Research & Technical Experience

The Human-Automation Interaction and Cognition (THInC) Lab

New robotic technologies are being introduced to save lives, increase efficiency and decrease operational costs in high-risk domains such as the military. However, there are growing concerns that the benefits of these systems may not be realized due to operators not trusting robots appropriately, resulting in their misuse and disuse. Poor trust calibration (i.e., both too much and too little trust) can result from a lack of transparency where humans and robots are not aware of each other’s states, plans, and actions.

My PhD research examines how human-robot interfaces may communicate intent, reasoning, and confidence information to increase transparency, facilitate appropriate trust, and support joint system performance. To date, little is known about how best to present this information, especially in high-tempo operations where operators need to quickly assess a machine’s trustworthiness and make decisions about compliance with its recommendations. In this line of research, candidate designs are being developed and empirically evaluated in the context of a simulated ground control station display for multiple unmanned aerial vehicles (UAVs).  These studies draw on multidisciplinary research in human factors, robotics, social psychology, artificial intelligence, and philosophy to design more transparent displays that will ultimately improve the safety and efficiency of human-robot teams in high-risk domains.

Duke University Robotics and Manufacturing Automation (RAMA) Lab

My research project in the Robotics and Manufacturing Automation (RAMA) Laboratory focused on developing decentralized control for the Entrapment/Escorting Mission. The mission tasks a swarm of robots to behave as bodyguards and follow a roaming target. The system utilized decentralized control, meaning each robot had to independently determine its movement without communicating with its peers or receiving direction from a central controller. The robots equally spaced themselves around the target to minimize gaps, and in this research, decentralized control was provided through artificially applying energies based on the Morse potential function. The simulation was performed using the commercial software package Webots, and the algorithm was experimentally validated in the RAMA Lab using e-puck robots.


  • Lieberman, K. M., Fricke, G. K., & Garg, D. P. (2012, October). Decentralized control of multi-agent escort formation via Morse potential function. In Proceedings of the 2012 ASME Dynamic Systems and Control Conference (DSCC2012), Ft. Lauderdale, FL.
  • Fricke, G. K., Lieberman, K., & Garg, D. P. (2012, October). Swarm Formations Under Nonholonomic and Numerosity Constraints. In ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference (pp. 475-481). American Society of Mechanical Engineers.