United States

Gamified rehabilitation tackles the problem of keeping patients engaged in, and motivated to do physical rehabilitation to improve its efficacy. However, with respect to standard rehabilitation, patients are freer to move about and may compensate their motion difficulties with parasite movements, which would greatly reduce the efficacy of the rehabilitation. To identify and characterize compensatory motions, we collected and analyzed video data of people playing the“tangible Pacman” game (an upper-limb rehabilitation game in which a patient moves a semi-passive robot, the “Pacman”, on a map to collect 6 apples, while being chased by one or two autonomous robots, the “ghosts”). Participants include 10healthy elderly adults and 10 chronic stroke patients, who played multiple runs of the game, with different-sized maps and various game configurations. By analyzing the video recordings we successfully identified higher shoulder and torso lateral tilt compensation in stroke patients and developed a proof-of-concept compensatory motion detection system that relies on a wearable Inertial Measurement Unit and ROS to provide in-game, real-time visual feedback on compensation.

IEEE RO-MAN 2021

Detecting Compensatory Motions and Providing Informative Feedback During a Tangible Robot Assisted Game for Post-Stroke Rehabilitation

compensatory motions

therapy robotics

gamification

**Welcome to ACL-IJCNLP 2021!**

The great event is jointly organized by the Association for Computational Linguistics (ACL) and Asian Federation of Natural Language Processing (AFNLP). 

As in previous years, the program of the conference includes a poster session, tutorials, workshops and demonstrations in addition to the main conference.


We were able to keep the registration fees similar to those charged for the virtual ACL 2020. The one fee allows attendance at the main conference and any/all tutorials and workshops. These fees would be $125 Regular Early and $175 Regular Late; $50 Student Early and $75 Student Late. Early registration closes at midnight July 11, 2021 (Eastern Daylight Time).

**Reminder:** It is ACL’s policy that at least one author of each accepted paper (including ACL Finding papers) must register for the conference.

**Reminder2:** Underline site will open closer to the event. If you already registered you will receive access detail

Registration is now open

IJCNLP-AACL 2021

The great event is jointly organized by the Association for Computational Linguistics (ACL) and Asian Federation of Natural Language Processing (AFNLP).

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. 

This paper explores Augmented Reality (AR)-based implementations in robotics and categorizes them based on the type of the used device, with the main focus on the least explored category - mobile AR. To determine the user’s experience in robot programming, an AR application prototype is developed as a co-interface to a Teach Pendant. The obtained results detail the users potential benefits from such mobile-based AR solutions in light of the current technologies.

A Study of Cobot Practitioners Needs for Augmented Reality Interfaces in the Context of Current Technologies

In this work, the problem of cooperative human-robot manipulation of an object
with large inertia is addressed. A variable admittance control scheme is proposed,
where the damping is adjusted based on the power transmitted from the human to
the robot. The aim is to minimize the energy injected by the human while also
allowing her/him to have control over the task. Evaluation via human-in-the-loop
simulations and comparison with a generic variable damping state-of-the-art
method is performed.

ConCodeIt! A Comparison of Concurrency Interfaces in Block-Based Visual Robot Programming

In this work we focus on the collision avoidance problem with respect to a moving spherical object. We assume knowledge of a nominal controller that achieves tracking of a desired trajectory in the absence of obstacles, and we design an auxiliary control scheme to guarantee that the robot's end-effector will always operate in a safe distance from the moving obstacle's surface. The controller we develop does not take into account the actual robot dynamics, thus constituting a truly model-free approach.

Influences of Media Literacy and Experiences of Robots into Negative Attitudes toward Robots in Japan

As autonomous collaborative robots are more widely used in work environments alongside humans it is of great importance to facilitate the communication between people and robotic systems, in a way that promotes safety and productivity. To this end, we propose an Augmented Reality (AR) based system that allows workers in a human-robot collaborative environment to interact with a robot while also receiving information regarding the robot state and plans that relate to the human’s safety and trust.

Intuitive and Safe Interaction in Multi-User Human Robot Collaboration Environments through Augmented Reality Displays

The ability to accurately identify user intention is a pre-requisite for designing collaborative control schemes to provide appropriate navigational assistance to PAPAW users. In this paper, we investigated a personalized multi-step intention recognition pipeline that consists of probabilistic models for the purpose of clustering, classifying, and filtering user-pushrim interactions. The developed pipeline is computationally efficient and was successfully implemented and tested in real-time. This framework can provide a foundation for the future development of a context-aware controller for PAPAWs by improving their controllability and maneuverability.

Living-Lab and Experimental Workshops for Design of I-RobEka Assistive Shopping Robot: ELSI Aspects with MEESTAR {303}

In-The-Wild learning from demonstration for therapies for autisim spectrum disorder. We developed a learning from demonstration based model to identify therapists' verbal behavior, and learn a generative model to output corresponding verbal behaviour based on the child's audio spectrogram input.

Human-Robot Artistic Co-Creation: a Study in Improvised Robot Dance

Following the broad outline of Active Student Participation theory, we propose a pedagogical approach CAR targeted toward education of new researchers in the Autonomous Vehicles area. CAR combines Creativity theory, Applied demo-oriented learning, and Real world research context. Furthermore, we report on applying the
approach to stimulate learning and engagement in a master’s course, in which students freely created a demo with 10 small robots running ROS2 and Ubuntu on Raspberry Pis, in connection to an ongoing research project and a real current
problem (SafeSmart project and COVID-19). The results suggested the feasibility of the CAR approach for enabling learning, as well as mutual benefits for both the students and researchers involved. 


On the Causality between Affective Impact and Coordinated Human-Robot Reactions

We present an interactive robotic platform for teleoperated grasping as an educational tool. With this open- source robot application, we engage children and young adults with robotics. Our teleoperation method uses the Leap Motion optical gesture tracker to simultaneously control each of the four degrees-of- freedom (DOF) of a robotic hand and the six-DOF tool pose of a serial manipulator.

Gesture-Based Teleoperated Grasping for Educational Robotics

This study investigates if and how college students cheat while engaged in a collaborative sorting task with a robot. Our study finds that prior exposure to cheating on the task significantly increases the likelihood of cheating. Yet, the tendency to cheat is not impacted by the clarity of the task rules.

Impact of Human Gaze Behavior and Robot Appearance on Motion Uncertainty During Cooperative Hand Movement Tasks

The contributions, of our study are: a) the comparison of a human vs a robot-tutor in terms of the students’ level of understanding from the course (knowledge acquisition) and opinions about the use of robots in the educational field, b) an analysis of how the exposure of pre-service teachers in a robot-tutor and Computational thinking course affects their robot-related attitudes. c) We investigate the differences in attitudes and understanding from the course between students, after having ten weeks of basically Computational thinking lessons, who have one or two lectures with a robot-tutor.

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Detecting Compensatory Motions and Providing Informative Feedback During a Tangible Robot Assisted Game for Post-Stroke Rehabilitation

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