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Wenhai Liu

8 accepted papers

2026

Nullspace Optimization of Redundant Robots for Dynamics Decoupling in Motion Force Control

RA-L 2026

The dynamics coupling between motion and force subspaces in robotic control poses significant challenges to ensuring force control robustness, particularly under large external disturbances. While actively shaping the system inertia can eliminate this coupling, it introduces additional disturbances

Cited by 0SourceScholar
2026

Nullspace Optimization of Redundant Robots for Dynamics Decoupling in Motion Force Control

ICRA 2026poster

The dynamics coupling between motion and force subspaces in robotic control poses significant challenges to ensuring force control robustness, particularly under large external disturbances. While actively shaping the system inertia can eliminate this coupling, it introduces additional disturbances …

Cited by 0SourceScholar
2025

ForceMimic: Force-Centric Imitation Learning with Force-Motion Capture System for Contact-Rich Manipulation

ICRA 2025

In most contact-rich manipulation tasks, humans apply time-varying forces to the target object, compensating for inaccuracies in the vision-guided hand trajectory. However, current robot learning algorithms primarily focus on trajectory-based policy, with limited attention given to learning force-re

Cited by 66SourcecodeScholar
2024

GAMMA: Generalizable Articulation Modeling and Manipulation for Articulated Objects

ICRA 2024poster

Articulated objects like cabinets and doors are widespread in daily life. However, directly manipulating 3D articulated objects is challenging because they have diverse geometrical shapes, semantic categories, and kinetic constraints. Prior works mostly focused on recognizing and manipulating articu…

Cited by 15SourcecodeScholar
2024

RPMArt: Towards Robust Perception and Manipulation for Articulated Objects

IROS 2024poster

Articulated objects are commonly found in daily life. It is essential that robots can exhibit robust perception and manipulation skills for articulated objects in real-world robotic applications. However, existing methods for articulated objects insufficiently address noise in point clouds and strug…

Cited by 4SourcecodeScholar
2022

SAGCI-System: Towards Sample-Efficient, Generalizable, Compositional, and Incremental Robot Learning

ICRA 2022poster

Building general-purpose robots to perform a diverse range of tasks in a large variety of environments in the physical world at the human level is extremely challenging. According to [1], it requires the robot learning to be sample-efficient, generalizable, compositional, and incremental. In this wo…

Cited by 28SourceScholar
2022

UKPGAN: A General Self-Supervised Keypoint Detector

CVPR 2022poster

Keypoint detection is an essential component for the object registration and alignment. In this work, we reckon keypoint detection as information compression, and force the model to distill out important points of an object. Based on this, we propose UKPGAN, a general self-supervised 3D keypoint det…

Cited by 31PDFcodeScholar