Focus

Our interdisciplinary workshop focuses on the human-centered design of adaptive robotic behavior from the lens of cognitive science. In this workshop, we invite researchers from different backgrounds, including engineering, human-machine interaction, and cognitive science, to discuss how cognitive modeling can be exploited to enhance adaptive human-robot interaction (HRI) frameworks. We aim to provide participants with diverse theoretical perspectives and potential research directions through interactive talks and panel discussions. 

Vision

Over the past two decades, there has been increased research interest in the Human-Robot Interaction (HRI) field: scientific papers published in HRI raised from about a hundred papers to almost ten thousand in 2020. However, this increased research interest does not comprehensively integrate the concepts of human-centered design (HCD) and thus does not utilize the full capabilities of HRI-based frameworks since less than 30% of the papers published in 2020 developed HRI frameworks focused on HCD concepts. HCD is important for better HRI as real-life applications often require humans and robots to cognitively align goals, have a shared task representation, and adapt to each other's behaviors. The low amount of work focusing on HCD design emphasizes the need to promote its inclusion in HRI research-an interdisciplinary research domain by nature.To address this issue, we propose an interdisciplinary workshop focusing on the aspects of HCD from the lens of cognitive science. In this workshop, we discuss how cognitive modeling can be applied for adaptive human-robot interaction from diverse theoretical perspectives and research domains by bringing speakers from engineering, human-machine interaction research, and cognitive science.

Mission

HRI can be implemented in different ways—either the human and the robot can collaborate in close contact (eg, coordinated lifting tasks), human-robot cooperation tasks (eg, human and the robot work alternately on different tasks within a process without direct interaction but share the same objective and workspace ), or the human and the robot can interact remotely (eg, teleoperation of a robotic system with the help of computer applications such as virtual reality), where the robot assists the human in tasks deemed too dangerous for direct human involvement or in tasks in hard-to-reach places or hostile environments. Both types of HRI require the human agent and the robotic system to adapt to each and the interaction environment.


Recent cognitive science and computational modeling works can inform adaptive HRI for robotics. For example, in an HRI task, given observed human behaviors, with considerations for the human's cognitive bounds and the task's environmental bounds, these computational models can help the robot infer the human's goals, intentions, or even the subjective utility functions. In addition, these models can also help the robot predict human decisions and behaviors given the inferred goals. Such considerations of the human agent will be more likely to reduce the inconvenience, threat, annoyance, or harm to human users and provide further accessibility, functionality, and protection instead. 


Given this background and motivation, our workshop focuses on three main questions: 

Topics

Topics of interest include but are not limited to:

Invited Speakers

Assistant Professor, Human And Robot Partners Lab, Robotics Institute, Carnegie Mellon University, USA

Senior Scientist, Italian Institute of Technology, Italy

Associate Professor, Electrical Engineering and Computer Sciences, UC Berkeley, USA

University of Birmingham, UK and Aalto University, Finland

Project Professor, University of Tokyo

Assistant professor, University of Michigan, USA