Great work from our undergraduate researchers this semester! Our teams were composed of students who went above and beyond their normal coursework and chose to be a part of a research team in the NeuroErgo Lab through the Aggie Research Program (ARP) and AggiE_Challenge!
Research is a team effort, and each of these students brought unique insights and dedication to their work! Many of them will be continuing on into the Spring 2023 semester and we are excited to see what the future brings! Way to go.
Exo Research Team
While there is extensive research evaluating exoskeletons for static postures or tasks with limited ranges of motion, their benefits or limitations for tasks involving more complex movements and high ranges of motion are not well investigated. In sectors like healthcare, the task requirements for patient handling are seldom repetitive, require a wider range of motion, and require the use of different muscle groups at the same time. To fill this gap, students Eshan Manchanda, Vishal Gottumukkala, and Jimena Cortes Escalona participated in a study to evaluate the performance of exoskeletons for tasks specific to patient handling, and compare their benefits for tasks ranging from none to low, too high ranges of motion. This team was led by Ph.D. students Oshin Tyagi, Tiash Rana-Mukherjee, and Master’s student Shivangi Dwivedi.
The project seeks to understand the aspects of human-robot teaming in an emergency response team. In order for the robot to be a successful team member, the trust in the robot needs to be optimal. Under-trust can lead to poor utilization, while overtrust can lead to safety issues. Students Thomas Bolf, Malik Rawashdeh, Diane Lee, Nora Ghosh, and Carlos Meisel want to understand human-robot team trust and its impacts on team collaboration and processes. This team was led by Ph.D. Student Aakash Yadav.
The LEARNER team focuses on developing an adaptive training platform for next-gen emergency responders that is accessible and scalable. This semester, students Isabella Pedron, Sebastian Villa Cuellar, and Sydney Hunt utilized next-gen technology like Virtual Reality and Exoskeletons to asses how users learn overtime in a Virtual Environment. This team was led by Lindsey Brenner and Ph.D. student Shantanu Vyas.
M3X – Dynamic Trust in Automated Driving
This project aims to explore and understand how drivers’ trust towards autonomy changes in different traffic situations in order to achieve a calibrated driver trust according to the autonomy capability. The team gained experience on a state-of-the-art high-fidelity driving simulator and received systematic training on multiple human physiological & behavioral measures (fNIRS, EEG, ECG, eye-tracking, etc.). Mattias Hollman investigated how heart rate data can reflect trust-induced physiological changes via heart rate variability analysis; Mihiran Pandey and Avi Bansal conducted entropy analysis on eye tracking data for trusting gaze behaviors. This team was led by Ph.D. student Yinsu Zhang.
See you all in 2023!!!