Comparing Rover and Helicopter Planetary Mission Architectures in a Mars Analog Setting in Iceland
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The Rover–Aerial Vehicle Exploration Network project field-tested planetary mission operations within a Mars analog environment in Iceland using stand-alone rover and helicopter architectures. Mission planning, implementation, and results are reported for the rover mission and briefly summarized for the helicopter mission. The outcomes of both missions are subsequently compared. Field implementation occurred from 2022 July to August at the Holuhraun lava flow. The rover science operations team executed a 14 sol (Martian day) mission that achieved mission, science, and sampling goals, including the contextualization, acquisition, and planned caching of two eolian and two rock samples. The helicopter science operations team executed a plan of comparable length but emphasized different science goals given long-range flight capabilities and landing limitations. The resolution and targetability of the rover payload enabled more detailed analyses, whereas the helicopter was better able to map flow-scale morphologies. The rover’s exploration was limited by daily mobility duration limits and hazardous terrain, whereas the helicopter’s exploration was constrained by landing site hazards. Resource limitations resulted from lengthier rover drives and data-volume-intensive helicopter imaging surveys. Future missions using combined rover–helicopter architectures should account for each spacecraft’s resource needs and acknowledge system strengths in different geologic settings. Both missions served to establish operations strategies and mission outcomes to be applied to future combined rover and helicopter mission architectures, while the helicopter mission also evaluated strategies and outcomes for future stand-alone airborne missions. Findings in this work are relevant to future missions seeking to optimize strategies for planetary mission operations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it