Design and Modeling of a Spherical Robot Actuated by a Cylindrical Drive
Bibliographic record
Abstract
Rolling spherical robots have been studied in the past few years as an alternative to legged and wheeled robots in unstructured environments. These systems are of uttermost interest for space exploration: fast, robust to collision and able to handle various terrain topologies. This paper introduces a novel barycentric spherical robot, dubbed the Autonomous Robotic Intelligent Explorer Sphere (ARIES). Equipped with an actuated cylindrical joint acting as a pendulum with two degrees-of-freedom (DoF), the ARIES has a continuous differential transmission to allow simultaneous rolling and steering. This mechanism allows an unprecedented mass allocation optimization, notably to provide a low center of mass. Kinematics and dynamics of this novel system are detailed. An analysis of the steering mechanism proves that it is more efficient than a more conventional 2-DoF tilting mechanism, while also retaining more space for a payload, for instance to host sensors for simultaneous localization and mapping, in the upper part of the sphere. Moreover, the kinematic input/output equations obtained significantly simplify the device's control. Finally, we present a first complete prototype with preliminary experimental tests.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".