Characterizing Input Methods for Human-to-Robot Demonstrations-Reference-Cited by-同舟云学术

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Characterizing Input Methods for Human-to-Robot Demonstrations

Published:2019-03 Issue: Volume: Page:
ISSN:
Container-title:2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)
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Author:

Praveena Pragathi,Subramani Guru,Mutlu Bilge,Gleicher Michael

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8666012/8673065/08673310.pdf?arnumber=8673310

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Teleoperation-Driven and Keyframe-Based Generalizable Imitation Learning for Construction Robots;Journal of Computing in Civil Engineering;2024-11

2. AirExo: Low-Cost Exoskeletons for Learning Whole-Arm Manipulation in the Wild;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. NetLfD: Network-Aware Learning From Demonstration for In-Contact Skills via Teleoperation;IEEE Robotics and Automation Letters;2023-11

4. Data-efficient learning of object-centric grasp preferences;2022 International Conference on Robotics and Automation (ICRA);2022-05-23

5. New CNN and hybrid CNN-LSTM models for learning object manipulation of humanoid robots from demonstration;Cluster Computing;2021-06-26

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