An admittance-controlled wheeled mobile manipulator for mobility assistance: Human–robot interaction estimation and redundancy resolution for enhanced force exertion ability

As mobile robots experience increased commercialization, development of intuitive interfaces for human-robot interaction gains paramount importance to promote pervasive adoption of such robots in society. Although smart devices may be useful to operate robots, prior research has not fully investigated the appropriateness of various interaction elements (e.g., touch, gestures, sensors, etc.) to render an effective human-robot interface. This paper provides overviews of a mobile manipulator and a tablet-based application to operate the mobile manipulator. In particular, a mobile manipulator is designed to navigate an obstacle course and to pick and place objects around the course, all under the control of a human operator who uses a tablet-based application. The tablet application provides the user live videos that are captured and streamed by a camera onboard the robot and an overhead camera. In addition, to remotely operate the mobile manipulator, the tablet application provides the user a menu of four interface element options, including, virtual buttons, virtual joysticks, touchscreen gesture, and tilting the device. To evaluate the intuitiveness of the four interface elements for operating the mobile manipulator, a user study is conducted in which participants’ performance is monitored as they operate the mobile manipulator using the designed interfaces. The analysis of the user study shows that the tablet-based application allows even non-experienced users to operate the mobile manipulator without the need for extensive training.

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Adaptive and safe mobile manipulator for human robot interaction

2013 IEEE Workshop on Robotic Intelligence in Informationally Structured Space (RiiSS) ◽

10.1109/riiss.2013.6607926 ◽

2013 ◽

Cited By ~ 1

Author(s):

Amal Meddahi ◽

Ryad Chellali

Keyword(s):

Human Robot Interaction ◽

Mobile Manipulator ◽

Robot Interaction

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A Comparison of Bystander and Team Member Distance in Human--Robot Interaction

PsycEXTRA Dataset ◽

10.1037/e543912014-001 ◽

2014 ◽

Author(s):

Mitchell S. Dunfee ◽

Tracy Sanders ◽

Peter A. Hancock

Keyword(s):

Team Member ◽

Human Robot Interaction ◽

Robot Interaction

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Modeling Human-Robot Interaction with Petri-Nets

PsycEXTRA Dataset ◽

10.1037/e578522012-052 ◽

2009 ◽

Cited By ~ 1

Author(s):

Rosemarie Yagoda ◽

Michael D. Coovert

Keyword(s):

Petri Nets ◽

Human Robot Interaction ◽

Robot Interaction

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Workload in Human-Robot Interaction: A Review of Manipulations and Outcomes

PsycEXTRA Dataset ◽

10.1037/e578522012-048 ◽

2009 ◽

Author(s):

Matthew S. Prewett ◽

Kristin N. Saboe ◽

Ryan C. Johnson ◽

Michael D. Coovert ◽

Linda R. Elliott

Keyword(s):

Human Robot Interaction ◽

Robot Interaction

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Biomimetic, sociable robots for human-robot interaction

PsycEXTRA Dataset ◽

10.1037/e584072011-013 ◽

2010 ◽

Author(s):

Eleanore Edson ◽

Judith Lytle ◽

Thomas McKenna

Keyword(s):

Human Robot Interaction ◽

Robot Interaction

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The role and relationship of mindreading and social attunement in HRI – position statements of interdisciplinary researchers. Workshop HRI'20

10.31234/osf.io/3p6cd ◽

2020 ◽

Author(s):

Agnieszka Wykowska ◽

Jairo Pérez-Osorio ◽

Stefan Kopp

Keyword(s):

Mental States ◽

Human Robot Interaction ◽

Human Interaction ◽

Artificial Agents ◽

The Novel ◽

Robot Interaction ◽

Novel Coronavirus ◽

Relationship Of ◽

The Relationship

This booklet is a collection of the position statements accepted for the HRI’20 conference workshop “Social Cognition for HRI: Exploring the relationship between mindreading and social attunement in human-robot interaction” (Wykowska, Perez-Osorio & Kopp, 2020). Unfortunately, due to the rapid unfolding of the novel coronavirus at the beginning of the present year, the conference and consequently our workshop, were canceled. On the light of these events, we decided to put together the positions statements accepted for the workshop. The contributions collected in these pages highlight the role of attribution of mental states to artificial agents in human-robot interaction, and precisely the quality and presence of social attunement mechanisms that are known to make human interaction smooth, efficient, and robust. These papers also accentuate the importance of the multidisciplinary approach to advance the understanding of the factors and the consequences of social interactions with artificial agents.

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