Copertina

Admittance Visuomotor Policy Learning for General-Purpose Contact-Rich Manipulations

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhou, Bo, Jiao, Ruixuan, Li, Yi, Yuan, Xiaogang, Fang, Fang, Li, Shihua
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Robotics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Active Admittance Control with Iterative Learning for General-Purpose Contact-Rich Manipulation
di: Zhou, Bo, et al.
Pubblicazione: (2024)

FoAR: Force-Aware Reactive Policy for Contact-Rich Robotic Manipulation
di: He, Zihao, et al.
Pubblicazione: (2024)

Should We Learn Contact-Rich Manipulation Policies from Sampling-Based Planners?
di: Zhu, Huaijiang, et al.
Pubblicazione: (2024)

Planning-Guided Diffusion Policy Learning for Generalizable Contact-Rich Bimanual Manipulation
di: Li, Xuanlin, et al.
Pubblicazione: (2024)

Reactive Diffusion Policy: Slow-Fast Visual-Tactile Policy Learning for Contact-Rich Manipulation
di: Xue, Han, et al.
Pubblicazione: (2025)

From a Single Demonstration to a General Policy for Contact-Rich Manipulation
di: Li, Xing, et al.
Pubblicazione: (2026)

Force Policy: Learning Hybrid Force-Position Control Policy under Interaction Frame for Contact-Rich Manipulation
di: Fang, Hongjie, et al.
Pubblicazione: (2026)

Closed-Loop Visuomotor Control with Generative Expectation for Robotic Manipulation
di: Bu, Qingwen, et al.
Pubblicazione: (2024)

History-Aware Visuomotor Policy Learning via Point Tracking
di: Chen, Jingjing, et al.
Pubblicazione: (2025)

DockAnywhere: Data-Efficient Visuomotor Policy Learning for Mobile Manipulation via Novel Demonstration Generation
di: Shan, Ziyu, et al.
Pubblicazione: (2026)

Referring-Aware Visuomotor Policy Learning for Closed-Loop Manipulation
di: Ma, Jiahua, et al.
Pubblicazione: (2026)

KineDex: Learning Tactile-Informed Visuomotor Policies via Kinesthetic Teaching for Dexterous Manipulation
di: Zhang, Di, et al.
Pubblicazione: (2025)

PhaForce: Phase-Scheduled Visual-Force Policy Learning with Slow Planning and Fast Correction for Contact-Rich Manipulation
di: Wang, Mingxin, et al.
Pubblicazione: (2026)

Fast Visuomotor Policy for Robotic Manipulation
di: Jia, Jingkai, et al.
Pubblicazione: (2025)

MemoAct: Atkinson-Shiffrin-Inspired Memory-Augmented Visuomotor Policy for Robotic Manipulation
di: Tan, Liufan, et al.
Pubblicazione: (2026)

DexKnot: Generalizable Visuomotor Policy Learning for Dexterous Bag-Knotting Manipulation
di: Zhang, Jiayuan, et al.
Pubblicazione: (2026)

Contact Coverage-Guided Exploration for General-Purpose Dexterous Manipulation
di: Liu, Zixuan, et al.
Pubblicazione: (2026)

Preference Aligned Visuomotor Diffusion Policies for Deformable Object Manipulation
di: Moletta, Marco, et al.
Pubblicazione: (2026)

ManipForce: Force-Guided Policy Learning with Frequency-Aware Representation for Contact-Rich Manipulation
di: Lee, Geonhyup, et al.
Pubblicazione: (2025)

Learning Visuomotor Policy for Multi-Robot Laser Tag Game
di: Li, Kai, et al.
Pubblicazione: (2026)

H2-COMPACT: Human-Humanoid Co-Manipulation via Adaptive Contact Trajectory Policies
di: Bethala, Geeta Chandra Raju, et al.
Pubblicazione: (2025)

DemoGen: Synthetic Demonstration Generation for Data-Efficient Visuomotor Policy Learning
di: Xue, Zhengrong, et al.
Pubblicazione: (2025)

Towards Tight Convex Relaxations for Contact-Rich Manipulation
di: Graesdal, Bernhard Paus, et al.
Pubblicazione: (2024)

STDArm: Transferring Visuomotor Policies From Static Data Training to Dynamic Robot Manipulation
di: Duan, Yifan, et al.
Pubblicazione: (2025)

Explicit Contact Optimization in Whole-Body Contact-Rich Manipulation
di: Leve, Victor, et al.
Pubblicazione: (2024)

Dexterous Contact-Rich Manipulation via the Contact Trust Region
di: Suh, H. J. Terry, et al.
Pubblicazione: (2025)

Spatial Policy: Guiding Visuomotor Robotic Manipulation with Spatial-Aware Modeling and Reasoning
di: Liu, Yijun, et al.
Pubblicazione: (2025)

Gentle Manipulation Policy Learning via Demonstrations from VLM Planned Atomic Skills
di: Zhou, Jiayu, et al.
Pubblicazione: (2025)

Constraint-Preserving Data Generation for Visuomotor Policy Learning
di: Lin, Kevin, et al.
Pubblicazione: (2025)

Mass-Adaptive Admittance Control for Robotic Manipulators
di: Gholampour, Hossein, et al.
Pubblicazione: (2025)

A Contact-Safe Reinforcement Learning Framework for Contact-Rich Robot Manipulation
di: Zhu, Xiang, et al.
Pubblicazione: (2022)

Simultaneous Contact Selection and Planning for Contact-Rich Manipulation with Cascaded Optimization
di: Zhang, Zhe, et al.
Pubblicazione: (2026)

HMC: Learning Heterogeneous Meta-Control for Contact-Rich Loco-Manipulation
di: Wei, Lai, et al.
Pubblicazione: (2025)

TAMEn: Tactile-Aware Manipulation Engine for Closed-Loop Data Collection in Contact-Rich Tasks
di: Wu, Longyan, et al.
Pubblicazione: (2026)

OmniVTA: Visuo-Tactile World Modeling for Contact-Rich Robotic Manipulation
di: Zheng, Yuhang, et al.
Pubblicazione: (2026)

Diffusion Policy: Visuomotor Policy Learning via Action Diffusion
di: Chi, Cheng, et al.
Pubblicazione: (2023)

Efficient Model Learning and Adaptive Tracking Control of Magnetic Micro-Robots for Non-Contact Manipulation
di: Jia, Yongyi, et al.
Pubblicazione: (2024)

ManiFoundation Model for General-Purpose Robotic Manipulation of Contact Synthesis with Arbitrary Objects and Robots
di: Xu, Zhixuan, et al.
Pubblicazione: (2024)

Certified Gradient-Based Contact-Rich Manipulation via Smoothing-Error Reachable Tubes
di: Li, Wei-Chen, et al.
Pubblicazione: (2026)

Recasting Classical Motion Planning for Contact-Rich Manipulation
di: Yang, Lin, et al.
Pubblicazione: (2025)