United States

Novel framework to create legible movements in multi-party interactions

IEEE RO-MAN 2021

Human robot skill transfer systems for mobile robot based on multi sensor fusion

human-robot interaction; robotic communication; legibility

[![](https://assets.underline.io/uploads/markdown_image/1/image/21d13e03491d7e9acf6b8c46c7979c25.png)](https://docs.google.com/spreadsheets/d/1SCDDfkQk7es4J6RULKHVx1RzbB0Mutla--Sle5SVfb0/edit?usp=sharing)

**RoboCup 2021 will be Worldwide!**

We are excited to announce that RoboCup 2021 is a fully remote event with RoboCup competitions and activities taking place all over the world. Everyone is invited to participate in, or observe, the [competition leagues](https://2021.robocup.org/leagues) and the [symposium](https://2021.robocup.org/symposium)!

**RoboCup Symposium**

The 24th RoboCup International Symposium will be held in conjunction with RoboCup 2021 in a purely online setting. Scientific papers will be presented reporting innovative, original research with relevance to robotics and artificial intelligence. Within the described scope of topics we also encouraged submissions of high-quality overview articles, papers describing real-world research, and papers reporting theoretical results. In addition to the main track with regular research papers, there will be a special track focused on systems, data, and benchmarks featuring papers describing novel, open-source hardware and software systems, as well as datasets and benchmarks relevant to the community. In addition to research paper presentations, the RoboCup Symposium 2021 includes keynote talks by Dieter Fox, Jean-Paul Laumond, and Stefanie Tellex, and several interactive sessions.

**RoboCup Introduction Video**
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Registration is required for entrance into RoboCup 2021. <br><br>
**Fees:** 
* Major Faculty or Symposium Faculty - US$50
* Major Student, Junior Mentor, Junior Student, or Symposium Student - US$20 

***Members of qualified teams:** Please contact your league for your registration password and proceed to register with your team. *<br>
***All non-team members:** Please register as "Symposium Only".*

You need to be registered to explore this event!

RoboCup 2021

The 24th RoboCup International Symposium will be held in conjunction with RoboCup 2021 in a purely online setting. Scientific papers will be presented reporting innovative, original research with relevance to robotics and artificial intelligence. Within the described scope of topics we also encouraged submissions of high-quality overview articles, papers describing real-world research, and papers reporting theoretical results. In addition to the main track with regular research papers, there will be a special track focused on systems, data, and benchmarks featuring papers describing novel, open-source hardware and software systems, as well as datasets and benchmarks relevant to the community. In addition to research paper presentations, the RoboCup Symposium 2021 includes keynote talks by Dieter Fox, Jean-Paul Laumond, and Stefanie Tellex, and several interactive sessions.

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. 

In this paper, we conduct a longitudinal user study to investigate the differences in interactions participants had with an experienced human coach (HC) delivering mindfulness training with the interactions another group of participants had with a Robot Coach (RC) teleoperated by the HC. We aim to gain an understanding of the
evolving user perceptions towards the coaches (HC and RC), which can, in turn, help us design effective strategies to develop autonomous robot coaches that can deliver mental wellbeing interventions.

Towards a context-based Bayesian recognition of transitions in locomotion activities

This trial tested a social robot to help deliver a low-intensity problem-solving session for students around study-related issues. In the trial, 72 students reported good ratings for emotional reaction to the robot, perceived utility, intention to use the robot again, confidence to use the robot, and perceived helpfulness from the robot. One week later, most students reported that the robot session helped them to fix their chosen issue, and that they used at least one idea from the session.

A Robot-Delivered Program for Low-Intensity Problem-Solving Therapy for Students in Higher Education

In this paper, we report that how much the presence of a robot increases the rate of valid responses in a questionnaire survey. We conducted a field experiment in which two conditions were compared: one with a robot and one without a robot. 
The result shows the potential that a robot can attract people’s attention and increase the response rates. However, the effect was small and short-term.


Hierarchical Motion Planning Framework for Manipulators in Human-Centered Environments

We propose emotional music prosody can play a key role in improving the interaction between humans and groups of robots by modifying the level of entitativity. We were able to show with significant results that the use of musical prosody improved likeability and trust over soundless gestures for groups of robots. We also demonstrate that is able to alter the level of entitativity perceived by external observers. Finally, our results indicate a complex relationship between entitativity and common HRI metrics.

Emotion Musical Prosody for Robotic Groups and Entitativity

This project aims at designing a Series Elastic Actuator for an active upper limb exoskeleton to be used directly in the workplace. The design we studied is based on linear springs and developed a theoretical method that allowed us to select the springs based on the application requirements. The higher purpose is to prevent work-related musculoskeletal diseases by assisting workers in their daily job, reducing muscular fatigue in the upper limb when performing tasks involving arm elevation and weight-lifting.

Tell me more! A Robot’s Struggle to Achieve Artificial Awareness

We propose a systematic approach to regularize RNN-based sequential prediction by incorporating domain knowledge with logic constraints. We apply two methods - adding a layer after the hidden unit and combining class probabilities to improve the standard sequential prediction model. We confirm the effectiveness of our methods on surgical activity detection.

Physiological Data-Based Evaluation of a Social Robot Navigation System

Real world environments require us to consider the possibility of deception when evaluating human intent. We propose an end-to-end system which uses changes in facial expressions to predict deceptive intent and show that it matches human performance on the task.



Social norms and cooperation in a collective-risk social dilemma:comparing reinforcement learning and norm-based approaches

While VR is a useful evaluation tool for HRI, it has been concerned that the human behavior may differ between VR and real environments due to the differences in cognitive characteristics. We investigated the differences of human behavior in real and VR condition for searching of hidden objects and precious manipulation. We found that precious manipulation task requires longer time in VR condition, and subjects tend to change their head posture during object search and manipulation. We also discuss the feasibility to use the findings in robot competitions.

A Two-Layered Approach to Adaptive Dialogues for Robotic Assistance

We present a new approach to human-aware robot navigation, which extends our previous proximity-based navigation framework by introducing visibility and predictability as new parameters. We derived these parameters from a user study and incorporated them into a cost function, which models the user’s discomfort with respect to a relative robot position based on proximity, visibility, predictability, and work efficiency.

An Adversarial Attacks Resistance-based Approach to EmotionRecognition from Images using Facial Landmarks

Faces are important in any interaction. It is the focal point of the interaction. In the experiment with interactive robotic art installation, we found no significant differences between distance mode, animacy, likeability, and safety before and after the interaction across the three conditions. The findings necessitate further consideration of the currently widely held belief on the utility of robot faces for successful HRI, particularly when the robot can generate attention-driven motion primitives.

Human robot skill transfer systems for mobile robot based on multi sensor fusion

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Towards a context-based Bayesian recognition of transitions in locomotion activities

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