Multi-Level Task Learning Based on Intention and Constraint Inference for Autonomous Robotic Manipulation-Reference-Cited by-同舟云学术

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Multi-Level Task Learning Based on Intention and Constraint Inference for Autonomous Robotic Manipulation

Published:2022-10-23 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
language:
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Author:

Willibald Christoph¹,Lee Dongheui¹

Affiliation:

1. Institute of Robotics and Mechatronics,German Aerospace Center (DLR),Wessling,Germany,82234

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9981026/9981028/09981288.pdf?arnumber=9981288

Reference25 articles.

1. Skill learning and task outcome prediction for manipulation

2. Confidence-based policy learning from demonstration using Gaussian mixture models

3. Learning robot skills through motion segmentation and constraints extraction;pais;HRI Workshop on Collaborative Manipulation,2013

4. IMITATION LEARNING OF DUAL-ARM MANIPULATION TASKS IN HUMANOID ROBOTS

5. Multimodal anomaly detection for assistive robots

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1. A Practical Roadmap to Learning from Demonstration for Robotic Manipulators in Manufacturing;Robotics;2024-07-10

2. Inverse Constraint Learning and Generalization by Transferable Reward Decomposition;IEEE Robotics and Automation Letters;2024-01

3. Online task segmentation by merging symbolic and data-driven skill recognition during kinesthetic teaching;Robotics and Autonomous Systems;2023-04

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