Passivity-Based Skill Motion Learning in Stiffness-Adaptive Unified Force-Impedance Control
Author:
Affiliation:
1. Chair of Robotics and Systems Intelligence, MIRMI - Munich Institute of Robotics and Machine Intelligence, Technical University of Munich,Germany
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9981026/9981028/09981728.pdf?arnumber=9981728
Reference30 articles.
1. Collaborative manufacturing with physical human–robot interaction
2. Skill learning and task outcome prediction for manipulation
3. Adaptive Neural Network Control of an Uncertain Robot With Full-State Constraints
4. Variable Impedance Control of Redundant Manipulators for Intuitive Human–Robot Physical Interaction
5. A Framework for Robot Manipulation: Skill Formalism, Meta Learning and Adaptive Control
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2. Tactile Robot Programming: Transferring Task Constraints into Constraint-Based Unified Force-Impedance Control;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13
3. The Inherent Representation of Tactile Manipulation Using Unified Force-Impedance Control;2023 62nd IEEE Conference on Decision and Control (CDC);2023-12-13
4. Adaptive Tuning of Robotic Polishing Skills based on Force Feedback Model;2023 IEEE International Conference on Robotics and Biomimetics (ROBIO);2023-12-04
5. Learning Compliant Stiffness by Impedance Control-Aware Task Segmentation and Multi-Objective Bayesian Optimization with Priors;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01
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