Welcome to the COHRINT (“coherent”) Lab!

Professor Nisar Ahmed’s research explores new algorithms and models for probabilistic reasoning that promote cooperative intelligence in mixed teams of humans and autonomous robotic nisar_prof_headshotvehicles. The COHRINT Lab blends this cutting-edge theory with real-world robotic software and hardware.

Key problem areas for aerospace applications include:

  • integrated sensing, perception, planning and control in human-robot teams
  • learning and prediction of human/autonomy decision making and task performance
  • fusion of complex information in dynamic sensor networks

FUSION 2018 Papers and RT-DUNE Workshop Paper Accepted

The COHRINT Lab will present 3 new papers at international conferences this summer :

“Flexible Semantic Human-Robot Sensing in Unknown Environments using Dynamic Information Gathering Policies,” by L. Burks and N. Ahmed (2018 ICRA RT-DUNE Workshop, Brisbane, Australia);

“Closed-loop Bayesian Semantic Data Fusion for Collaborative Human-Autonomy Target Search,” by L. Burks, I. Loefgren, L. Barbier, J. Muesing, J. McGinley, S. Vunnam, and N.Ahmed (FUSION 2018, Cambridge, UK);

“Weak in the NEES?: Auto-tuning Kalman Filters with Bayesian Optimization,” by Z. Chen, C. Heckman, S. Julier, and N. Ahmed (FUSION 2018, Cambridge, UK);