This work will build a foundation for distributed human-robot teams that are able to adapt to the individual team member’s cognitive and physical state to support effective collaboration.
The overall goal of our research is to investigate cognitive-physical adaptation during human-robot collaboration using brain and physiological signals in order to develop robot systems that can adapt to the humans who are working with them and to allow humans to better assess how the human-robot team is working as a unit in order to improve the overall outcomes. This project is a collaboration between Erin Solovey, Rodica Neamtu and Yanhua Li at WPI and Holly Yanco, Adam Norton, Yi-Ning Wu, and Pei-Chun Kao at UMass-Lowell. It is funded through the WPI-UML Seed Grants.
We are looking for motivated undergraduate and graduate research assistants for this project. We have both paid and volunteer positions, or students can enroll in an independent study for credit. Work will involve experiment design, running human subjects experiments, as well as data analysis and machine learning on multidimensional time series data.