Information requirements for function allocation during Mars mission exploration activities

2019-12-05T14:43:42Z (GMT) by Jordan R Hill
The desire to send humans to Mars will require a change in the way that extravehicular activity (EVA) is performed; in-space crews (including those within a vehicle or habitat monitoring others conducting EVA) will need to be more autonomous and that will require them to monitor large amounts of information in order to ensure crew safety and mission success. The amount of information to perceive and process will overwhelm unassisted intra-vehicular (IV) crewmembers, meaning that automation will need to be developed to support these crews on Mars while EVA is performed (Mishkin, Lee, Korth, & LeBlanc, 2007). This dissertation seeks to identify the information requirements for the performance of scientific EVA and determine which information streams will need to be allocated to in-space crew and which are the most effective streams to automate. The first study uses Mars rover operations as a homology—as defined by von Bertalanffy (1968)—to human scientific exploration. Mars rover operations personnel were interviewed using a novel method to identify the information requirements to perform successful science on Mars, how that information is used, and the timescales on which those information streams operate. The identified information streams were then related to potential information streams relevant to human exploration in order to identify potential function allocation or automated system development areas. The second study focused on one identified mission-critical information stream for human space exploration: monitoring astronaut status physiologically. Heart rate, respiration rate, and heart rate variability measurements were recorded from participants as they performed field science tasks (potentially tasks that are similar to those that will be performed by astronauts on Mars). A statistical method was developed to analyze this data in order to determine whether or not physiological responses to different tasks were statistically different, and whether any of those differences followed consistent patterns. A potential method to automate the monitoring of physiological data was also described. The results of this work provide a more detailed outline of the information requirements for EVA on Mars and can be used as a starting point for others in the exploration community to further develop automation or function allocation to support astronauts as they explore Mars.