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A framework for learning from demonstration with minimal human effort

Abstract:

We consider robot learning in the context of shared autonomy, where control of the system can switch between a human teleoperator and autonomous control. In this setting we address reinforcement learning, and learning from demonstration, where there is a cost associated with human time. This cost represents the human time required to teleoperate the robot, or recover the robot from failures. For each episode, the agent must choose between requesting human teleoperation, or using one of its au...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/LRA.2020.2970619

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Department:
ENGINEERING SCIENCE
Sub department:
Engineering Science
Role:
Author
ORCID:
0000-0002-7556-6098
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Journal:
IEEE Robotics and Automation Letters Journal website
Volume:
5
Issue:
2
Pages:
2023-2030
Publication date:
2020-01-30
Acceptance date:
2020-01-22
DOI:
EISSN:
2377-3766
Keywords:
Pubs id:
1095116
Local pid:
pubs:1095116
Deposit date:
2020-03-23

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