Embodiment Effects in Interactions with Failing Robots

Abstract: The increasing use of robots in real-world applications will inevitably cause users to encounter more failures in interactions. While there is a longstanding effort in bringing human-likeness to robots, how robot embodiment affects users’ perception of failures remains largely unexplored. In this paper, we extend prior work on robot failures by assessing the impact that embodiment and failure severity have on people’s behaviours and their perception of robots. Our findings show that when using a smart-speaker embodiment, failures negatively affect users’ intention to frequently interact with the device, however not when using a human-like robot embodiment. Additionally, users significantly rate the human-like robot higher in terms of perceived intelligence and social presence. Our results further suggest that in higher severity situations, human-likeness is distracting and detrimental to the interaction. Drawing on quantitative findings, we discuss benefits and drawbacks of embodiment in robot failures that occur in guided tasks.

16/11/2020

remote object grounding, visual-and-language navigation, intelligent robot agent, indoor environment, referring expression grounding

4:56

25/04/2020

Jan Deriu, Don Tuggener, Pius von Däniken and
Jon Ander Campos, Alvaro Rodrigo, Thiziri Belkacem, Aitor Soroa, Eneko Agirre, Mark Cieliebak

Roland Hafner, Tim Hertweck, Philipp Kloeppner and
Michael Bloesch, Michael Neunert, Markus Wulfmeier, Saran Tunyasuvunakool, Nicolas Heess, Martin Riedmiller

Learning Physical Common Sense as Knowledge Graph Completion via BERT Data Augmentation and Constrained Tucker Factorization

Applications, Applications, Computer Vision; Deep Learning, Deep Autoencoders; Deep Learning, Generative Models; Probabilistic Methods , Reinforcement Learning and Planning, Deep RL

5:13

16/11/2020

policy learning, zero-order optimization, reinforcement learning, model predictive control, robotics, model-based learning

5:09

25/04/2020

human-in-the-loop, decision support, algorithm aversion, automation bias, algorithm assisted decision making, child welfare

15:04

25/04/2020

Kei Ota, Devesh Jha, Tadashi Onishi and
Asako Kanezaki, Yusuke Yoshiyasu, Yoko Sasaki, Toshisada Mariyama, Daniel Nikovski

Sam Devlin, Raluca Georgescu, Ida Momennejad and
Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann

Matt Deitke, Winson Han, Alvaro Herrasti and
Aniruddha Kembhavi, Eric Kolve, Roozbeh Mottaghi, Jordi Salvador, Dustin Schwenk, Eli VanderBilt, Matthew Wallingford, Luca Weihs, Mark Yatskar, Ali Farhadi