Gaussian Process-Based Prediction of Human Trajectories to Promote Seamless Human-Robot Handovers-Reference-Cited by-同舟云学术

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Gaussian Process-Based Prediction of Human Trajectories to Promote Seamless Human-Robot Handovers

Published:2023-08-28 Issue: Volume: Page:
ISSN:
Container-title:2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)
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Author:

Lockwood Kyle¹,Strenge Garrit¹,Bicer Yunus¹,Imbiriba Tales¹,Furmanek Mariusz P.²,Padir Taskin¹,Erdogmus Deniz¹,Tunik Eugene³,Yarossi Mathew¹

Affiliation:

1. Northeastern University,Department of Electrical and Computer Engineering,Boston,MA,USA,02115

2. University of Rhode Island,Physical Therapy Department,Kingston,RI,USA,02881

3. Northeastern University,Movement and Rehabilitation Sciences,Department of Physical Therapy,Boston,MA,USA,02115

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10309296/10309265/10309536.pdf?arnumber=10309536

Reference22 articles.

1. Learning from demonstration: repetitive movements for autonomous service robotics

2. Reinforcement learning of motor skills with policy gradients

3. Implementation and experimental validation of Dynamic Movement Primitives for object handover

4. Adaptation and Robust Learning of Probabilistic Movement Primitives

5. Measurement Instruments for the Anthropomorphism, Animacy, Likeability, Perceived Intelligence, and Perceived Safety of Robots

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