Automated Spacewalk Task and Route Advisor (ASTRA) gives EVA planners a tool to efficiently make an optimal decision and the confidence to clearly advocate their choices. Our system guides EVA planners through their process by providing automated, optimized paths as a starting point for path building. ASTRA gives users the ability to compare, refine, and summarize their path decisions. Through this process, EVA planners build confidence, crystallize their arguments, and prepare to advocate their decisions to their peers.
During Extra-Vehicular Activities, EVA planners must monitor for any current or future deviations in the EVA from the original planned path. Live View enables planners to see where astronauts are, and monitor how they are progressing along their route.
In order to better visualize constraints and geospatial information, GIS data layers are integrated into the lunar map view. GIS data layers can also be leveraged to visualize constraints, as seen in the Metabolic Advisor.
If an EVA is subject to change, ASTRA will surface an off-nominal notification in the Live View map. Off-nominal notifications can indicate varying levels of severity. This visual, paired with existing comm loops, enhances an EVA planner’s understanding of plan changes.
When generating a new path, EVA planners must first select the waypoints that they expect the astronauts to cover. When beginning from an off-nominal notification, the New Waypoint, as well as the original path’s waypoints are pre-selected.
With waypoints selected, the EVA planner may choose an optimization function to create their path options. Path building algorithms informed by optimization functions have previously been utilized in rover missions, and can be expanded to human EVA operations.
The system is able to auto-generate paths according to a specified optimization function and waypoints. This automation eliminates impossible (i.e., unsafe) routes, allowing EVA planners to focus their time and energy on choosing between the potential compatible futures.
Route information is organized in a table format, allowing EVA planners to quickly and easily compare route options’ statistics. Additionally, there are indicators to differentiate between values that are safe, approaching danger, or completely dangerous.
As a planner compares and narrows down, they can deselect paths in the table to hide them from the map. This enables EVA planners to make more nuanced comparisons as they finalize their decisions.
The optimization functions that inform ASTRA’s automated path generation rely on physical constraints, or constraints that have clear safety & feasibility parameters. For more nebulous constraints, ASTRA enables planners to use their judgement to make informed modifications.
Path modification leverages existing GIS design patterns, with editing tools EVA planners are already familiar with. While ASTRA does give the freedom for planners to edit paths, the system does make it clear if a proposed change will violate a constraint identified by the optimization function. For example, if a path modification pushes the expected CO2 saturation beyond an acceptable margin, ASTRA will make this visually evident to the user.
Once an EVA planner reaches a path modification decision, an overview page of the changes of the new path as it compares to the original path will appear.
We devised a test to evaluate the efficacy of ASTRA for tactical EVA planning. Through a comparison with the planners' current tools, we quantified and observed the potential impact of ASTRA on the EVA decision-making process.
We tested our design with 9 NASA personnel and experts with experience in EVAs and related fields. We weighted each participant according to their level of direct experience working with EVAs.
Participants were given a scenario that places them in the middle of an EVA, where an incident happened that required re-planning of the remainder of the EVA. With consideration of specific factors and safety rules, they then had to decide on a new route twice: once using the control design and once using ASTRA.
Our ultimate goal was to see whether our solution decreases negative workload-related emotions and increases confidence in advocating their decision
Control
To mimic the current manual tools and fragmented data that EVA planners currently rely on, our control was a spreadsheet with a series of data of an EVA divided up by several tabs.
Experimental
Our experimental design was the first iteration of ASTRA, where all the potential routes were on one map and associated data was laid out in a table.
Think Aloud
We asked participants to think aloud while they decided on a route to help us better understand their thoughts and feelings during the decision-making process. This allowed us to gather qualitative data on how they felt making a decision.
Confidence Rating
After choosing a route, participants were asked to rate their confidence in their decision on a scale of 1 (not confident at all) to 10 ( completely confident).
NASA Task Load Index (TLX) Questionnaire
NASA Task Load Index (TLX) Questionnaire: Participants were asked to complete the NASA Task Load Index (TLX) questionnaire to assess their subjective workload ratings for our tool as it compares to the control.
"I hope we actually get to use a tool like that" - EVA Systems Engineer
In our tests, we qualitatively and quantitatively measured confidence & workload metrics of ASTRA’s users in comparison to their experiences with the control. During observation, we noted fewer instances of hesitation, more confident body language, and more certain phrasing when justifying responses to the experiment’s EVA Officer. In our post-test interview questions, most users expressed positive comparisons to the control test in terms of ease of use and access to information. Furthermore, users who had actual experience in EVA back rooms shared positive comparisons to existing workflows.
To bolster these observations, we utilized TLX questionnaire and confidence rating metrics to help us quantify subjective experiences reliably and consistently. Here are our results:
NASA Task Load Index (TLX) Subjective Workload
In the context of the EVA workflow, we believe this decreased mental load will result in more mental energy spared towards optimal decision making. By making it more difficult to design a plan that violates clear constraints, ASTRA allows EVA planners to focus on decisions that require human judgment.
NASA TLX Manual >
Confidence Ratings
In our research, we found that difficulties expressing certainty in a modified plan were responsible for lost time and increased frustration in the chain of command. This increase in self-confidence supports our belief that ASTRA’s guided path building process helps to crystallize a planner’s line of thinking, resulting in more confident advocacy of a modified plan.
