HRI in an ecological dynamic experiment: The GEE corpus based approach for the Emox robot

Guillaume, Leslie; Auberge, Véronique; Magnani, Romain; Aman, Frédéric; Cottier, Cécile; Sasa, Yuko; Wolf, Christian; Nebout, Florian; Neverova, Natalia; Bonnefond, Nicolas; Nègre, Amaury; Tsvetanova, Liliya; Girard-Rivier, Maxence

doi:10.1109/arso.2015.7428207

Cited by 4 publications

(4 citation statements)

References 17 publications

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“…Firstly, we present our experiment conducted in lab conditions, similar to those in [3]. Secondly, we present the results of two experiments conducted in ecological conditions 3 as in the Living Lab method [10]. To this end, we used our dynamic specification of utility parameters to switch between the following settings for (d rp , θ rp ): setting 0 (0.8m, π/2rad) (beside person), and setting 1 (0.8m, πrad) (behind person).…”

Section: Methodsmentioning

confidence: 99%

“…Human perception of physical and social variables is known to be influenced by environmental and situational factors [5], [6], [7], [8], [9]. HRI studies on gestures [10], speech interaction [11], gaze and position [12] have shown that the way people interact with and perceive a robot can depend on the type of experimental conditions (lab or ecological), as well as how the robot behaves, and the situation or context in which it is deployed [13]. Experimentation in ecological conditions followed by a critical analysis of the human-robot system is therefore key to truly test the robot and understand how people react to it, what people think of it, and how it should evolve.…”

Section: Related Workmentioning

confidence: 99%

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Studying Navigation as a Form of Interaction: a Design Approach for Social Robot Navigation Methods

Scales

Aycard

Auberge

2020

2020 IEEE International Conference on Robotics and Automation (ICRA)

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Social Navigation methods attempt to integrate knowledge from Human Sciences fields such as the notion of Proxemics into mobile robot navigation. They are often evaluated in simulations, or lab conditions with informed participants, and studies of the impact of the robot behavior on humans are rare. Humans communicate and interact through many vectors, among which are motion and positioning, which can be related to social hierarchy and the socio-physical context. If a robot is to be deployed among humans, the methods it uses should be designed with this in mind. This work acts as the first step in an ongoing project in which we explore how to design navigation methods for mobile robots destined to be deployed among humans. We aim to consider navigation as more than just a functionality of the robot, and to study the impact of robot motion on humans. In this paper, we focus on the personfollowing task. We selected a state of the art person-following method as the basis for our method, which we modified and extended in order for it to be more general and adaptable. We conducted pilot experiments using this method on a real mobile robot in ecological contexts. We used results from the experiments to study the Human-Robot Interaction as a whole by analysing both the person-following method and the human behavior. Our preliminary results show that the way in which the robot followed a person had an impact on the interaction that emerged between them.

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Section: Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Studying Navigation as a Form of Interaction: a Design Approach for Social Robot Navigation Methods

Scales

Aycard

Auberge

2020

2020 IEEE International Conference on Robotics and Automation (ICRA)

Self Cite

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show abstract

“…Although these metrics are useful, there are still issues with the acceptability of mobile robots, particularly when humans attribute social intentions or attitudes to a mobile robot's navigation. Vocal prosody (pitch, rhythm, and tone) has been widely studied as a means to convey social attitudes and relation information in interactions between both humans and robots [26,27]. In addition to studying vocal prosody, ref.…”

Section: State Of the Art 21 Design And Evaluation Of Social Navigati...mentioning

confidence: 99%

“…The remaining scales capture physical perceptions of the robot, with Sturdy-Frail, Strong-Weak, Smooth-Abrupt, and Rigid-Supple. The scales were chosen based on words that participants in prior HRI studies had used to self-annotate their own recorded interaction data after a long experiment with a small butler robot [26,27]. For more details about the choice of the adjectives in our scales, we refer the reader to [30].…”

Section: Perceptual Scalesmentioning

confidence: 99%

Planning Socially Expressive Mobile Robot Trajectories

Scales,

Aycard,

Aubergé

2024

Sensors

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Many mobile robotics applications require robots to navigate around humans who may interpret the robot’s motion in terms of social attitudes and intentions. It is essential to understand which aspects of the robot’s motion are related to such perceptions so that we may design appropriate navigation algorithms. Current works in social navigation tend to strive towards a single ideal style of motion defined with respect to concepts such as comfort, naturalness, or legibility. These algorithms cannot be configured to alter trajectory features to control the social interpretations made by humans. In this work, we firstly present logistic regression models based on perception experiments linking human perceptions to a corpus of linear velocity profiles, establishing that various trajectory features impact human social perception of the robot. Secondly, we formulate a trajectory planning problem in the form of a constrained optimization, using novel constraints that can be selectively applied to shape the trajectory such that it generates the desired social perception. We demonstrate the ability of the proposed algorithm to accurately change each of the features of the generated trajectories based on the selected constraints, enabling subtle variations in the robot’s motion to be consistently applied. By controlling the trajectories to induce different social perceptions, we provide a tool to better tailor the robot’s actions to its role and deployment context to enhance acceptability.

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From vocal prosody to movement prosody, from HRI to understanding humans

Scales,

Aubergé,

Aycard

2023

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Human–Human and Human–Robot Interaction are known to be influenced by a variety of modalities and parameters. Nevertheless, it remains a challenge to anticipate how a given mobile robot’s navigation and appearance will impact how it is perceived by humans. Drawing a parallel with vocal prosody, we introduce the notion of movement prosody, which encompasses spatio-temporal and appearance dimensions which are involved in a person’s perceptual experience of interacting with a mobile robot. We design a novel robot motion corpus, encompassing variables related to the kinematics, gaze, and appearance of the robot, which we hypothesize are involved in movement prosody. Initial results of three perception experiments suggest that these variables have significant influences on participants’ perceptions of robot socio-affects and physical attributes.

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HRI in an ecological dynamic experiment: The GEE corpus based approach for the Emox robot

Cited by 4 publications

References 17 publications

Studying Navigation as a Form of Interaction: a Design Approach for Social Robot Navigation Methods

Studying Navigation as a Form of Interaction: a Design Approach for Social Robot Navigation Methods

Planning Socially Expressive Mobile Robot Trajectories

From vocal prosody to movement prosody, from HRI to understanding humans

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