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Explainability in human-robot teaming

Banitalebi Dehkordi, Maryam, Mansy, Reda, Zaraki, Abolfazl, Singh, Arpit and Setchi, Rossitza 2021. Explainability in human-robot teaming. Procedia Computer Science 192 , pp. 3487-3496. 10.1016/j.procs.2021.09.122

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Abstract

In human-robot teaming, one of the crucial keys for the team’s success is that the robot and human teammates can collaborate accordingly in a coordinated manner. Each teammate should be aware of what the other teammate is going to perform and likely to need. In this context, a robot is expected to understand human teammate intention and performance and explain its actions and decisions and its rationale to its teammate. In addition, the capability to model the expectation of a human teammate empowers the robot to collaborate with human understandably and expectedly, leading to effective teaming. Through forming mental modelling, the robot can understand the impact of its own behaviour on the mental model of the human. In addition, the desirable traits in human-robot teaming, including fluent behaviour, adaptability, trust-building, effective communication, and explainability, can be achieved through mental modelling. In this work, we introduce a scenario for human-robot teaming considering all the five desirable traits in teaming with the main focus on explainability and effective communication. Using a general model reconciliation, the expectation of the human teammate of the robot can be modelled, and the explanation can be generated. In a considered scenario including Care-O-bot 4 service robot and a human teammate, we assume that the robot detects the human’s current task (analysing his body gesture) and predicts his following action and his expectation from the robot. In a reciprocal interdependence task, the robot coordinates his behaviour and acts accordingly by picking up the relevant tool. Through explanation and communication robot further offers the outcome of his decision to the human teammate and adapts its action by handing the tool to the human upon his desire.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Engineering
Additional Information: his is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)
Publisher: Elsevier
ISSN: 1877-0509
Date of First Compliant Deposit: 6 October 2021
Date of Acceptance: 8 June 2020
Last Modified: 07 Oct 2021 10:58
URI: http://orca.cardiff.ac.uk/id/eprint/144671

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