Lilia Moshkina

Human perspective on affective robotic behavior: a longitudinal study

Humans are inherently social creatures, and affect plays no small role in their social nature. We use our emotional expressions to communicate our internal state, our moods assist or hinder our interactions on a daily basis, we constantly form lasting attitudes towards others, and our personalities make us uniquely predisposed to perform certain tasks. In this paper, we present a framework under development that combines these four areas of affect to influence robotic behavior, and describe initial results of a longitudinal human-robot interaction study. The study was designed to inform the development of the framework in order to increase ease and pleasantness of human-robot interaction.

On TAMEing robots

This paper presents a framework for affective robotic behavior (TAME) and describes an exploratory experimental study to identify relevant affective phenomena to include into the framework in order to increase ease and pleasantness of human-robot interaction.

TAME: Time-Varying Affective Response for Humanoid Robots

This paper describes the design of a complex time-varying affective software architecture. It is an expansion of the TAME architecture (Traits, Attitudes, Moods, and Emotions) as applied to humanoid robotics. In particular it is intended to promote effective human-robot interaction by conveying the robot’s affective state to the user in an easy-to-interpret manner.

Social engagement in public places: a tale of one robot

In this paper, we describe a large-scale (over 4000 participants) observational field study at a public venue, designed to explore how social a robot needs to be for people to engage with it. In this study we examined a prediction of Computers Are Social Actors (CASA) framework: the more machines present human-like characteristics in a consistent manner, the more likely they are to invoke a social response. Our humanoid robot’s behavior varied in the amount of social cues, from no active social cues to increasing levels of social cues during story-telling to human-like game-playing interaction. We found several strong aspects of support for CASA: the robot that provides even minimal social cues (speech) is more engaging than a robot that does nothing, and the more human-like the robot behaved during story-telling, the more social engagement was observed. However, contrary to the prediction, the robot’s game-playing did not elicit more engagement than other, less social behaviors.

TAME: Time-varying Affective Response for Humanoid Robots

This paper describes the design of a complex time-varying affective architecture. It is an expansion of the TAME architecture (traits, attitudes, moods, and emotions) as applied to humanoid robotics. It particular it is intended to promote effective human-robot interaction by conveying the robot’s affective state to the user in an easy-to-interpret manner.

Mood as an affective component for robotic behavior with continuous adaptation via Learning Momentum

The design and implementation of mood as an affective component for robotic behavior is described in the context of the TAME framework - a comprehensive, time-varying affective model for robotic behavior that encompasses personality traits, attitudes, moods, and emotions. Furthermore, a method for continuously adapting TAMEs Mood component (and thereby the overall affective system) to individual preference is explored by applying Learning Momentum, which is a parametric adjustment learning algorithm that has been successfully applied in the past to improve navigation performance in real-time, reactive robotic systems.

Lethality and autonomous systems: The roboticist demographic

This paper reports the methods and results of an on-line survey addressing the issues surrounding lethality and autonomous systems that was conducted as part of a research project for the U.S. Army Research Office. The robotics researcher demographic, one of several targeted in this survey that includes policymakers, the military, and the general public, provides the data for this report. The design and administration of this survey and an analysis and discussion of the survey results are provided.

Usability evaluation of an automated mission repair mechanism for mobile robot mission specification

This paper describes a usability study designed to assess ease of use, user satisfaction, and performance of a mobile robot mission specification system. The software under consideration, MissionLab, allows users to specify a robot mission as well as compile it, execute it, and control the robot in real-time. In this work, a new automated mission repair mechanism that aids users in correcting faulty missions was added to the system. This mechanism was compared to an older version in order to better inform the development process, and set a direction for future improvements in usability.

Reusable semantic differential scales for measuring social response to robots

This paper presents eight novel reusable semantic differential scales measuring a variety of concepts relevant to the field of social HRI: Understandability, Persuasiveness, Naturalness, Appropriateness, Welcome, Appeal, Unobtrusiveness and Ease. These scales were successfully used in two HRI experiments, and were found to have acceptable (> 0.7) or higher levels of internal reliability. These scales are reusable and were designed to simplify comparison between HRI studies, especially in the area of social robotics, where measuring the quality of interaction and social response to robots is of paramount importance.