Explainable Human-Robot Training and Cooperation with Augmented Reality
February 02, 2023 Β· Declared Dead Β· π CHI Extended Abstracts
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Authors
Chao Wang, Anna Belardinelli, Stephan Hasler, Theodoros Stouraitis, Daniel Tanneberg, Michael Gienger
arXiv ID
2302.01039
Category
cs.HC: Human-Computer Interaction
Citations
32
Venue
CHI Extended Abstracts
Last Checked
4 months ago
Abstract
The current spread of social and assistive robotics applications is increasingly highlighting the need for robots that can be easily taught and interacted with, even by users with no technical background. Still, it is often difficult to grasp what such robots know or to assess if a correct representation of the task is being formed. Augmented Reality (AR) has the potential to bridge this gap. We demonstrate three use cases where AR design elements enhance the explainability and efficiency of human-robot interaction: 1) a human teaching a robot some simple kitchen tasks by demonstration, 2) the robot showing its plan for solving novel tasks in AR to a human for validation, and 3) a robot communicating its intentions via AR while assisting people with limited mobility during daily activities.
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