patient anatomy and complex human-in-the-loop interactions pose…
Generalizable whole-body global manipulation of deformable linear objects by dual-arm robot in 3-D constrained environments
Mingrui Yu, Kangchen Lv, Changhao Wang +3
Constrained environments are common in practical applications of manipulating deformable linear objects (DLOs), where movements of both DLOs and robots should be constrained. This…
Learning to Estimate 3-D States of Deformable Linear Objects from Single-Frame Occluded Point Clouds
Kangchen Lv, Mingrui Yu, Yifan Pu +3
Accurately and robustly estimating the state of deformable linear objects (DLOs), such as ropes and wires, is crucial for DLO manipulation and other applications. However, it remai…
A Coarse-to-Fine Framework for Dual-Arm Manipulation of Deformable Linear Objects with Whole-Body Obstacle Avoidance
Mingrui Yu, Kangchen Lv, Changhao Wang +2
Manipulating deformable linear objects (DLOs) to achieve desired shapes in constrained environments with obstacles is a meaningful but challenging task. Global planning is necessar…
Global Model Learning for Large Deformation Control of Elastic Deformable Linear Objects: An Efficient and Adaptive Approach
Mingrui Yu, Kangchen Lv, Hanzhong Zhong +2
Robotic manipulation of deformable linear objects (DLOs) has broad application prospects in many fields. However, a key issue is to obtain the exact deformation models (i.e., how r…
Glance and Focus Networks for Dynamic Visual Recognition
Gao Huang, Yulin Wang, Kangchen Lv +4
Spatial redundancy widely exists in visual recognition tasks, i.e., discriminative features in an image or video frame usually correspond to only a subset of pixels, while the rema…
Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image Classification
Yulin Wang, Kangchen Lv, Rui Huang +3
The accuracy of deep convolutional neural networks (CNNs) generally improves when fueled with high resolution images. However, this often comes at a high computational cost and hig…
Graph-based Kinship Reasoning Network
Wanhua Li, Yingqiang Zhang, Kangchen Lv +3
In this paper, we propose a graph-based kinship reasoning (GKR) network for kinship verification, which aims to effectively perform relational reasoning on the extracted features o…