© 2013 Massachusetts Institute of Technology. Human-robot collaboration presents an opportunity to improve the efficiency of manufacturing and assembly processes, particularly for aerospace manufacturing where tight integration and variability in the build process make physical isolation of robotic-only work challenging. In this paper, we develop a robotic scheduling and control capability that adapts to the changing preferences of a human co-worker or supervisor while providing strong guarantees for synchronization and timing of activities. This innovation is realized through dynamic execution of a flexible optimal scheduling policy that accommodates temporal disturbance. We describe the Adaptive Preferences Algorithm that computes the fle...