An Interactive Multisensing Framework for Personalized Human Robot Collaboration and Assistive Training Using Reinforcement Learning-Reference-Cited by-同舟云学术

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An Interactive Multisensing Framework for Personalized Human Robot Collaboration and Assistive Training Using Reinforcement Learning

Published:2017-06-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 10th International Conference on PErvasive Technologies Related to Assistive Environments
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Author:

Tsiakas Konstantinos¹,Papakostas Michalis¹,Theofanidis Michail¹,Bell Morris²,Mihalcea Rada³,Wang Shouyi⁴,Burzo Mihai⁵,Makedon Fillia¹

Affiliation:

1. HERACLEIA Human-Centered Computing Laboratory, CSE Dept., University of Texas at Arlington

2. Dept. of Psychiatry, Yale School of Medicine

3. CSE Dept., University of Michigan

4. Industrial Engineering Dept., University of Texas at Arlington

5. Mechanical Engineering Dept., University of Michigan-Flint

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3056540.3076191

Reference39 articles.

1. Safe and dependable physical human-robot interaction in anthropic domains: State of the art and challenges

2. THE BIG FIVE PERSONALITY DIMENSIONS AND JOB PERFORMANCE: A META-ANALYSIS

3. HUMAN–ROBOT COLLABORATION: A SURVEY

4. The structure of phenotypic personality traits.

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1. A Review on the Effectiveness of Machine Learning and Deep Learning Algorithms for Collaborative Robot;Archives of Computational Methods in Engineering;2023-05-30

2. Human–robot collaboration and machine learning: A systematic review of recent research;Robotics and Computer-Integrated Manufacturing;2023-02

3. Human-robot interactions in manufacturing: A survey of human behavior modeling;Robotics and Computer-Integrated Manufacturing;2022-12

4. A hybrid model-based evolutionary optimization with passive boundaries for physical human-robot interaction;2022 International Conference on Robotics and Automation (ICRA);2022-05-23

5. Toward human-centric smart manufacturing: A human-cyber-physical systems (HCPS) perspective;Journal of Manufacturing Systems;2022-04

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