Cognitive Autonomy:

Human-machine interaction and teaming

Mission

The objective of this research is a new architecture for modeling, prediction, and control of cyber-physical systems with a human in the loop, that is highly responsive to the human, yet maintains safety, reliability, and high performance.


Supported by NSF CNS-1836952

Research Topics and Publication

Human behavior modeling

Shared control for human operator training

Inverse optimal control

Human subject experiments

  • S. Byeon, W. Jin, D. Sun and I. Hwang, "Human-Automation Interaction for Assisting Novices to Emulate Experts by Inferring Task Objective Functions," 2021 IEEE/AIAA 40th Digital Avionics Systems Conference (DASC), 2021, pp. 1-6, doi: 10.1109/DASC52595.2021.9594324. [Student Paper Awards Finalist]

  • S. Byeon, D. Sun and I. Hwang, "Skill-level-based Hybrid Shared Control for Human-Automation Systems*," 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2021, pp. 1507-1512, doi: 10.1109/SMC52423.2021.9658994.

  • D. Sun and I. Hwang, 2020. On Controlled Mode Discernibility for Nonlinear Hybrid Systems with Unknown Exogenous Input. Submitted to Automatica.

  • S. Byeon, D. Sun, and I. Hwang, "Human behavior modeling via identification of task objective and variability," Submitted to IEEE transactions on human-machine systems.

  • S. G. Clarke, S. Byeon and I. Hwang, "A Low Complexity Approach to Model-Free Stochastic Inverse Linear Quadratic Control," in IEEE Access, vol. 10, pp. 9298-9308, 2022, doi: 10.1109/ACCESS.2022.3144933.

People

  • Principal investigators

  • Team members

    • Dawei Sun

    • Joonwon Choi

    • Yutong Zhang

Sponsor and Collaboration

NSF CPS Frontier: Cognitive Autonomy for Human CPS (learn more). From 2019 to present (2022)