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

ICRA 2019, RA-L, AHFE, and ACM CSUR Papers Accepted

The following new research publications have been accepted:

-S. McGuire, P.M. Furlong, T. Fong, C. Heckman, D.J. Szafir, S. Julier, and N.
, “Everybody Needs Somebody Sometimes: Validation of Adaptive Recovery in
Robotic Space Operations,”  accepted to IEEE Robotics and Automation Letters and ICRA 2019 — congratulations, Steve!

-J. Stechschulte, N. Ahmed, and C. Heckman, “Low-overlap 3-D point
cloud registration with Bayesian outlier rejection,” accepted to ICRA 2019 — congratulations, John (from Prof. Chris Heckman’s ARPG research group)!

-B. Israelsen and N. Ahmed, “‘Dave…I can assure you…it’s going to be alright…’:
A definition, case for, and survey of algorithmic assurances in human-autonomy trust
ACM Computing Surveys, v.51 no.6, Jan 2019, 113:1-113:37 — congratulations, Brett!

-B. Israelsen, N. Ahmed, E. Frew, D. Lawrence, and B. Argrow, “Machine Self-Confidence in Autonomous Systems via Meta-Analysis of Decision Processes,” accepted to the 2019 Applied Human Factors and Ergonomics Conference (AHFE 2019)congratulations, Brett!

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);