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Towards Endowing Collaborative Robots with Fast Learning for Minimizing Tutors' Demonstrations: What and When to Do?

Title
Towards Endowing Collaborative Robots with Fast Learning for Minimizing Tutors' Demonstrations: What and When to Do?
Type
Article in International Conference Proceedings Book
Year
2020
Authors
Cunha, A
(Author)
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Erlhagen, W
(Author)
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Sousa, E
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Louro, L
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Vicente, P
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Monteiro, S
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Bicho, E
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Conference proceedings International
Pages: 368-378
4th Iberian Robotics Conference (Robot) - Advances in Robotics
Porto, PORTUGAL, NOV 20-22, 2019
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Authenticus ID: P-00R-XQS
Abstract (EN): Programming by demonstration allows non-experts in robot programming to train the robots in an intuitive manner. However, this learning paradigm requires multiple demonstrations of the same task, which can be time-consuming and annoying for the human tutor. To overcome this limitation, we propose a fast learning system - based on neural dynamics - that permits collaborative robots to memorize sequential information from single task demonstrations by a human-tutor. Important, the learning system allows not only to memorize long sequences of sub-goals in a task but also the time interval between them. We implement this learning system in Sawyer (a collaborative robot from Rethink Robotics) and test it in a construction task, where the robot observes several human-tutors with different preferences on the sequential order to perform the task and different behavioral time scales. After learning, memory recall (of what and when to do a sub-task) allows the robot to instruct inexperienced human workers, in a particular human-centered task scenario.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 11
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Towards collaborative robots as intelligent co-workers in human-robot joint tasks: What to do and who does it? (2020)
Article in International Conference Proceedings Book
Cunha, A; Ferreira, F; Sousa, E; Louro, L; Vicente, P; Monteiro, S; Erlhagen, W; Bicho, E
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