A Hierarchical Behavioral Dynamic Approach for Naturally Adaptive Human-Agent Pick-and-Place Interactions

Interactive or collaborative pick-and-place tasks occur during all kinds of daily activities, for example, when two or more individuals pass plates, glasses, and utensils back and forth between each other when setting a dinner table or loading a dishwasher together. In the near future, participation in these collaborative pick-and-place tasks could also include robotic assistants. However, for human-machine and human-robot interactions, interactive pick-and-place tasks present a unique set of challenges. A key challenge is that high-level task-representational algorithms and preplanned action or motor programs quickly become intractable, even for simple interaction scenarios. Here we address this challenge by introducing a bioinspired behavioral dynamic model of free-flowing cooperative pick-and-place behaviors based on low-dimensional dynamical movement primitives and nonlinear action selection functions. Further, we demonstrate that this model can be successfully implemented as an artificial agent control architecture to produce effective and robust human-like behavior during human-agent interactions. Participants were unable to explicitly detect whether they were working with an artificial (model controlled) agent or another human-coactor, further illustrating the potential effectiveness of the proposed modeling approach for developing systems of robust real/embodied human-robot interaction more generally.

Download Full-text

Intersubjectivity in human–agent interaction

Interaction Studies ◽

10.1075/is.8.3.05cas ◽

2007 ◽

Vol 8 (3) ◽

pp. 391-410 ◽

Cited By ~ 20

Author(s):

Justine Cassell ◽

Andrea Tartaro

Keyword(s):

Human Robot Interaction ◽

Embodied Conversational Agents ◽

Conversational Agents ◽

Robot Interaction ◽

Human Agent ◽

Unconscious Communication ◽

Agent Interaction ◽

And Behavior ◽

And Robotics

What is the hallmark of success in human–agent interaction? In animation and robotics, many have concentrated on the looks of the agent — whether the appearance is realistic or lifelike. We present an alternative benchmark that lies in the dyad and not the agent alone: Does the agent’s behavior evoke intersubjectivity from the user? That is, in both conscious and unconscious communication, do users react to behaviorally realistic agents in the same way they react to other humans? Do users appear to attribute similar thoughts and actions? We discuss why we distinguish between appearance and behavior, why we use the benchmark of intersubjectivity, our methodology for applying this benchmark to embodied conversational agents (ECAs), and why we believe this benchmark should be applied to human–robot interaction.

Download Full-text

Exploring the Effect of Communication Patterns and Transparency on Performance in a Human-Robot Team

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1071181319631054 ◽

2019 ◽

Vol 63 (1) ◽

pp. 160-164 ◽

Cited By ~ 1

Author(s):

Shan G. Lakhmani ◽

Julia L. Wright ◽

Michael R. Schwartz ◽

Daniel Barber

Keyword(s):

Information Sharing ◽

Team Performance ◽

Human Performance ◽

Target Identification ◽

Communication Patterns ◽

Human Robot Interaction ◽

Communication Pattern ◽

Identification Task ◽

Robot Interaction ◽

Human Agent

Human-robot interaction requires communication, however what form this communication should take to facilitate effective team performance is still undetermined. One notion is that effective human-agent communications can be achieved by combining transparent information-sharing techniques with specific communication patterns. This study examines how transparency and a robot’s communication patterns interact to affect human performance in a human-robot teaming task. Participants’ performance in a target identification task was affected by the robot’s communication pattern. Participants missed identifying more targets when they worked with a bidirectionally communicating robot than when they were working with a unidirectionally communicating one. Furthermore, working with a bidirectionally communicating robot led to fewer correct identifications than working with a unidirectionally communicating robot, but only when the robot provided less transparency information. The implications these findings have for future robot interface designs are discussed.

Download Full-text

An innovative high-level human-robot interaction for disabled persons

IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 ◽

10.1109/robot.2004.1307406 ◽

2004 ◽

Cited By ~ 8

Author(s):

P. Nilas ◽

P. Rani ◽

N. Sarkar

Keyword(s):

Disabled Persons ◽

Human Robot Interaction ◽

Robot Interaction ◽

High Level

Download Full-text

Empirical Aesthetics, Computational Cognitive Modeling, and Experimental Phenomenology: Methodological remarks on “Shaping and Co-Shaping Forms of Vitality in Music: Beyond Cognitivist and Emotivist Approaches to Musical Expressiveness” by Jin Hyun Kim

Empirical Musicology Review ◽

10.18061/emr.v8i3-4.3939 ◽

2013 ◽

Vol 8 (3-4) ◽

pp. 178

Author(s):

Uwe Seifert

Keyword(s):

Cognitive Modeling ◽

Emotional Processing ◽

Affective Computing ◽

Human Robot Interaction ◽

Empirical Adequacy ◽

Robot Interaction ◽

Experimental Phenomenology ◽

Computational Cognitive Modeling ◽

The Mind ◽

Near Future

The core ideas of the proposed framework for empirical aesthetics are interpreted as focusing on processes, interaction, and phenomenological experience. This commentary first touches on some methodological impediments to developing theories of processing and interaction, and emphasizes the necessity of computational cognitive modeling using robots to test the empirical adequacy of such theories. Further, the importance of developing and integrating phenomenological methods into current experimental research is stressed, using experimental phenomenology as reference. Situated cognition, affective computing, human-robot interaction research, computational cognitive modeling and social and cultural neuroscience are noted as providing relevant insight into the empirical adequacy of current theories of cognitive and emotional processing. In the near future these fields will have a stimulating impact on empirical aesthetics and research on music and the mind.

