Evaluating and Enhancing Human-Robot Interaction for Multiple Diverse Users in a Real-World Context

Lead Research Organisation: University of Glasgow
Department Name: School of Computing Science


The increasing availability of socially-intelligent robots with functionality for a range of purposes, from guidance in museums (Gehle et al., 2015), to companionship for the elderly (Hebesberger et al., 2016), has motivated a growing number of studies attempting to evaluate and enhance Human-Robot Interaction (HRI). But, as Honig and Oron-Gilad (2018) review of recent work on understanding and resolving failures in HRI observes, most research has focused on technical ways of improving robot reliability. They argue that progress requires a "holistic approach" in which "[t]he technical knowledge of hardware and software must be integrated with cognitive aspects of information processing, psychological knowledge of interaction dynamics, and domain-specific knowledge of the user, the robot, the target application, and the environment" (p.16). Honig and Oron-Gilad point to a particular need to improve the ecological validity of evaluating user communication in HRI, by moving away from experimental, single-person environments, with low-relevance tasks, mainly with younger adult users, to more natural settings, with users of different social profiles and communication strategies, where the outcome of successful HRI matters.
The main contribution of this PhD project is to develop an interdisciplinary approach to evaluating and enhancing communication efficacy of HRI, by combining state-of-the-art social robotics with theory and methods from socially-informed linguistics (Coupland, Sarangi & Candlin, 2014) and conversation analysis (Clift, 2016). Specifically, the project aims to improve HRI with the newly-developed MultiModal Mall Entertainment Robot (MuMMER). MuMMER is a humanoid robot, based on the SoftBank Robotics' Pepper robot, which has been designed to interact naturally and autonomously in the communicatively-challenging space of a public shopping centre/mall with unlimited possible users of differing social backgrounds and communication styles (Foster et al., 2016). MuMMER's role is to entertain and engage visitors to the shopping mall, thereby enhancing their overall experience in the mall. This in turn requires ensuring successful HRI which is socially acceptable, helpful and entertaining for multiple, diverse users in a real-world context. As of June 2019, the technical development of the MuMMER system has been nearly completed, and the final robot system will be located for 3 months in a shopping mall in Finland during the autumn of 2019.
The PhD project will evalute HRI with MuMMER in a new context, a large shopping mall in an English-speaking context, in Scotland's largest, and most socially and ethnically-diverse city, Glasgow. Project objectives are to:
Design a set of sociolinguistically-informed observational studies of HRI with MuMMER in situ with users from a range of social, ethnic, and language backgrounds, using direct and indirect methods
Identify the minimal technical modification(dialogue, non-verbal, other) to optimise HRI, and thereby user experience and engagement, also considering indices such as consumer footfall to the mall
Implement technical alterations, and re-evaluate with new users.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S02266X/1 30/06/2019 31/12/2027
2280395 Studentship EP/S02266X/1 30/09/2019 31/03/2024 Rhiannon Fyfe