United States

With the increased use of social robots in critical
applications, like elder care and rehabilitation, it becomes necessary
to investigate the user’s trust in robots to prevent over- and
under-utilization of the robotic systems. While several studies
have shown how trust increases through personalised behaviour,
there is a lack of research concerned with the influence of
personalised physical appearance. This study explores the effect
of personalised physical appearance on trust in human-robotinteraction
(HRI).

IEEE RO-MAN 2021

The Difference between Trust Measurement and Behavior: Investigating the Effect of Personalizing a Robot&#39;s Appearance on Trust in HRI

human robot trust

human robot interaction

personalization

[![](https://assets.underline.io/markdown_image/1/image/f25361a85b7c83a7476c0b3c1c0bb1b2.png)](https://drive.google.com/file/d/18jcAcciCBQHj6R07Dbpm2HCOBEIwAOCU/view?usp=sharing)


Dear Colleagues and Friends,

The 33rd IEEE International Conference on Robot and Human Interactive Communication, IEEE RO-MAN 2024, was held at Pasadena Convention Center in Pasadena, USA.

The theme of the IEEE RO-MAN 2024 was **“Embracing Human-Centered HRI”**.

With the continuous technological effort of understanding human needs, creating human-desired robotic systems, and developing real human user experiences, we are marching together towards building a promising and excellent human quality of life, all for our wellness and our next generation.

The conference provided a forum for researchers and practitioners to discuss a variety of topics related to the broad theme of Robot and Human Interactive Communication involving theories, methodologies, technologies, empirical and experimental studies, and generated more insights for the future of Robot and Human Interactive Communication!

We hope you continue to enjoy the post-conference content on Underline!
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IEEE RO-MAN 2024

The 33rd IEEE International Conference on Robot and Human Interactive Communication was held in Pasadena, California, USA. The theme of the IEEE RO-MAN 2024 was “Embracing Human-Centered HRI”.

The Difference between Trust Measurement and Behavior: Investigating the Effect of Personalizing a Robot's Appearance on Trust in HRI

panel

RO-MAN 2021's theme is trustworthiness and cooperation. We chose this term well before the pandemic put the world on edge and added a new reason for us to question our own personal safety when in the company of others. But what about in the company of social robots? What would cause us to trust, or not trust, them? How do we as researchers create that feeling, that critical component of any relationship? With social robots, it is of course largely in our power to design the physical form, the control code and the interface software to maximize trustworthiness, facilitate cooperation and enhance the quality of human-robot interaction. This theme also touches upon people's expectations and perceptions of robots, as well as other social, cognitive and cultural factors that will influence human-robot interactions. We will have a special session/track on this topic, invite targeted submissions and include plenary speakers who are specialist in this area. We sincerely hope that this focus will help enlighten the design-thinking of all of us as we fabricate and program our own various systems.

To access RO-MAN Virtual 2021, [please register here.](https://ro-man2021.org/registration/)

RO-MAN 2021's theme is trustworthiness and cooperation. We chose this term well before the pandemic put the world on edge and added a new reason for us to question our own personal safety when in the company of others. But what about in the company of social robots? What would cause us to trust, or not trust, them? How do we as researchers create that feeling, that critical component of any relationship? With social robots, it is of course largely in our power to design the physical form, the control code and the interface software to maximize trustworthiness, facilitate cooperation and enhance the quality of human-robot interaction. 

Childhood ambulatory disorders affect physical, cognitive, and social development. We propose using a custom assistive robot for engaging children in early mobility interventions. Our first study showed that during driving interventions, children looked at the robot more while it was active, but other results were mixed. In our second study on ambulatory free play, children looked at and engaged with the robot more when it was active. This research is a first step in developing robots for early mobility interventions.

Design of an Assistive Robot for Infant Mobility Interventions

A socially assistive robot can support children in developmental and well-being aspects. The robot's visual aesthetics influences users' initial judgments and is essential for creating first impressions, trust, and desirability. Our work proposes and demonstrates a methodology for evaluating children's perception of visual qualities in SARs, aiming to pave the way for new design tools to support robotic designers and developers.

