A navigating system will be highly valuable to astronauts during EVA on planetary surfaces. Applied to the future manned missions to the Moon, a lunar EVA mission planner will assist astronauts navigate during their traverses and our mission planning system informs the crewmember of planetary terrain mapping (digital elevation maps, editing, waypoint automation and path planning, 3D viewing and zooming), sun illumination levels, life support status, metabolic costs, scientific timelines and emergency walkback calculations. For geology and scientific purposes the planner includes re-planning options and allows the use to specify lunar sample acquisition location. The EVA mission provides explorers with real-time traverse assessment and navigation and was designed to be interfaced with existing NASA metabolic workload (LEGACI) and voice recognition (MAS) capabilities. Balancing task allocation between humans and computers is crucial to the development of effective decision support systems.
This research effort investigates the appropriate balance between humans and automation for geospatial path problem solving within the high-risk domain of human planetary surface exploration, where decisions are time critical and humans must adapt to uncertainty. In order to develop flexible and robust decision support systems for Lunar and planetary exploration, human-automation role allocations are examined to understand how humans conduct complex optimizations under different automated assistance. Human-in-the-loop testing was employed to understand the effects of the automated assistance and different visualizations on path planning performance across multivariate cost functions. Based on experimental results, knowledge-based reasoning is supported more by manual sensitivity analysis as opposed to automated generate paths. While the latter results in overall better path performance, the dependence on this aid leads to automation bias and decreased situation awareness and manual sensitivity analysis. With respect to visualizations, elevation contours promoted low cost paths with short task time when human operators could depend on the automation.