Interactive Text2Pickup Networks for Natural Language-Based Human-Robot Collaboration

In this letter, we propose the Interactive Text2Pickup (IT2P) network for human-robot collaboration that enables an effective interaction with a human user despite the ambiguity in user's commands. We focus on the task where a robot is expected to pick up an object instructed by a human, and to...

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Veröffentlicht in:	IEEE robotics and automation letters 2018-10, Vol.3 (4), p.3308-3315
Hauptverfasser:	Ahn, Hyemin, Choi, Sungjoon, Kim, Nuri, Cha, Geonho, Oh, Songhwai
Format:	Artikel
Sprache:	eng
Schlagworte:	Ambiguity Collaboration Commands Deep learning in robotics Estimation Heating systems learning and adaptive systems Questions Robots social human-robot interaction Task analysis Training Uncertainty
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