ON THE REDEFINITION OF FAN OUT METRIC FOR HUMAN ROBOT INTERACTIONS WITH HUMANOID SOCCER ROBOTS

2010 ◽  
Vol 07 (04) ◽  
pp. 565-586 ◽  
Author(s):  
MOHAN RAJESH ELARA ◽  
CARLOS ANTONIO ACOSTA CALDERON ◽  
CHANGJIU ZHOU ◽  
WIJERUPAGE SARDHA WIJESOMA
Keyword(s):  
Human Robot Interaction ◽  
False Alarms ◽  
Robot Interaction ◽  
Significant Drop ◽  
Task Failure ◽  
General Index ◽  
Single Operator ◽  
Tolerance Model ◽  
Soccer Robots

Fan out (FO) is adopted as a general index among human robot interaction researchers in predicting the maximum number of robots a single operator can handle simultaneously while maintaining performance at acceptable levels. Neglect tolerance model forms the basis for FO metric that assumes ideal conditions wherein the operator switches control between robots sequentially based on acceptable performance ignoring any false alarms due to erroneous interactions. In this article, we redefine the FO metric to account for any additional demands due to the occurrence of false alarms, as these additional demands could lead to task failure. Experiments with our virtual and real humanoid soccer robots across tele-operation and semi-autonomous modes of autonomy showed significant drop in FO predictions with inclusion of demands due to false alarms for all experimental cases.

Validating extended neglect tolerance model for human robot interactions in humanoid soccer robots

Robotica ◽  
2010 ◽  
Vol 29 (3) ◽  
pp. 421-432 ◽  
Author(s):  
R. E. Mohan ◽  
W. S. Wijesoma ◽  
C. A. A. Calderon ◽  
C. J. Zhou
Keyword(s):  
False Alarm ◽  
Task Complexity ◽  
Human Robot Interaction ◽  
False Alarms ◽  
Robot Interaction ◽  
Tolerance Model ◽  
Robot Performance ◽  
Robot Tasks ◽  
The Impact ◽  
Soccer Robots

SUMMARYEstimating robot performance in human robot teams is a vital problem in human robot interaction community. In a previous work, we presented extended neglect tolerance model for estimation of robot performance, where the human operator switches control between robots sequentially based on acceptable performance levels, taking into account any false alarms in human robot interactions. Task complexity is a key parameter that directly impacts the robot performance as well as the false alarms occurrences. In this paper, we validate the extended neglect tolerance model for two robot tasks of varying complexity levels. We also present the impact of task complexity on robot performance estimations and false alarms demands. Experiments were performed with real and virtual humanoid soccer robots across tele-operated and semi-autonomous modes of autonomy. Measured false alarm demand and robot performances were largely consistent with the extended neglect tolerance model predictions for both real and virtual robot experiments. Experiments also showed that the task complexity is directly proportional to false alarm demands and inversely proportional to robot performance.

Defining the Challenges Operators Face when Controlling Multiple Unmanned Vehicles

2005 ◽  
Vol 49 (3) ◽  
pp. 392-396
Author(s):  
Peter N. Squire ◽  
Raja Parasuraman
Keyword(s):  
Supervisory Control ◽  
Unmanned Vehicles ◽  
Human Robot Interaction ◽  
Human Operator ◽  
Simulation Environment ◽  
Robot Interaction ◽  
Human In The Loop ◽  
Control Interface ◽  
New Findings ◽  
Single Operator

To achieve effective human-robot interaction (HRI) it is important to determine what types of supervisory control interfaces lead to optimal human-robot teaming. Research in HRI has demonstrated that operators controlling fewer robots against opponents of equal strength face greater challenges when control is restricted to only automation. Using human-in-the-loop evaluations of delegation-type interfaces, the present study examined the challenges and outcomes of a single operator supervising (1) more or less robots than a simulated adversary, with either a (2) flexible or restricted control interface. Testing was conducted with 12 paid participants using the RoboFlag simulation environment. Results from this experiment support past findings of execution timing deficiencies related to automation brittleness, and present new findings that indicate that successful teaming between a single human operator and a robotic team is affected by the number of robots and the type of interface.

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

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

Biomimetic, sociable robots for human-robot interaction

2010 ◽  
Author(s):  
Eleanore Edson ◽  
Judith Lytle ◽  
Thomas McKenna
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction

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

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.

Shall I trust you? From child human-robot interaction to trusting relationships

2019 ◽  
Author(s):  
Cinzia Di Dio ◽  
Federico Manzi ◽  
Giulia Peretti ◽  
Angelo Cangelosi ◽  
Paul L. Harris ◽  
...  
Keyword(s):  
Behavioral Pattern ◽  
Human Robot Interaction ◽  
School Age Children ◽  
Social Relevance ◽  
Robot Interaction ◽  
Cognitive Correlates ◽  
The Social ◽  
The Relationship

Studying trust within human-robot interaction is of great importance given the social relevance of robotic agents in a variety of contexts. We investigated the acquisition, loss and restoration of trust when preschool and school-age children played with either a human or a humanoid robot in-vivo. The relationship between trust and the quality of attachment relationships, Theory of Mind, and executive function skills was also investigated. No differences were found in children’s trust in the play-partner as a function of agency (human or robot). Nevertheless, 3-years-olds showed a trend toward trusting the human more than the robot, while 7-years-olds displayed the reverse behavioral pattern, thus highlighting the developing interplay between affective and cognitive correlates of trust.

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