Sun-Synchronous Robotic Exploration: Technical Description and Field Experimentation
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
Sun-synchronous robotic exploration is accomplished by reasoning about sunlight: where the Sun is in the sky, where and when shadows will fall, and how much power can be obtained through various courses of action. We conducted experiments in the Canadian high arctic using a solar-powered rover to prove the concept of Sun-synchronous exploration. Using knowledge of orbital mechanics, local terrain, and locomotion power, the rover Hyperion planned Sun-synchronous routes to visit designated sites while obtaining the necessary solar power for continuous operation. Hyperion executed its plan, beginning and ending each 24-h period with batteries fully charged, after traveling two circuits of more than 6 km in barren, Mars-like terrain. The objective of the Sun-Synchronous Navigation project (http://www.frc.ri.cmu.edu/sunsync) was to create hardware and software technologies needed to realize Sun-synchronous exploration and to validate these technologies in field experimentation. In the process, we learned important technical lessons regarding rover mechanism, motion control, planning algorithms, and system architecture. In this paper we describe the concept of Sun-synchronous exploration. We overview the design of the robot Hyperion and the software system that enables it to operate in synchrony with the Sun. We then discuss results and lessons from analysis of our field experiments. This paper describes rover and planetary exploration research at Carnegie Mellon during 2000-2002.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.002 | 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