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Design and Modeling of a Spherical Robot Actuated by a Cylindrical Drive

2022· article· en· W4285038229 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venue2022 International Conference on Robotics and Automation (ICRA) · 2022
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space Agency
KeywordsKinematicsPayload (computing)RobotMechanism (biology)Control theory (sociology)Robot kinematicsComputer scienceTerrainInverted pendulumDegrees of freedom (physics and chemistry)Kinematics equationsTrajectoryTopology (electrical circuits)SimulationEngineeringMobile robotPhysicsArtificial intelligenceClassical mechanics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.238
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it