Motor Resonance as Indicator for Quality of Interaction - Does it Scale to Natural Movements?

This paper is the output of work that is financed by a grant by the Air Force Office for Scientific Research (AFOSR). © 2018 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.Detecting in an automatic manner whether a particular interaction between man and machine “works”, is an unsolved problem in human-machine interaction. No computational technique exists by which the artificial agent could perceive whether the interaction works from the viewpoint of the human or whether interactional breakdown is likely to occur. In human-robot interaction motor resonance has been proposed as a potential candidate for assessing what might be termed “quality of interaction”. Other authors have asserted that “the measure of resonance indicates the extent to which an artificial agent is considered as a social inter-actor” and call it “a plausible foundation for higher-order social cognition”. Motor interference is often used as a metric for resonance. While the above suggests that motor resonance might be suitable as general measure for the potential of an artificial agent to be conceived of as a social entity, the question remains whether it can be used as a measure for the quality of an ongoing interaction

Can Real-time, Adaptive Human-Robot Motor Coordination Improve Humans’ Overall Perception of a Robot?

Previous research on social interaction among humans suggested that interpersonal motor coordination can help to establish social rapport. Our research addresses the question of whether, in a human-humanoid interaction experiment, the human’s overall perception of a robot can be improved by realising motor coordination behaviour that allows the robot to adapt in real-time to a person’s behaviour. A synchrony detection method using information distance was adopted to realise the real-time human-robot motor coordination behaviour, which guided the humanoid robot to coordinate its movements to a human by measuring the behaviour synchrony between the robot and the human. The feedback of the participants indicated that most of the participants preferred to interact with the humanoid robot with the adaptive motor coordination capability. The results of this proof-of-concept study suggest that the motor coordination mechanism improved humans’ overall perception of the humanoid robot. Together with our previous findings, namely that humans actively coordinate their behaviours to a humanoid robot’s behaviours, this study further supports the hypothesis that bidirectional motor coordination could be a valid approach to facilitate adaptive human-humanoid interaction.Peer reviewedFinal Accepted Versio

Moving Just Like You: Motor Interference Depends on Similar Motility of Agent and Observer

Recent findings in neuroscience suggest an overlap between brain regions involved in the execution of movement and perception of another’s movement. This so-called “action-perception coupling” is supposed to serve our ability to automatically infer the goals and intentions of others by internal simulation of their actions. A consequence of this coupling is motor interference (MI), the effect of movement observation on the trajectory of one’s own movement. Previous studies emphasized that various features of the observed agent determine the degree of MI, but could not clarify how human-like an agent has to be for its movements to elicit MI and, more importantly, what ‘human-like’ means in the context of MI. Thus, we investigated in several experiments how different aspects of appearance and motility of the observed agent influence motor interference (MI). Participants performed arm movements in horizontal and vertical directions while observing videos of a human, a humanoid robot, or an industrial robot arm with either artificial (industrial) or human-like joint configurations. Our results show that, given a human-like joint configuration, MI was elicited by observing arm movements of both humanoid and industrial robots. However, if the joint configuration of the robot did not resemble that of the human arm, MI could longer be demonstrated. Our findings present evidence for the importance of human-like joint configuration rather than other human-like features for perception-action coupling when observing inanimate agents

From automata to animate beings: the scope and limits of attributing socialness to artificial agents

Understanding the mechanisms and consequences of attributing socialness to artificial agents has important implications for how we can use technology to lead more productive and fulfilling lives. Here, we integrate recent findings on the factors that shape behavioral and brain mechanisms that support social interactions between humans and artificial agents. We review how visual features of an agent, as well as knowledge factors within the human observer, shape attributions across dimensions of socialness. We explore how anthropomorphism and dehumanization further influence how we perceive and interact with artificial agents. Based on these findings, we argue that the cognitive reconstruction within the human observer is likely to be far more crucial in shaping our interactions with artificial agents than previously thought, while the artificial agent's visual features are possibly of lesser importance. We combine these findings to provide an integrative theoretical account based on the “like me” hypothesis, and discuss the key role played by the Theory‐of‐Mind network, especially the temporal parietal junction, in the shift from mechanistic to social attributions. We conclude by highlighting outstanding questions on the impact of long‐term interactions with artificial agents on the behavioral and brain mechanisms of attributing socialness to these agents

