United States

In this work, we present a framework for human-robot collaboration allowing the human operator to alter the robot plan execution online. To achieve this goal, we introduce branched AND/OR graphs, an extension to AND/OR graphs, to manage flexible and adaptable human-robot collaboration. In our study, the operator can alter the plan execution using two implementations of Branched AND/OR graphs for learning by demonstration, using kinesthetic teaching, and task repetition. Finally, we demonstrated the effectiveness of our framework in a defect spotting scenario where the operator supervises robot operations and modifies online the plan when necessary.

IEEE RO-MAN 2021

Branched AND/OR Graphs: Toward Flexible and Adaptable Human-Robot Collaboration

branched and/or graphs: toward flexible and adaptablehuman-robot collaboration

**31st IEEE International Conference on Robot & Human Interactive Communication**
 This conference is a leading forum where state-of-the-art innovative results, the latest developments as well as future perspectives relating to robot and human interactive communication are presented and discussed.
 
 The conference covers a wide range of topics related to Robot and Human Interactive Communication, involving theories, methodologies, technologies, empirical and experimental studies. Papers related to the study of robotic technology, psychology, cognitive science, artificial intelligence, human factors, ethics and policies, interaction-based robot design and other topics related to human-robot interaction are welcome.
 
 **CONFERENCE THEME:**
 Social, asocial, and antisocial robots
 
 Robots are starting to populate our lives: at work, in our homes, hotels, shops. However, not everybody is comfortable with robots finding a place in society. For example, people may be afraid that robots will replace humans in their jobs. This belief is exacerbated by the media that, on one side, raise expectations of robots’ capabilities, while amplifying fears and worries on the other side.
 
 In the next years, due to the increasing request for interaction with people in social environments, academic research and market analyses predict that robots will become more and more “social”. But, at the same time, robots may incur the risk of being perceived as “asocial” as their pervasiveness in everyday environments may become an obstacle to social interaction between humans. Or they may even be rejected as “antisocial” if researchers do not take care to develop robots that behave according to the customs and habits of the communities where they are expected to operate.
 
 To prevent this from happening, robotic researchers can no longer take the luxury of being mere technicians. They must be capable of addressing all the challenges raised by future robot-populated communities in a multidisciplinary way. They need to share their knowledge with the public to make people aware of what robots really are, what expectations we can have from them, the risks we may incur, and the possible mitigation plans.
 
 While being open to any kind of contribution related to Human-Robot Interactive Communication, the RO-MAN 2022 conference will emphasize these aspects of robotic research. How can we create robots capable of being welcomed as our assistants and companions in society while, at the same time, not being perceived as “asocial” or “antisocial?” How can we create robots perceived as facilitators of the natural development of human beings and communities, rather than obstacles?
 
 Contributions from different disciplines, not exclusively related to technological development, will be welcomed as crucial to pave the way to global acceptance of future robots with an informed attitude.
 
 [![](https://assets.underline.io/uploads/markdown_image/1/image/af259abe105b3791c498ae1552d75710.png)](https://drive.google.com/file/d/18w73BZPB_JVOgcrcdZDqYpEupwVt4CnU/view?usp=sharing)

A registration is required to access this event page. If you have not already done so, please use the below link to register for the event. 

[Register Here](http://www.smile.unina.it/ro-man2022/welcome-to-ieee-ro-man-2022/)

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IEEE RO-MAN 2022

31st IEEE International Conference on Robot & Human Interactive Communication
This conference is a leading forum where state-of-the-art innovative results, the latest developments as well as future perspectives relating to robot and human interactive communication are presented and discussed.

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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

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.

Interactive Robotic Systems as Boundary-Crossing Robots – the User’s View

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.

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