Download Full-text

A Human-Robot Cooperative and Personalized Compliant Joint Controller for Upper-Limb Rehabilitation Robots: The Elbow Joint Validation

10.21203/rs.3.rs-595139/v1 ◽

2021 ◽

Author(s):

Stefano Dalla Gasperina ◽

Valeria Longatelli ◽

Francesco Braghin ◽

Alessandra Laura Giulia Pedrocchi ◽

Marta Gandolla

Keyword(s):

Upper Limb ◽

Human Robot Interaction ◽

Control Law ◽

Robot Interaction ◽

Activation Patterns ◽

Upper Limb Rehabilitation ◽

Control Framework ◽

High Level ◽

Limb Rehabilitation ◽

Muscular Activation

Abstract Background: Appropriate training modalities for post-stroke upper-limb rehabilitation are key features for effective recovery after the acute event. This work presents a novel human-robot cooperative control framework that promotes compliant motion and renders different high-level human-robot interaction rehabilitation modalities under a unified low-level control scheme. Methods: The presented control law is based on a loadcell-based impedance controller provided with positive-feedback compensation terms for disturbances rejection and dynamics compensation. We developed an elbow flexion-extension experimental setup, and we conducted experiments to evaluate the controller performances. Seven high-level modalities, characterized by different levels of (i) impedance-based corrective assistance, (ii) weight counterbalance assistance, and (iii) resistance, have been defined and tested with 14 healthy volunteers.Results: The unified controller demonstrated suitability to promote good transparency and render compliant and high-impedance behavior at the joint. Superficial electromyography results showed different muscular activation patterns according to the rehabilitation modalities. Results suggested to avoid weight counterbalance assistance, since it could induce different motor relearning with respect to purely impedance-based corrective strategies. Conclusion: We proved that the proposed control framework could implement different physical human-robot interaction modalities and promote the assist-as-needed paradigm, helping the user to accomplish the task, while maintaining physiological muscular activation patterns. Future insights involve the extension to multiple degrees of freedom robots and the investigation of an adaptation control law that makes the controller learn and adapt in a therapist-like manner.

Download Full-text

I–C–E Framework: Concepts for Group Dynamics Research in Human-Robot Interaction

International Journal of Social Robotics ◽

10.1007/s12369-020-00642-z ◽

2020 ◽

Vol 12 (6) ◽

pp. 1213-1229

Author(s):

Anna M. H. Abrams ◽

Astrid M. Rosenthal-von der Pütten

Keyword(s):

Social Sciences ◽

Group Dynamics ◽

Theoretical Foundation ◽

Human Robot Interaction ◽

Future Research ◽

Robot Interaction ◽

The Past ◽

Social Settings ◽

The Social ◽

Near Future

AbstractThe research community of human-robot interaction relies on theories and phenomena from the social sciences in order to study and validate robotic developments in interaction. These studies mainly concerned one (human) on one (robot) interactions in the past. The present paper shifts the attention to groups and group dynamics and reviews relevant concepts from the social sciences: ingroup identification (I), cohesion (C) and entitativity (E). Ubiquitous robots will be part of larger social settings in the near future. A conceptual framework, the I–C–E framework, is proposed as a theoretical foundation for group (dynamics) research in HRI. Additionally, we present methods and possible measures for these relevant concepts and outline topics for future research.

Download Full-text

The Relationship Between Trust and Use Choice in Human-Robot Interaction

Human Factors The Journal of the Human Factors and Ergonomics Society ◽

10.1177/0018720818816838 ◽

2019 ◽

Vol 61 (4) ◽

pp. 614-626 ◽

Cited By ~ 10

Author(s):

Tracy Sanders ◽

Alexandra Kaplan ◽

Ryan Koch ◽

Michael Schwartz ◽

P. A. Hancock

Keyword(s):

General Assumption ◽

Human Robot Interaction ◽

Primary Concern ◽

Income Loss ◽

Robot Interaction ◽

Loss Of Life ◽

Human Agent ◽

The Relationship ◽

Robotic Agent ◽

Trust Scale

Objective: To understand the influence of trust on use choice in human-robot interaction via experimental investigation. Background: The general assumption that trusting a robot leads to using that robot has been previously identified, often by asking participants to choose between manually completing a task or using an automated aid. Our work further evaluates the relationship between trust and use choice and examines factors impacting choice. Method: An experiment was conducted wherein participants rated a robot on a trust scale, then made decisions about whether to use that robotic agent or a human agent to complete a task. Participants provided explicit reasoning for their choices. Results: While we found statistical support for the “trust leads to use” relationship, qualitative results indicate other factors are important as well. Conclusion: Results indicated that while trust leads to use, use is also heavily influenced by the specific task at hand. Users more often chose a robot for a dangerous task where loss of life is likely, citing safety as their primary concern. Conversely, users chose humans for the mundane warehouse task, mainly citing financial reasons, specifically fear of job and income loss for the human worker. Application: Understanding the factors driving use choice is key to appropriate interaction in the field of human-robot teaming.

Download Full-text