"My work focused on developing a method for moderating users’ trust in robots by quantifying a robot’s confidence in its ability to accomplish a specified task. This is strikingly similar to existing research in reachability, which assesses whether a robot can compute a policy (or “plan of action”) to move from a start state to some goal state. The key difference is that our work targets the setting in which the environment is dynamic: there exists some change in the robot’s environment that may limit its ability to perform a task, thus requiring it to assess whether a task is safely accomplishable or not. This is critical especially when humans are involved, such as predicting driveability for self-driving cars. I was able to apply critical thinking skills and research experience garnered through UROPs at MIT. I also had a chance to cultivate enhanced teamwork skills and continue practicing collaborative research."
Kaili's Story
Gabrielle Kaili Liu '23 worked in a research internship at the Collaborative Learning and Adaptive Robots (CLeAR) Lab in Singapore and the team she worked on focused on moderating trust in collaborative robotics.
"Being in Singapore for the summer, I’ve gained a broader perspective by partaking in a leading research institution’s pursuit of innovative technologies and research through a global “looking-glass,” and the sense that I am truly part of an international effort to make the world a better place is tremendously inspiring. The mentorship and guidance I have received while at NUS is profound, and it has been great to be part of Singapore’s community."Gabrielle Kaili Liu '23
Major & Class Year
Mathematics with Computer Science '23
Location
Singapore
MISTI Program
Internship
MISTI Host
National University of Singapore