United States

We present a novel Tic-tac-toe scenario with Reinforcement Learning – based algorithm, i.e. SwarmPlay, where each playing component is presented by an individual drone that has its own mobility and swarm intelligence to win against a human player. The SwarmPlay technology provides a high level of engagement and immersion with the user as it proposes a multi-agent swarm instead of a single interactive robot.

IEEE RO-MAN 2021

Investigating Reward/Punishment Strategies in the Persuasiveness of Social Robots

swarm

human-swarm interaction

computer vision

reinforcement learning

AAMAS is the leading scientific conference for research in autonomous agents and multi-agent systems. The AAMAS conference series was initiated in 2002 as the merging of three respected scientific meetings: the International Conference on Multi-Agent Systems (ICMAS), the International Workshop on Agent Theories, Architectures, and Languages (ATAL), and the International Conference on Autonomous Agents (AA). The aim of the joint conference is to provide a single, high-profile, internationally-respected archival forum for scientific research in the theory and practice of autonomous agents and multi-agent systems.

Browse keynotes, discussions, panels and over 300 presentations.


AAMAS 2020

AAMAS is the leading scientific conference for research in autonomous agents and multi-agent systems. The AAMAS conference series was initiated in 2002 as the merging of three respected scientific meetings: the International Conference on Multi-Agent Systems (ICMAS), the International Workshop on Agent Theories, Architectures, and Languages (ATAL), and the International Conference on Autonomous Agents (AA). 

technical paper

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 work, we have developed an autonomous robotic assistant for the task of blood suction in robotic surgery. This system was demonstrated to improve surgical performance and reduced cognitive demands compared to the manual teleoperation of the suction. Moreover, the system was tested in a user study. In this, the autonomy collaborated with the user to complete a surgical task. This study allowed us to identify key collaboration aspects required for an effective autonomous blood suction system.

Multi-camera Torso Pose Estimation using Graph Neural Networks

Storytelling with an embodied agent through empathetic interaction by leveraging creative contents with affective robotic agency

Design of Dynamic Tangible Workspaces for Games:Application on Robot-Assisted Upper Limb Rehabilitation

We propose the use of interactive vignettes as an alternative to traditional text- and video-based vignettes for conducting large-scale Human-Robot Interaction (HRI) studies. Interactive vignettes maintain the advantages of traditional vignettes while offering additional affordances for participant interaction and data collection through interactive elements. We discuss the core affordances of interactive vignettes, including explorability, responsiveness, and non-linearity, and look into how these affordances can enable HRI research with more complex scenarios.

Socially Compliant Human-Robot Interaction for Autonomous Scanning Tasks in Supermarket Environments

This paper provides insights into trust repair strategies in HRI by examining trustworthiness and its attributes of ability, benevolence, and integrity. Furthermore, we also consider how anthropomorphism can act as a moderator between trust repairs and their effects on trustworthiness.

Robot Mirroring: Promoting Empathy with an Artificial Agent by Reflecting the User's Physiological Affective States

In this work we present a kinematics model for the humanoid robot Pepper. The model is based on analytical solutions of the inverse kinematics, which provide very accurate and fast results. It is envisioned to be used in a human-humanoid pose matching imitation system as it allows for translation of human joint positions to robot joint angles while maintaining the angle configuration of the body pose.

Analytical Solution of Pepper’s Inverse Kinematics for a Pose Matching Imitation System

We investigate two extensions to our grounded word-learning system to increase transparency. The first extension uses deictic gestures (i.e., pointing) to interact with users. The second extension visualizes the current state of the lexicon on the robot's tablet. We performed a user study (n=32) to evaluate the system. In a quantitative analysis, we did not see a performance increase for the extensions, but found other benefits. In a qualitative analysis, we identified challenges for word-learning systems.

Monocular 3D object detection for an indoor robot environment

Skill imitation has been an important ability in
human-robot collaboration since it allows expeditious robot
teaching of new tasks. To mimic the human
pose, inverse kinematic solvers have been used to endow kinematic
structures with human-like motion. Nevertheless, these
solutions tend to be formulated for a specific robot or task. To
address this generalization issue, this work presents the ICONS
framework for imitation constraints, which proposes a general
formulation for pose imitation, paired with a computationally
efficient solver.

ICONS: Imitation CONStraints for Robot Collaboration

An appropriate user interface to collect human demonstration data for deformable object manipulation has been mostly overlooked in the literature. We present an inter-action design for demonstrating cloth folding to robots. Users choose pick and place points on the cloth and can preview a visualization of a simulated cloth before real-robot execution. Two interfaces are proposed: A 2D display-and-mouse based GUI, and a 3D Augmented Reality interface where the chosen points are placed by hand gestures.

How context shapes the appropriateness of a robot’s voice

As the demands on health and social care increase so too does the pressure on the carers we rely on to provide that care. However, as demand increase we risk placing too much burden on the care sector. This talk discusses the deployment of a humanoid robot to a day center catering for guests suffering with dementia with the aim of supporting the center staff to run group activities.

Exploring the Applicability of the Socially Assistive Robot Stevie in a Day Center for People with Dementia

Wearable robots are traditionally used as tools for assisting muscular strength and decrease the physical loads of users. In this study, we are interested in the social aspect of wearable robots and investigate the effects of wearing them toward perceived impressions of them. For this purpose, we newly developed a wearable robot, Fylgear, with minimum capabilities to interact with a user. We experimentally investigated whether wearing a robot changes people’s perception of the robot by using different questionnaire items: a set of positive impressions and kawaii feeling. The experiment results showed that participants who wear the robot positively evaluated the robot in the context of likeability and total impression, but there are no significant differences in perceived kawaii feelings.

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Multi-camera Torso Pose Estimation using Graph Neural Networks

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