Autonomous Training for Long-Term Spaceflight

This technology evaluates the performance data of a simulated SSRMS visiting vehicle capture and generates a scenario to target any weaknesses seen the in previous capture attempt. Scenarios are varied primarily by adjusting the initial vehicle offsets relative to SSRMS as well as the vehicle drift rates. Malfunctions can also be included for crew practice of off-nominal scenarios, such as electronic or mechanical failures of the SSRMS. The technology employs a series of strategy modules that individually analyze aspects of the performance data and compete for relevance in the overall assessment of the data. For example, analysis of the crew hand controller inputs and vehicle alignment may show that the crew had suboptimal performance along a specific axis of the SSRMS approach toward the visiting vehicle. In that case, the simulator would generate a scenario tuned for that specific axis to allow the crew additional practice until demonstrating success in that weak area. Crew performance data is also plotted to allow for tracking the skill retention levels over time and adjusting the overall difficulty of the scenarios to rebuild the skills at an appropriate pace.