PhD student Luke Burks’ work on “Optimal Continuous State Planning with Semantic Observations” will appear at the 2017 Multi-Disciplinary Conference on Reinforcement Learning and Decision-Making in Ann Arbor, MI this June.
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 vehicles. 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