CMU CENTER OF EXCELLENCE: Trusted Human-Machine Teaming
Abstract
The Carnegie Mellon University Center of Excellence in Trusted Human-Machine Teaming aims to provide the underlying science and technology for an integrated framework for human cognitive state estimation in the context of adaptive human-machine teaming, algorithms for human and machine adaptation that reflect tenets of human teamwork, and elucidate the relationship between trust dynamics, mutual adaptability and understanding in the context of human and multirobot eamwork under high uncertainty and risk. In close collaboration with AFRL scientists the research will integrate methods from neuroscience, cognitive modeling, AI and robotics to develop and test the framework. The research will provide multiple innovations including (a) neural estimation of human intention before conscious decision, (b) neural detection and estimation of affective states based on object valence, (c) perceptual learning, (d) cognitive modeling of elements of mental state and their mapping to the neurological level, (e) scalable algorithms for trusted human-machine teamwork with multiple autonomous teammates, under uncertainty and risk, (f)planning for appropriate adaptations on the part of the mult-agent autonomous system, and (g) efficient computational methods for co-adaptive trust calibration of system and human. The research goals are totally aligned with the Air Force strategic vision for trusted autonomy of large numbers of adaptively collaborating autonomous agents teaming with humans. In particular, the research results will contribute to (a) the design and evaluation of trusted autonomous multi-robot systems, (b) effective intervention and training methods to allow operators to appropriately calibrate their trust in their machine team mates, and (c) prediction of limitations and benefits of engineered multi-robot systems in the context of adaptive human-machine teaming.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 28, 2018
- Source ID
- FA95501810251
Entities
People
- Katia Sycara
Organizations
- Air Force Office of Scientific Research
- Massachusetts Institute of Technology
- United States Air Force