Overhead Work Assist with Passive Gravity Compensation Mechanism and Horizontal Link Mechanism for Agriculture

Abstract— Today’s world is undeniably technology-driven and children are the ones who adopt technology with ease. This fact could be leveraged to design assistive technologies for children using social robots as they are observed to be efficient pedagogical agents. Robotic technology is evolving rapidly and robots are designed to play social roles in education, health care and home assistance. However, there has been limited research focusing on the use of robotic technologies for designing interactions with children in the global south, owing to which the response behaviour towards robot-assisted interventions is unknown. To address this gap, we conducted a study to understand the response behaviour of Indian children
of the age 3-6 years towards robot-assisted interventions during directive tasks. Our analysis shows that the children could follow to robot’s instructions during the tasks and complete the tasks successfully. The exploratory outcomes also highlight
the acceptance and benefits of using robotic assistants as a facilitator in education, cognitive therapies and healthcare.

Understanding the Perception of Incremental Robot Response in Human-Robot Interaction

This paper proposes a novel dynamic method based on Behavior Trees that integrates planning and allocation of tasks in mixed human robot teams, suitable for manufacturing environments. The Behavior Tree formulation allows encoding a single job as a compound of different tasks with temporal constraints. The role allocation problem is solved with multiple simplified online optimization sub-problems. These sub-problems are defined as Mixed-Integer Linear Programs, that, according to the worker-actions related costs and the workers' availability, allocate the yet-to-execute tasks among the available workers.

Older Adults’ Opinion on Social Robot as Companion

This work presents the improvements of Hydracer, a robot manipulator driven by electro-hydrostatic actuators, to achieve human-robot interaction. To solve the problems of Hydracer and to achieve flexible force control, we worked on the system improvements: reduction of internal leakage by considering oil property, enhancement of reliability of ceramics components, and the parameter identification to improve its controllability. Flexible force control of Hydracer by zero-torque control with gravity compensation was realized.


TIRL: Enriching Actor-Critic RL with non-expert human teachers\\ and a Trust Model

In this work, we designed a teachable robot that encourages a pair of students to discuss their thoughts and teaching decisions during the tutoring session. The robot adapts to the students' talking activity. The results of our user study (n = 68) showed that the adaptive robot was successful in creating more dialogue between dyad members and in increasing task engagement. Over time, the adaptive robot was also able to encourage both members to contribute more equally to the conversation.

A Model for the Representation of the Extraversion-Introversion Personality Traits in the Communication Style of a Social Robot

We implemented a dedicated human-aware navigation system that adapts the configuration of the navigation parameters based on two human-like personalities, extrovert and introvert, and we compared them with a no social behavior. We evaluated the system in a dynamic scenario in which each participant needed to pass by a robot moving in the opposite direction, showing a different personality each time. The results show that 19 out of 20 subjects involved in the study perceived a difference among the personalities exhibited by the robot, both in terms of proxemics and velocity. Furthermore, the results highlight a general preference of a complementary robot’s personality, helping to suggest some guidelines for future works in the human-aware navigation field.

Modeling Human-Like Robot Personalities As a Key to Foster Socially Aware Navigation

While we've made signfiicant progress in models of gesture production, there are still significant behavioral effects on humans that observe these gestures. Namely, we find that f-formation, perspective taking, feasability in the configuration space, and exophora play outsized roles in present day gesture generation models for robots. We suggest a way forward but leave it to future work to explore.

Evaluation of Immersive Teleoperation Systems using Standardized Tasks and Measurements

The identification of social groups has been a challenge for robotics as it encompasses a number of disciplines. We propose a hierarchical clustering method for grouping individuals into free standing conversational groups, utilising their position and orientation. The proposed method is evaluated on the SALSA dataset with achieved F1 score of 0.94. The algorithm is also evaluated for scalability and implemented on a mobile robot attempting to detect social groups and engage in interaction.

Designing Robotic Cabinets That Assist Users' Tyding Behaviors

We propose a CNN-LSTM network to estimate human engagement intention.
We build a multi-branch, inputs-adjustable architecture to provide the flexibility of accommodating different types of input features (image features and semantic social cues).
We propose a feature transition method to handle multiparty HRI.

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