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Boucher C, Stower R, Varadharajan VS, Zibetti E, Levillain F, St-Onge D. Motion-based communication for robotic swarms in exploration missions. Auton Robots 2023. [DOI: 10.1007/s10514-022-10079-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
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MoTiS Parameters for Expressive Multi-Robot Systems: Relative Motion, Timing, and Spacing. Int J Soc Robot 2022; 14:1965-1993. [PMID: 36277304 PMCID: PMC9576134 DOI: 10.1007/s12369-022-00936-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/05/2022] [Indexed: 11/03/2022]
Abstract
Multi-robot systems are moving into human spaces, such as working with people in factories (Bacula et al., in: Companion of the 2020 ACM/IEEE international conference on human–robot interaction, pp 119–121, 2020) or in emergency support (Wagner in Front Robot AI 8, 2021; Baxter et al., in: Autonomous robots and agents, Springer, pp 9–16, 2007) and it is crucial to consider how robots can communicate with the humans in the space. Our work evaluates a parameter framework to allow multi-robot groups of x, y, \documentclass[12pt]{minimal}
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\begin{document}$$\theta $$\end{document}θ robots to effectively communicate using expressive motion. While expressive motion has been extensively studied in single robots (Knight et al., in: 2016 IEEE international conference on intelligent robots and systems (IROS), IEEE, 2016; Bacula and LaViers in Int J Soc Robot, 1–16, 2020; Dragan et al., in: 2013 8th ACM/IEEE international conference on human–robot interaction (HRI), IEEE, pp 301–308, 2013; Kirby et al., in: The 18th IEEE international symposium on robot and human interactive communication, 2009, RO-MAN 2009, IEEE, pp 607–612, 2009), moving to multi-robots creates new challenges as the state space expands and becomes more complex. We evaluate a hierarchical framework of six parameters to generate multi-robot expressive motion consisting of: (1) relative direction, (2) coherence, (3) relative speed, (4) relative start time, (5) proximity, and (6) geometry. We conducted six independent online studies to explore each parameter, finding that four out of six of the parameters had significant impact on people’s perception of the multi-robot group. Additional takeaways of our studies clarify what humans interpret as a robot group, when the group is perceived positively versus negatively, and the critical role of architectural floor plan in interpreting robot intent.
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Lomas JD, Lin A, Dikker S, Forster D, Lupetti ML, Huisman G, Habekost J, Beardow C, Pandey P, Ahmad N, Miyapuram K, Mullen T, Cooper P, van der Maden W, Cross ES. Resonance as a Design Strategy for AI and Social Robots. Front Neurorobot 2022; 16:850489. [PMID: 35574227 PMCID: PMC9097027 DOI: 10.3389/fnbot.2022.850489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 03/23/2022] [Indexed: 11/20/2022] Open
Abstract
Resonance, a powerful and pervasive phenomenon, appears to play a major role in human interactions. This article investigates the relationship between the physical mechanism of resonance and the human experience of resonance, and considers possibilities for enhancing the experience of resonance within human-robot interactions. We first introduce resonance as a widespread cultural and scientific metaphor. Then, we review the nature of "sympathetic resonance" as a physical mechanism. Following this introduction, the remainder of the article is organized in two parts. In part one, we review the role of resonance (including synchronization and rhythmic entrainment) in human cognition and social interactions. Then, in part two, we review resonance-related phenomena in robotics and artificial intelligence (AI). These two reviews serve as ground for the introduction of a design strategy and combinatorial design space for shaping resonant interactions with robots and AI. We conclude by posing hypotheses and research questions for future empirical studies and discuss a range of ethical and aesthetic issues associated with resonance in human-robot interactions.
