United States

In this work we investigated the effect of eight different robot characteristics on an interaction with a child with Type 1 Diabetes, aiming to improve their self-management. Results indicated that movements of the robot were considered entertaining, emotional expressions of the robot contributed to bonding and eye contact was not appreciated by all children. The results can be used to improve interactions between children and robots.

IEEE RO-MAN 2021

Investigating Experiences with a Robot Teaching Children Self-Management: A Field Trial

robot characteristics

self-management

child-robot interaction

**About**
 The PErvasive Technologies Related to Assistive Environments (PETRA) conference is a highly interdisciplinary conference that focuses on computational and engineering approaches to improve the quality of life and enhance human performance in a wide range of settings, in the workplace, at home, in public spaces, urban environments, and other. Outcomes of this conference have a broad impact in application areas that include, manufacturing, transportation, healthcare, energy systems, security and safety, robotics, biomedicine, environment and conservation, and many others. PETRA brings together very different types of technologies to also address important social and healthcare issues for sensitive populations, such as the elderly, persons suffering from chronic conditions such as Alzheimer’s, Parkinson’s, Cerebral Palsy, and other disabilities or traumas.

 PETRA (which means “stone” in Greek) addresses important human living needs. From a technological perspective, PETRA motivates and inspires new scientific thrusts, innovations and discoveries to improve living environments, a particularly important issue, in an increasingly crowded and complex world where the need for inclusiveness and connectivity with the rest of the world is key. For the elderly in particular, PETRA addresses the fact that, as people grow older; they will increasingly rely on technology to be able to prolong staying in their homes and enjoy an independent life.

 The PETRA 2021 proceedings will be published in the ACM Digital Library as part of the ACM ICPS program. The ISBN number assigned to PETRA '21 is 978-1-4503-8792-7

PETRA 2021

The PErvasive Technologies Related to Assistive Environments (PETRA) conference is a highly interdisciplinary conference that focuses on computational and engineering approaches to improve the quality of life and enhance human performance in a wide range of settings, in the workplace, at home, in public spaces, urban environments, and other. Outcomes of this conference have a broad impact in application areas that include, manufacturing, transportation, healthcare, energy systems, security and safety, robotics, biomedicine, environment and conservation, and many others. PETRA brings together very different types of technologies to also address important social and healthcare issues for sensitive populations, such as the elderly, persons suffering from chronic conditions such as Alzheimer’s, Parkinson’s, Cerebral Palsy, and other disabilities or traumas.

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. 

Social behaviors and displays of affect are critical for successful child-robot interactions. In this paper we discuss a new approach to creating generalized displays of affect for an appendage from a collection of cartoons. We then discuss the design of a continuum robotic appendage that can display the emotional configurations from our data and evaluation study.

Design and Evaluation of an Affective, Continuum Robotic Appendage for Child-Robot Interaction

We present a speaker-aware robotic system which recognizes users by voice in realistic, noisy conditions, highlighting the potential of speaker identification to enrich industrial and social HRI. We approach this as a CNN-based audio classification task, with the particular aim of producing fast, reliable, and explainable predictions. Our method is evaluated on a challenging 6-speaker dataset collected "in the wild" and showcased in a manufacturing scenario, where a collaborative robot personalizes its responses and prevents non-authorized users from executing commands.

Why Talk to People When You Can Talk to Robots? Far-Field Speaker Identification in the Wild

Interaction forces between humans and robots must be within safe limits to avoid threats to human life and unacceptable damage to equipment. This limits robot speed and ultimately stops the robot safely. Interaction is normally considered as a single point of contact. In this paper, end-effector interaction and body interaction are distinguished and demonstrated on a real industrial manipulator. This approach allows monitoring two points of contact, for better interaction measurement and for avoiding unnecessary stops.

Estimating Robot Body Torque for Two-Handed Cooperative Physical Human-Robot Interaction

This study introduces the control architecture of a platform aimed at promoting good mental health for workers interacting with cobots through automatic adaption capabilities. Starting from the identification of the parameters that could influence the collaboration experience, the envisioned human-driven control structure is presented together with a detailed description of the components required to implement such an automated system.

Relevant Perception Modalities for Flexible Human-Robot Teams

We describe a method of teaching a robot its empathic behavioural response from its interaction with people. Firsst, we bootstrap the training through a pre-learning mechanism in which training is conducted by users who know the robotic system. Then we developed an online learning scheme for naive users to personalize their robot further. Our interface enables natural human-robot interaction via the suite of sensors that allows the users to provide evaluative feedback during the interaction with the robot.

Robot player adaptation to human opponents in physical, competitive robogames

Socially assistive robots (SARs) are currently 
being developed to assist in the delivery of Applied Behavior 
Analysis (ABA) therapies to individuals diagnosed with Autism 
Spectrum Disorder (ASD). Although SARs have demonstrated 
positive outcomes, minimal research has focused on
investigating needs of the therapists that deliver treatments. 
Therapist perspectives are important as they will likely be the 
primary end-users of SARs. In this study, we investigated the 
perceptions and design requirements of ABA therapists towards 
SARs and the interfaces used to operate them. Therapists were 
interviewed after they independently designed, developed, and 
implemented their own robot-mediated interventions. Overall, 
therapists’ general perceptions towards integrating a SAR 
within their existing workflow was positive and they expected 
that children would benefit from ABA therapies delivered by a 
SAR. The therapists also provided insights on design 
requirements for utilizing SARs and their interfaces as well as 
potential clinical and future use cases for this technology

Designing Proactive Objects with Artificial Eyes Based on Perceptual Crossing Paradigm

This work presents insights on deploying an affordable Socially Assistive Robots (SARs) at actual elder care facilites for symptoms and exposure screening of COVID-19. The study considered not only the older adults, but also caregivers and clinicians, and their preferences towards the robot and the interaction. A survey evaluated participants' preference on the screening agent, positive and negative aspecs of the interaction and their reactions by an observer.

An Experimental Study of the Accuracy vs Inference Speed of RGB-D Object Recognition in Mobile Robotics

To resolve the lack of prosthesis supply and reduce cost issues, this paper provides an overview of a self-trainable user-customized system architecture for a 3D printed prosthetic hand to minimize the challenge of accessing and maintaining these supporting devices.

Would you Take Advice from a Robot? Developing a Framework for Inferring Human-Robot Trust in Time-Sensitive Scenarios

In this paper we explore the utility, usability, and accessibility of a tele-operated Stretch robot in a real kitchen environment. Our focus is on accessible teleoperation -- making it possible for diverse users to control the Stretch to do useful things, both through interface design principles, customization, and by moving towards mixed autonomy

Natural Gradient Shared Control

We present a AR-based robot visualization system which allows people to visualize robots and their intent, allowing users to see robots through walls and gain greater awareness of robots in shared human-robot workspaces.

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Investigating Experiences with a Robot Teaching Children Self-Management: A Field Trial

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