Team Science of Convergence
As we work together, our research team engages in “team science,” reflecting on and studying team effectiveness and efficiency.
In the following Team-Science videos, Dr. Keri Stephens shares findings we have thus far for improving interdisciplinary teamwork.
Tips for Running Effective Meetings
Tips for Naming Files and Storage
How to Submit Your Work
How to Handle a “Revise and Resubmit”
Convergent Research Informatics and Data Curation
One of the key ways of achieving convergence is by creating a repository of data and data models that involve gathering causal information regarding factors such as robot geolocalized trajectories, camera recordings from the point of view of robots, interviews from IRB subjects, human factor sensor collection during robot encounters, and more. We use graph database networks to create causal relationships and we connect them to chatbots in order to query the data seamlessly. Here we show a recording of the process of interacting with this data repository for robot encounters.
Community Reactions: Human-Robot Encounters
We study people’s reactions to encounters with autonomous mobile robots in indoor settings, illustrated in this figure. We envision a future where these types of spontaneous encounters with mobile robots will be commonplace. Therefore we find it critically important to investigate people’s perceptions during these encounters. We employ methods from social science and biosignal analysis to learn about these situations.
Community Reactions: Community-Robot Encounters
At the convergence of HRI, Social Sciences, and Robot Autonomy, we study incidental encounters in outdoor environments with groups of people. Such deployments allow us to ask questions about how to improve interactions, how should robots ask for help, what behaviors are useful, etc.
Robot Services: People Preferences during Campus Tours
Our team is working with UT Campus Tours and UT Landmarks Tours to deliver tours to diverse communities using robots. Campus Tours gives daily tours to students, visitors, etc, and has been quite open to complementing tours with roots. We are actively working Landmark Tours which delivers tours for art enthusiasts of the art around campus. These tours give us an opportunity to learn people preferences of robots walking behavior while moving freely during the tours.
Robot Services: Locating Missing Objects
To investigate the effect of robots on public enviroments our team has created various behaviors using a common infrastruture consisting of several Boston Dynamics Spot Robots. In the video below a Spot robot explores a building in search of missing items that someone in the community might want to recover. This work has been recently submitted for publication. A copy of the manuscript can be found here: Ryan Gupta, Luis Sentis et al., “Fast LiDAR Informed Visual Search in Unseen Indoor Environments”, 2024″.
Community Reactions: Robots in Diverse Communities
A major part of our study consists of studying the response of people in diverse communities to robots performing tasks or interacting with them in their daily lives. The video below shows a longitudinal ethnographic study of the AI quadrupedal robot interacting with regular YMCA customers on their daily routines during a period of one week.