Towards Scalable Measures of Quality of Interaction: Motor Interference

© 2019 Copyright held by the owner/author(s).Motor resonance, the activation of an observer's motor control system by another actor's movements, has been claimed to be an indicator for quality of interaction. Motor interference as one of the consequences of the presence of resonance can be detected by analysing an actor's spatial movements. It has therefore been used as an indicator for the presence of motor resonance. Unfortunately, the experimental paradigm in which motor interference has been shown to be detectable is ecologically implausible both in terms of the types of movements employed and the number of repetitions required. In the presented experiment we tested whether some of these experimental constraints can be relaxed or modified towards a more naturalistic behaviour without losing the ability to detect the interference effect. In the literature, spatial variance has been analytically quantified in many different ways. This study found these analytical variations to be nonequivalent by implementing them. Back-and-forth transitive movements were tested for motor interference; the effect was found to be more robust than with left-right movements, though the direction of interference was opposite to that reported in the literature. We conclude that motor interference, when measured by spatial variation, lacks promise for embedding in naturalistic interaction scenarios because the effect sizes were small.Peer reviewe

A motion system for social and animated robots

This paper presents an innovative motion system that is used to control the motions and animations of a social robot. The social robot Probo is used to study Human-Robot Interactions (HRI), with a special focus on Robot Assisted Therapy (RAT). When used for therapy it is important that a social robot is able to create an "illusion of life" so as to become a believable character that can communicate with humans. The design of the motion system in this paper is based on insights from the animation industry. It combines operator-controlled animations with low-level autonomous reactions such as attention and emotional state. The motion system has a Combination Engine, which combines motion commands that are triggered by a human operator with motions that originate from different units of the cognitive control architecture of the robot. This results in an interactive robot that seems alive and has a certain degree of "likeability". The Godspeed Questionnaire Series is used to evaluate the animacy and likeability of the robot in China, Romania and Belgium

Addressing joint action challenges in HRI: Insights from psychology and philosophy

The vast expansion of research in human-robot interactions (HRI) these last decades has been accompanied by the design of increasingly skilled robots for engaging in joint actions with humans. However, these advances have encountered significant challenges to ensure fluent interactions and sustain human motivation through the different steps of joint action. After exploring current literature on joint action in HRI, leading to a more precise definition of these challenges, the present article proposes some perspectives borrowed from psychology and philosophy showing the key role of communication in human interactions. From mutual recognition between individuals to the expression of commitment and social expectations, we argue that communicative cues can facilitate coordination, prediction, and motivation in the context of joint action. The description of several notions thus suggests that some communicative capacities can be implemented in the context of joint action for HRI, leading to an integrated perspective of robotic communication.French National Research Agency (ANR) ANR-16-CE33-0017 ANR-17-EURE-0017 FrontCog ANR-10-IDEX-0001-02 PSLJuan de la Cierva-Incorporacion grant IJC2019-040199-ISpanish Government PID2019-108870GB-I00 PID2019-109764RB-I0

How can the study of action kinematics inform our understanding of human social interaction?

The kinematics of human actions are influenced by the social context in which they are performed. Motion-capture technology has allowed researchers to build up a detailed and complex picture of how action kinematics vary across different social contexts. Here we review three task domains-point-to-point imitation tasks, motor interference tasks and reach-to-grasp tasks-to critically evaluate how these tasks can inform our understanding of social interactions. First, we consider how actions within these task domains are performed in a non-social context, before highlighting how a plethora of social cues can perturb the baseline kinematics. We show that there is considerable overlap in the findings from these different tasks domains but also highlight the inconsistencies in the literature and the possible reasons for this. Specifically, we draw attention to the pitfalls of dealing with rich, kinematic data. As a way to avoid these pitfalls, we call for greater standardisation and clarity in the reporting of kinematic measures and suggest the field would benefit from a move towards more naturalistic tasks

The Impact of Context on EEG Motor Imagery Neurofeedback and Related Motor Domains

Neurofeedback (NF) is a versatile non-invasive neuromodulation technique. In combination with motor imagery (MI), NF has considerable potential for enhancing motor performance or supplementing motor rehabilitation. However, not all users achieve reliable NF control. While research has focused on various brain signal properties and the optimisation of signal processing to solve this issue, the impact of context, i.e. the conditions in which NF motor tasks occur, is comparatively unknown. We review current research on the impact of context on MI NF and related motor domains. We identify long-term factors that act at the level of the individual or of the intervention, and short-term factors, with levels before/after and during a session. The reviewed literature indicates that context plays a significant role. We propose considering context factors as well as within-level and across-level interactions when studying MI NF