Progressive Co-adaptation in Human-Machine Interaction

Gallina, Paolo; Bellotto, Nicola; Luca, Massimiliano Di

doi:10.5220/0005561003620368

Cited by 17 publications

(4 citation statements)

References 32 publications

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“…To adapt arbitration to the user and hence find the optimal amount of assistance, Oh et al [2019] propose to learn the best arbitration parameter online from the user interaction with the system. Considering in general human-machine interfaces, Gallina et al [2015] proposed an approach in between goal-oriented design (which maximizes performance) and human-centered design (which maximizes usability): progressive co-adaptation. The idea here is that as the user through interaction with the system adapts and improves their skills , concurrently the system should monitor these improvements and adjust its parameters accordingly.…”

Section: Adaptation Co-adaptation and Trusting The Assistance Systemmentioning

confidence: 99%

Gaze-based intention estimation: principles, methodologies, and applications in HRI

Belardinelli¹

2023

Preprint

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Intention prediction has become a relevant field of research in Human-Machine and Human-Robot Interaction. Indeed, any artificial system (co)-operating with and along humans, designed to assist and coordinate its actions with a human partner, would benefit from first inferring the human's current intention. To spare the user the cognitive burden of explicitly uttering their goals, this inference relies mostly on behavioral cues deemed indicative of the current action. It has been long known that eye movements are highly anticipatory of the single steps unfolding during a task, hence they can serve as a very early and reliable behavioural cue for intention recognition. This review aims to draw a line between insights in the psychological literature on visuomotor control and relevant applications of gaze-based intention recognition in technical domains, with a focus on teleoperated and assistive robotic systems.Starting from the cognitive principles underlying the relationship between intentions, eye movements, and action, the use of eye tracking and gaze-based models for intent recognition in Human-Robot Interaction is considered, with prevalent methodologies and their diverse applications. Finally, special consideration is given to relevant human factors issues and current limitations to be factored in when designing such systems.CCS Concepts: • General and reference → Surveys and overviews; • Computing methodologies → Cooperation and coordination;• Human-centered computing → HCI theory, concepts and models.

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Section: Adaptation Co-adaptation and Trusting The Assistance Systemmentioning

confidence: 99%

Gaze-based intention estimation: principles, methodologies, and applications in HRI

Belardinelli¹

2023

Preprint

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“…In more recent work, it was hypothesized that better collaborative approaches can be designed by also considering how humans change their policy by interacting with the robot [16]. Nikolaidis et al [33] introduced a formalization for mutual adaptation between a robot and a human in a collaborative task.…”

Section: Adaptation Of Roles In Phrimentioning

confidence: 99%

“…Human-machine adaptation is a widely studied field even beyond pHRI [16], implementing adaptive control schemes which conform to an unknown gain of the human [17]. Adaptation could be integrated by changing the cobot policy when thresholds of safety have been reached.…”

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confidence: 99%

The effects of role transitions and adaptation in human–cobot collaboration

et al. 2023

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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“…A richer dataset with data from naive participants would indeed provide a better characterization not only of the users' sensorimotor behavior in itself, but it would indeed allow testing for learning effects within each participant and individual differences between participants. This would also help to investigate the co-adaptation process between human and robotic systems (Gallina et al, 2015). On the one hand, indeed, visuomotor adaptation to the new environment produces effective motor learning enabling the user to better handle the initially unfamiliar sensorimotor mapping.…”

Section: Configuration (Fixation Time)mentioning

confidence: 99%

Gaze-Based Intention Estimation for Shared Autonomy in Pick-and-Place Tasks

Fuchs

Belardinelli

2021

Front. Neurorobot.

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Shared autonomy aims at combining robotic and human control in the execution of remote, teleoperated tasks. This cooperative interaction cannot be brought about without the robot first recognizing the current human intention in a fast and reliable way so that a suitable assisting plan can be quickly instantiated and executed. Eye movements have long been known to be highly predictive of the cognitive agenda unfolding during manual tasks and constitute, hence, the earliest and most reliable behavioral cues for intention estimation. In this study, we present an experiment aimed at analyzing human behavior in simple teleoperated pick-and-place tasks in a simulated scenario and at devising a suitable model for early estimation of the current proximal intention. We show that scan paths are, as expected, heavily shaped by the current intention and that two types of Gaussian Hidden Markov Models, one more scene-specific and one more action-specific, achieve a very good prediction performance, while also generalizing to new users and spatial arrangements. We finally discuss how behavioral and model results suggest that eye movements reflect to some extent the invariance and generality of higher-level planning across object configurations, which can be leveraged by cooperative robotic systems.

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Progressive Co-adaptation in Human-Machine Interaction

Cited by 17 publications

References 32 publications

Gaze-based intention estimation: principles, methodologies, and applications in HRI

Gaze-based intention estimation: principles, methodologies, and applications in HRI

The effects of role transitions and adaptation in human–cobot collaboration

Gaze-Based Intention Estimation for Shared Autonomy in Pick-and-Place Tasks

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