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Affiliation(s)
- James Derek Lomas
- Department of Human Centered Design, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, Netherlands
| | - Albert Lin
- Center for Human Frontiers, Qualcomm Institute, University of California, San Diego, San Diego, CA, United States
| | - Suzanne Dikker
- Department of Psychology, New York University, New York, NY, United States
- Department of Clinical Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Deborah Forster
- Center for Human Frontiers, Qualcomm Institute, University of California, San Diego, San Diego, CA, United States
| | - Maria Luce Lupetti
- Department of Human Centered Design, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, Netherlands
| | - Gijs Huisman
- Department of Human Centered Design, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, Netherlands
| | - Julika Habekost
- The Design Lab, California Institute of Information and Communication Technologies, University of California, San Diego, San Diego, CA, United States
| | - Caiseal Beardow
- Department of Human Centered Design, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, Netherlands
| | - Pankaj Pandey
- Centre for Cognitive and Brain Sciences, Indian Institute of Technology, Gandhinagar, India
| | - Nashra Ahmad
- Centre for Cognitive and Brain Sciences, Indian Institute of Technology, Gandhinagar, India
| | - Krishna Miyapuram
- Centre for Cognitive and Brain Sciences, Indian Institute of Technology, Gandhinagar, India
| | - Tim Mullen
- Intheon Labs, San Diego, CA, United States
| | - Patrick Cooper
- Department of Physics, Duquesne University, Pittsburgh, PA, United States
| | - Willem van der Maden
- Department of Human Centered Design, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, Netherlands
| | - Emily S. Cross
- Social Robotics, Institute of Neuroscience and Psychology, School of Computing Science, University of Glasgow, Glasgow, United Kingdom
- SOBA Lab, School of Psychology, Macquarie University, Sydney, NSW, Australia
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Ercengiz M, Safalı S, Kaya A, Turan ME. A hypothetic model for examining the relationship between happiness, forgiveness, emotional reactivity and emotional security. CURRENT PSYCHOLOGY 2022; 42:1-15. [PMID: 35370385 PMCID: PMC8960667 DOI: 10.1007/s12144-022-02909-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/11/2022] [Indexed: 11/25/2022]
Abstract
The ultimate goal of life is happiness, according to Plato. Perhaps the most critical questions in the life of human beings have been on happiness and processes that affect happiness. The present study was planned during the COVID-19 pandemic; perhaps human beings are most needed for happiness. The original hypothetical model and the findings constitute the powerful and different aspects of the present study. This study determined a hypothetical model to examine the relationships among happiness, forgiveness, emotional reactivity, and emotional security. The participant group of the study consists of a total of 916 individuals from Turkey, 617 women, and 299 men. The age scale of the participants is between 18-25. Participants completed the Heartland Forgiveness Scale, the Emotional Security Scale, the Emotional Reactivity Scale, and the Oxford Happiness Scale. Mediation analysis was conducted using Hayes' (2017) process macro. According to the proposed model in the study, emotional reactivity mediates the relationship between forgiveness and happiness. As the individual's forgiveness increases, their emotional reactivity decreases, and as the emotional reactivity decreases, the individual's level of happiness increases.
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Affiliation(s)
- Mustafa Ercengiz
- Faculty of Education, Agri Ibrahim Cecen University, Agri, Turkey
| | - Serdar Safalı
- Faculty of Education, Agri Ibrahim Cecen University, Agri, Turkey
| | - Alican Kaya
- Faculty of Education, Agri Ibrahim Cecen University, Agri, Turkey
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Hebbar V, Langbort C. A Model for Tacit Communication in Collaborative Human-UAV Search-and-Rescue. ENTROPY (BASEL, SWITZERLAND) 2021; 23:1027. [PMID: 34441168 PMCID: PMC8392000 DOI: 10.3390/e23081027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 08/06/2021] [Accepted: 08/06/2021] [Indexed: 11/21/2022]
Abstract
Tacit communication can be exploited in human robot interaction (HRI) scenarios to achieve desirable outcomes. This paper models a particular search and rescue (SAR) scenario as a modified asymmetric rendezvous game, where limited signaling capabilities are present between the two players-rescuer and rescuee. We model our situation as a co-operative Stackelberg signaling game, where the rescuer acts as a leader in signaling its intent to the rescuee. We present an efficient game-theoretic approach to obtain the optimal signaling policy to be employed by the rescuer. We then robustify this approach to uncertainties in the rescue topology and deviations in rescuee behavior. The paper thus introduces a game-theoretic framework to model an HRI scenario with implicit communication capacity.
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Affiliation(s)
- Vijeth Hebbar
- Coordinated Science Laboratory, University of Illinois Urbana-Champaign, Champaign, IL 61820, USA;
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Santos M, Notomista G, Mayya S, Egerstedt M. Interactive Multi-Robot Painting Through Colored Motion Trails. Front Robot AI 2020; 7:580415. [PMID: 33501341 PMCID: PMC7806061 DOI: 10.3389/frobt.2020.580415] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 09/11/2020] [Indexed: 11/13/2022] Open
Abstract
In this paper, we present a robotic painting system whereby a team of mobile robots equipped with different color paints create pictorial compositions by leaving trails of color as they move throughout a canvas. We envision this system to be used by an external user who can control the concentration of different colors over the painting by specifying density maps associated with the desired colors over the painting domain, which may vary over time. The robots distribute themselves according to such color densities by means of a heterogeneous distributed coverage control paradigm, whereby only those robots equipped with the appropriate paint will track the corresponding color density function. The painting composition therefore arises as the integration of the motion trajectories of the robots, which lay paint as they move throughout the canvas tracking the color density functions. The proposed interactive painting system is evaluated on a team of mobile robots. Different experimental setups in terms of paint capabilities given to the robots highlight the effects and benefits of considering heterogeneous teams when the painting resources are limited.
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Affiliation(s)
- María Santos
- School of Electrical and Computer Engineering, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA, United States
| | - Gennaro Notomista
- School of Mechanical Engineering, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA, United States
| | - Siddharth Mayya
- GRASP Laboratory, University of Pennsylvania, Philadelphia, PA, United States
| | - Magnus Egerstedt
- School of Electrical and Computer Engineering, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA, United States
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