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Zhenjun Yu

11 accepted papers

2026

Flow before Imitation: Learning Dexterous In-Hand Manipulation with Dynamic Visuotactile Shortcut Policy

ICRA 2026poster

Dexterous in-hand manipulation remains a long-standing challenge in robotics, primarily due to the complex contact dynamics and partial observability. While humans synergize vision and touch for such tasks, robotic approaches often prioritize one modality, therefore limiting adaptability. This paper…

Cited by 0Scholar
2025

AgentWorld: An Interactive Simulation Platform for Scene Construction and Mobile Robotic Manipulation

CoRL 2025poster

We introduce AgentWorld, an interactive simulation platform for developing household mobile manipulation capabilities. Our platform combines automated scene construction that encompasses layout generation, semantic asset placement, visual material configuration, and physics simulation, with a dual-m…

Cited by 0SourceScholar
2025

DexTOG: Learning Task-Oriented Dexterous Grasp With Language Condition

RA-L 2025

This study introduces a novel language-guided diffusion-based learning framework, DexTOG, aimed at advancing the field of task-oriented grasping (TOG) with dexterous hands. Unlike existing methods that mainly focus on 2-finger grippers, this research addresses the complexities of dexterous manipulat

Cited by 8SourceScholar
2025

Dynamic Reconstruction of Hand-Object Interaction with Distributed Force-aware Contact Representation

ICCV 2025poster

We present ViTaM-D, a novel visual-tactile framework for reconstructing dynamic hand-object interaction with distributed tactile sensing to enhance contact modeling. Existing methods, relying solely on visual inputs, often fail to capture occluded interactions and object deformation. To address this…

Cited by 0SourcePDFScholar
2024

DiPGrasp: Parallel Local Searching for Efficient Differentiable Grasp Planning

RA-L 2024

Grasp planning is an important task for robotic manipulation. Though it is a richly studied area, a standalone, fast, and differentiable grasp planner that can work with robot grippers of different DOFs has not been reported. In this work, we present DiPGrasp, a grasp planner that satisfies all thes

Cited by 8SourceScholar
2024

MS-MANO: Enabling Hand Pose Tracking with Biomechanical Constraints

CVPR 2024poster

This work proposes a novel learning framework for visual hand dynamics analysis that takes into account the physiological aspects of hand motion. The existing models which are simplified joint-actuated systems often produce unnatural motions. To address this we integrate a musculoskeletal system wit…

Cited by 7SourcePDFScholar
2024

TacIPC: Intersection- and Inversion-Free FEM-Based Elastomer Simulation for Optical Tactile Sensors

RA-L 2024

Tactile perception stands as a critical sensory modality for human interaction with the environment. Among various tactile sensor techniques, optical sensor-based approaches have gained traction, notably for producing high-resolution tactile images. This letter explores gel elastomer deformation sim

Cited by 17SourceScholar
2023

Demonstrating RFUniverse: A Multiphysics Simulation Platform for Embodied AI

RSS 2023poster

Multiphysics phenomena, the coupling effects involving different aspects of physics laws, are pervasive in the real world and can often be encountered when performing everyday household tasks. Intelligent agents which seek to assist or replace human laborers will need to learn to cope with such phe…

2023

Precise Robotic Needle-Threading with Tactile Perception and Reinforcement Learning

CoRL 2023poster

This work presents a novel tactile perception-based method, named T-NT, for performing the needle-threading task, an application of deformable linear object (DLO) manipulation. This task is divided into two main stages: \textit{Tail-end Finding} and \textit{Tail-end Insertion}. In the first stage, t…

Cited by 8SourceScholar
2023

Visual-Tactile Sensing for In-Hand Object Reconstruction

CVPR 2023poster

Tactile sensing is one of the modalities human rely on heavily to perceive the world. Working with vision, this modality refines local geometry structure, measures deformation at contact area, and indicates hand-object contact state. With the availability of open-source tactile sensors such as DIGIT…

Cited by 24SourcePDFScholar