Copertina

Automatic Derivation of an Optimal Task Frame for Learning and Controlling Contact-Rich Tasks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Mohammadi, Ali Mousavi, Vochten, Maxim, Aertbeliën, Erwin, De Schutter, Joris
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Robotics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A Coordinate-Invariant Local Representation of Motion and Force Trajectories for Identification and Generalization Across Coordinate Systems
di: Verduyn, Arno, et al.
Pubblicazione: (2026)

BILTS: A Bi-Invariant Similarity Measure for Robust Object Trajectory Recognition under Reference Frame Variations
di: Verduyn, Arno, et al.
Pubblicazione: (2024)

Enhancing Hand Palm Motion Gesture Recognition by Eliminating Reference Frame Bias via Frame-Invariant Similarity Measures
di: Verduyn, Arno, et al.
Pubblicazione: (2025)

Enhancing motion trajectory segmentation of rigid bodies using a novel screw-based trajectory-shape representation
di: Verduyn, Arno, et al.
Pubblicazione: (2023)

Using Intent Estimation and Decision Theory to Support Lifting Motions with a Quasi-Passive Hip Exoskeleton
di: Callens, Thomas, et al.
Pubblicazione: (2023)

From Instantaneous to Predictive Control: A More Intuitive and Tunable MPC Formulation for Robot Manipulators
di: Ubbink, Johan, et al.
Pubblicazione: (2024)

Robot Trajectron: Trajectory Prediction-based Shared Control for Robot Manipulation
di: Song, Pinhao, et al.
Pubblicazione: (2024)

Passivity-Centric Safe Reinforcement Learning for Contact-Rich Robotic Tasks
di: Zhang, Heng, et al.
Pubblicazione: (2025)

Diffusion-Based Impedance Learning for Contact-Rich Manipulation Tasks
di: Geiger, Noah, et al.
Pubblicazione: (2025)

A Survey on Imitation Learning for Contact-Rich Tasks in Robotics
di: Tsuji, Toshiaki, et al.
Pubblicazione: (2025)

Bresa: Bio-inspired Reflexive Safe Reinforcement Learning for Contact-Rich Robotic Tasks
di: Zhang, Heng, et al.
Pubblicazione: (2025)

SRL-VIC: A Variable Stiffness-Based Safe Reinforcement Learning for Contact-Rich Robotic Tasks
di: Zhang, Heng, et al.
Pubblicazione: (2024)

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

TacUMI: A Multi-Modal Universal Manipulation Interface for Contact-Rich Tasks
di: Cheng, Tailai, et al.
Pubblicazione: (2026)

ViTaMIn: Learning Contact-Rich Tasks Through Robot-Free Visuo-Tactile Manipulation Interface
di: Liu, Fangchen, 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)

SHaRe-RL: Structured, Interactive Reinforcement Learning for Contact-Rich Industrial Assembly Tasks
di: Stranghöner, Jannick, et al.
Pubblicazione: (2025)

Safe Learning for Contact-Rich Robot Tasks: A Survey from Classical Learning-Based Methods to Safe Foundation Models
di: Zhang, Heng, et al.
Pubblicazione: (2025)

A Task-Efficient Reinforcement Learning Task-Motion Planner for Safe Human-Robot Cooperation
di: Liu, Gaoyuan, et al.
Pubblicazione: (2025)

FILIC: Dual-Loop Force-Guided Imitation Learning with Impedance Torque Control for Contact-Rich Manipulation Tasks
di: Ge, Haizhou, et al.
Pubblicazione: (2025)

LEMMo-Plan: LLM-Enhanced Learning from Multi-Modal Demonstration for Planning Sequential Contact-Rich Manipulation Tasks
di: Chen, Kejia, et al.
Pubblicazione: (2024)

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

Online Multi-Contact Feedback Model Predictive Control for Interactive Robotic Tasks
di: Han, Seo Wook, et al.
Pubblicazione: (2024)

Geometric Algebra for Optimal Control with Applications in Manipulation Tasks
di: Löw, Tobias, et al.
Pubblicazione: (2022)

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

Learning to Act Through Contact: A Unified View of Multi-Task Robot Learning
di: Omar, Shafeef, et al.
Pubblicazione: (2025)

An Optimal Control Formulation of Tool Affordance Applied to Impact Tasks
di: Ti, Boyang, et al.
Pubblicazione: (2024)

ATK: Automatic Task-driven Keypoint Selection for Robust Policy Learning
di: Zhang, Yunchu, et al.
Pubblicazione: (2025)

Optimistic Reinforcement Learning-Based Skill Insertions for Task and Motion Planning
di: Liu, Gaoyuan, et al.
Pubblicazione: (2025)

Task2Morph: Differentiable Task-inspired Framework for Contact-Aware Robot Design
di: Cai, Yishuai, et al.
Pubblicazione: (2024)

GenCHiP: Generating Robot Policy Code for High-Precision and Contact-Rich Manipulation Tasks
di: Burns, Kaylee, et al.
Pubblicazione: (2024)

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)

Model Predictive Control for Cooperative Docking Between Autonomous Surface Vehicles with Disturbance Rejection
di: Battocletti, Gianpietro, et al.
Pubblicazione: (2025)

Mastering Contact-rich Tasks by Combining Soft and Rigid Robotics with Imitation Learning
di: Montero, Mariano Ramírez, et al.
Pubblicazione: (2024)

RichMap: A Reachability Map Balancing Precision, Efficiency, and Flexibility for Rich Robot Manipulation Tasks
di: Lu, Yupu, et al.
Pubblicazione: (2026)

Learning Adaptive Force Control for Contact-Rich Sample Scraping with Heterogeneous Materials
di: Cetin, Cenk, et al.
Pubblicazione: (2026)

Bellman Value Decomposition for Task Logic in Safe Optimal Control
di: Sharpless, William, et al.
Pubblicazione: (2026)

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

Contact-Rich and Deformable Foot Modeling for Locomotion Control of the Human Musculoskeletal System
di: Gong, Haixin, et al.
Pubblicazione: (2025)