13 papers
Interaction Latents as Actions for Contact-Rich Manipulation
Yuhang Zheng, Yujie Zang, Yuchen Liu +9
Contact-rich manipulation requires robots to coordinate not only where to move, but also how contact and force should evolve throughout an interaction. Yet most robot policies repr…
Construction of log Calabi--Yau boundaries from int-amplified endomorphisms
Shou Yoshikawa
In this paper, we prove that -Gorenstein projective complex varieties admitting int-amplified endomorphisms are of Calabi--Yau type.
UMI-WM: Interactive World Modeling for Bimanual Manipulation from Wrist Cameras
Jingxiang Guo, Haoyu Zhao, Xidong Zhang +6
Universal Manipulation Interface (UMI) pairs wrist-camera videos with camera trajectories and gripper openings, providing scalable, robot-free data for learning how bimanual action…
SyLink Hand: A Synergy-Inspired Linkage-Driven Anthropomorphic Hand for Human-Like Dexterity
Hao Wu, Yanzhe Wang, Yu Feng +4
Designing anthropomorphic robotic hands that balance functional dexterity with mechanical simplicity remains a significant challenge. Inspired by human hand synergies, this paper p…
ShapeForce: Low-Cost Soft Robotic Wrist for Contact-Rich Manipulation
Jinxuan Zhu, Zihao Yan, Yangyu Xiao +5
Contact feedback is essential for contact-rich robotic manipulation, as it allows the robot to detect subtle interaction changes and adjust its actions accordingly. Six-axis force-…
AdaptPNP: Integrating Prehensile and Non-Prehensile Skills for Adaptive Robotic Manipulation
Jinxuan Zhu, Chenrui Tie, Xinyi Cao +8
Non-prehensile (NP) manipulation, in which robots alter object states without forming stable grasps (for example, pushing, poking, or sliding), significantly broadens robotic manip…
Benchmarking Generalizable Bimanual Manipulation: RoboTwin Dual-Arm Collaboration Challenge at CVPR 2025 MEIS Workshop
Tianxing Chen, Kaixuan Wang, Zhaohui Yang +96
Embodied Artificial Intelligence (Embodied AI) is an emerging frontier in robotics, driven by the need for autonomous systems that can perceive, reason, and act in complex physical…
Goal-VLA: Image-Generative VLMs as Object-Centric World Models Empowering Zero-shot Robot Manipulation
Haonan Chen, Jingxiang Guo, Bangjun Wang +7
Generalization remains a fundamental challenge in robotic manipulation. To tackle this challenge, recent Vision-Language-Action (VLA) models build policies on top of Vision-Languag…
DexSinGrasp: Learning a Unified Policy for Dexterous Object Singulation and Grasping in Densely Cluttered Environments
Lixin Xu, Zixuan Liu, Zhewei Gui +6
Grasping objects in cluttered environments remains a fundamental yet challenging problem in robotic manipulation. While prior works have explored learning-based synergies between p…
MetaFold: Language-Guided Multi-Category Garment Folding Framework via Trajectory Generation and Foundation Model
Haonan Chen, Junxiao Li, Ruihai Wu +9
Garment folding is a common yet challenging task in robotic manipulation. The deformability of garments leads to a vast state space and complex dynamics, which complicates precise…
Manual2Skill: Learning to Read Manuals and Acquire Robotic Skills for Furniture Assembly Using Vision-Language Models
Chenrui Tie, Shengxiang Sun, Jinxuan Zhu +7
Humans possess an extraordinary ability to understand and execute complex manipulation tasks by interpreting abstract instruction manuals. For robots, however, this capability rema…
TelePreview: A User-Friendly Teleoperation System with Virtual Arm Assistance for Enhanced Effectiveness
Jingxiang Guo, Jiayu Luo, Zhenyu Wei +5
Teleoperation provides an effective way to collect robot data, which is crucial for learning from demonstrations. In this field, teleoperation faces several key challenges: user-fr…
Grasp: A Unified Representation of Robot and Object Interaction for Cross-Embodiment Dexterous Grasping
Zhenyu Wei, Zhixuan Xu, Jingxiang Guo +5
Dexterous grasping is a fundamental yet challenging skill in robotic manipulation, requiring precise interaction between robotic hands and objects. In this paper, we present $\math…