Presentation
Adaptive Mission Planning: Initial Development of Technologies for Evolving Workload Predictions Across Missions
DescriptionThe purpose of the present study is to determine how mission data, terrain data, and participant feedback in an after-action review (AAR) can be combined to improve performance of a human-autonomy team in consecutive missions. The overall goal of the research is to move toward an intelligent mission planning interface that integrates passively collected human performance data, explicit human feedback, and terrain data to generate and extrapolate dynamic cost maps of upcoming mission areas. This is the first of several planned studies in the development of intelligent mission planning technologies, therefore secondary goals of the study are to identify necessary improvements to the simulation environment, scenario design, and workload prediction algorithm used in the study. In this paper, we investigate how these intelligent mission planning tools impact performance, and we analyze qualitative feedback from participants to understand how the implementation of these tools can be improved in future iterations.
Event Type
Lecture
TimeTuesday, September 10th10:25am - 10:45am MST
LocationFlagstaff
Human AI Robot Teaming (AI)