Conference Proceedings
Explainability for Human-Robot Collaboration
E Yadollahi, M Romeo, FI Dogan, W Johal, M De Graaf, S Levy-Tzedek, I Leite
ACM IEEE International Conference on Human Robot Interaction | Published : 2024
Abstract
In human-robot collaboration, explainability bridges the communication gap between complex machine functionalities and humans. An active area of investigation in robotics and AI is understanding and generating explanations that can enhance collaboration and mutual understanding between humans and machines. A key to achieving such seamless collaborations is understanding end-users, whether naive or expert, and tailoring explanation features that are intuitive, user-centred, and contextually relevant. Advancing on the topic not only includes modelling humans' expectations for generating the explanations but also requires the development of metrics to evaluate generated explanations and assess ..
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Grants
Awarded by Swedish Foundation for Strategic Research
Awarded by Australian Research Council Discovery Early Career Research Award
Awarded by UKRI TAS Node on Trust
Awarded by Australian Research Council
Funding Acknowledgements
At KTH, this workshop is partially funded by grants from the Swedish Foundation for Strategic Research (SSF FFL18-0199), the S-FACTOR project from NordForsk, Digital Futures, and the Vinnova Competence Center for Trustworthy Edge Computing Systems and Applications. Dr Johal is supported by the Australian Research Council Discovery Early Career Research Award (Grant No. DE210100858). Dr Romeo's contribution is supported by the UKRI TAS Node on Trust (Grant EP/V026682/1).