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

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2020

Autores

Cunha, A (Autor) Outra; Ferreira, F (Autor) Outra; Erlhagen, W (Autor) Outra; Sousa, E (Autor) Outra; Louro, L (Autor) Outra; Vicente, P (Autor) Outra; Monteiro, S (Autor) Outra; Bicho, E (Autor) Outra

Ata de Conferência Internacional

Título: FOURTH IBERIAN ROBOTICS CONFERENCE: ADVANCES IN ROBOTICS, ROBOT 2019, VOL 1

Páginas: 368-378

4th Iberian Robotics Conference (Robot) - Advances in Robotics

Porto, PORTUGAL, NOV 20-22, 2019

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 1 Citação

Outras Informações

ID Authenticus: P-00R-XQS

DOI: 10.1007/978-3-030-35990-4_30

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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11