publication . Article . Preprint . 2020

A Socially Adaptable Framework for Human-Robot Interaction

Ana Tanevska; Ana Tanevska; Ana Tanevska; Francesco Rea; Giulio Sandini; Lola Cañamero; Alessandra Sciutti;
Open Access English
  • Published: 19 Oct 2020 Journal: Frontiers in Robotics and AI, volume 7 (issn: 2296-9144, Copyright policy)
  • Publisher: Frontiers Media S.A.
Abstract
In our everyday lives we regularly engage in complex, personalized, and adaptive interactions with our peers. To recreate the same kind of rich, human-like interactions, a social robot should be aware of our needs and affective states and continuously adapt its behavior to them. Our proposed solution is to have the robot learn how to select the behaviors that would maximize the pleasantness of the interaction for its peers. To make the robot autonomous in its decision making, this process could be guided by an internal motivation system. We wish to investigate how an adaptive robotic framework of this kind would function and personalize to different users. We also wish to explore whether the adaptability and personalization would bring any additional richness to the human-robot interaction (HRI), or whether it would instead bring uncertainty and unpredictability that would not be accepted by the robot's human peers. To this end, we designed a socially adaptive framework for the humanoid robot iCub. As a result, the robot perceives and reuses the affective and interactive signals from the person as input for the adaptation based on internal social motivation. We strive to investigate the value of the generated adaptation in our framework in the context of HRI. In particular, we compare how users will experience interaction with an adaptive versus a non-adaptive social robot. To address these questions, we propose a comparative interaction study with iCub whereby users act as the robot's caretaker, and iCub's social adaptation is guided by an internal comfort level that varies with the stimuli that iCub receives from its caretaker. We investigate and compare how iCub's internal dynamics would be perceived by people, both in a condition when iCub does not personalize its behavior to the person, and in a condition where it is instead adaptive. Finally, we establish the potential benefits that an adaptive framework could bring to the context of repeated interactions with a humanoid robot.
Persistent Identifiers
Subjects
free text keywords: human-robot interaction, social adaptability, affective interaction, personalized HRI, emotion recognition, Artificial Intelligence, Computer Science Applications, Social robots and social learning, Human-human and human-robot interaction and communication, Architectures for Cognitive Development and Open-Ended Learning, Robotics and AI, Original Research, Computer Science - Robotics, lcsh:Mechanical engineering and machinery, lcsh:TJ1-1570, lcsh:Electronic computers. Computer science, lcsh:QA75.5-76.95, Personalization, Human–computer interaction, Adaptation (computer science), Humanoid robot, Context (language use), Human–robot interaction, iCub, Robot, Computer science, Social robot
Funded by
EC| wHiSPER
Project
wHiSPER
investigating Human Shared PErception with Robots
  • Funder: European Commission (EC)
  • Project Code: 804388
  • Funding stream: H2020 | ERC | ERC-STG
Validated by funder
36 references, page 1 of 3

[1] Lindblom B (1990) Explaining phonetic variation: A sketch of the h&h theory. In: Speech production and speech modelling, Springer, pp 403{439 [OpenAIRE]

[2] Savidis A, Stephanidis C (2009) Uni ed design for user interface adaptation. [OpenAIRE]

[3] Mehrabian A, Epstein N (1972) A measure of emotional empathy 1. Journal of personality 40(4):525{543 [OpenAIRE]

[4] Kidd CD, Taggart W, Turkle S (2006) A sociable robot to encourage social interaction among the elderly. In: Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006., IEEE, pp 3972{3976 [OpenAIRE]

[5] Broadbent E, Jayawardena C, Kerse N, Sta ord RQ, MacDonald BA (2011) Human-robot interaction research to improve quality of life in elder carean approach and issues. In: Workshops at the TwentyFifth AAAI Conference on Arti cial Intelligence

[6] Sharkey A (2014) Robots and human dignity: a consideration of the e ects of robot care on the dignity of older people. Ethics and Information Technology 16(1):63{75

[7] Wood LJ, Zaraki A, Walters ML, Novanda O, Robins B, Dautenhahn K (2017) The iterative development of the humanoid robot kaspar: An assistive robot for children with autism. In: International Conference on Social Robotics, Springer, pp 53{63 [OpenAIRE]

[8] Plaisant C, Druin A, Lathan C, Dakhane K, Edwards K, Vice JM, Montemayor J (2000) A storytelling robot for pediatric rehabilitation. In: Proceedings of the fourth international ACM conference on Assistive technologies, ACM, pp 50{55 [OpenAIRE]

[9] Admoni H, Scassellati B (2014) Data-driven model of nonverbal behavior for socially assistive humanrobot interactions. In: Proceedings of the 16th International Conference on Multimodal Interaction, ACM, pp 196{199 [OpenAIRE]

[10] Paiva A, Leite I, Ribeiro T (2014) Emotion modeling for social robots. The Oxford handbook of a ective computing pp 296{308

[11] Tanaka F, Matsuzoe S (2012) Children teach a care-receiving robot to promote their learning: Field experiments in a classroom for vocabulary learning. Journal of Human-Robot Interaction 1(1)

[12] Ramachandran A, Litoiu A, Scassellati B (2016) Shaping productive help-seeking behavior during robotchild tutoring interactions. In: The Eleventh ACM/IEEE International Conference on Human Robot Interaction, IEEE Press, pp 247{254 [OpenAIRE]

[13] Jimenez F, Yoshikawa T, Furuhashi T, Kanoh M (2015) An emotional expression model for educationalsupport robots. Journal of Arti cial Intelligence and Soft Computing Research 5(1):51{57

[14] Ahmad MI, Mubin O, Shahid S, Orlando J (2019) Robots adaptive emotional feedback sustains childrens social engagement and promotes their vocabulary learning: a long-term child{robot interaction study. Adaptive Behavior 27(4):243{266

[15] Vaufreydaz D, Johal W, Combe C (2016) Starting engagement detection towards a companion robot using multimodal features. Robotics and Autonomous Systems 75:4{16

36 references, page 1 of 3
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