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Science robotics

Skill brycewang-stanford/Awesome-Journal-Skills/English-NaturalScience-Journal-Skills/skills/science-robotics

Use when targeting Science Robotics (Sci Robot) or deciding whether a robotics manuscript fits this AAAS venue. Encodes the journal's fit, framing, method-and-evidence bar, house style, official-submission re-check, and desk-reject heuristics.From its SKILL.md

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npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill science-robotics

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SKILL.md

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Science Robotics (science-robotics)

Journal positioning

Science Robotics is an AAAS journal dedicated to robotics research with demonstrated capability and broad scientific or societal significance. It occupies a position analogous to other Science-family specialty journals: the bar is not incremental technical improvement in a niche robotic system but a result that shifts what is possible or understood in robotics and is legible to scientists outside the immediate sub-field. Demonstrated performance in realistic or challenging environments — not just simulation — is a recurrent editorial requirement. The readership includes roboticists, engineers, biologists, materials scientists, and clinical researchers who engage with robotics as a tool for scientific discovery or societal benefit.

This skill is a fit / venue-selection / re-framing tool. It does not replace the journal's current official submission guidelines. Before submitting, re-check the live author instructions on the AAAS / Science Robotics site and the submission system.

When to trigger

  • The author names Science Robotics or Sci Robot as the target venue.
  • A robotics paper claims broad significance and demonstrated capability and the author is evaluating AAAS tier versus IEEE or Nature-family alternatives.
  • A paper from an adjacent field (materials, biology, medicine) involves a robotic system with field-level significance and needs venue framing.
  • The author wants to identify the most common desk-reject risks for this venue.

Scope & topic fit

  • Novel robotic systems demonstrating new locomotion, manipulation, sensing, or actuation capabilities in realistic conditions.
  • Soft robotics, bioinspired robotics, and morphological computation with demonstrated mechanical capability and conceptual insight.
  • Human-robot interaction and collaborative robotics with demonstrated safe, effective performance in human-scale environments.
  • Medical robotics, surgical systems, and rehabilitation devices where demonstrated clinical or preclinical performance is central.
  • Autonomous systems and robot intelligence (perception, planning, learning) where the robotic integration and demonstrated task performance are the primary contribution.
  • Robotic exploration, environmental monitoring, or disaster response with documented field performance.

Method & evidence bar

  • Demonstrated capability is the primary bar: results must show the robot doing something genuinely new, not a slightly better version of existing capabilities; real-world or realistically constrained experiments are preferred over pure simulation.
  • Physical performance claims must be quantified with appropriate metrics, repeated trials, and statistical characterization; single-run demonstrations are insufficient for central claims.
  • For learning-based robotics, the training environment and sim-to-real transfer assumptions must be clearly stated; evaluation in conditions that differ from training is expected.
  • Fabrication and hardware reproducibility: materials, manufacturing processes, and key parameters should be described with sufficient detail for the robotics community to assess reproducibility.
  • Videos and supplementary demonstrations are expected and strongly influence editorial evaluation; production quality of videos should match the significance of the claim.
  • Comparison to relevant prior robotic systems is required; the performance advance must be quantified relative to credible baselines.

Structure & house style

  • AAAS format: Research Article format with abstract, introduction, results, discussion, materials and methods; re-check current Science Robotics specific requirements.
  • The abstract and introduction must establish broad significance: what barrier in robotics or in the broader science/society this work removes.
  • The structured abstract (if required by current instructions) should be drafted; check current AAAS requirements for this venue.
  • Video supplementary material is expected for experimental results; the editorial office reviews video evidence alongside text claims.
  • Main text figures should demonstrate the system in action; schematics, performance plots, and comparison tables should be integrated logically.
  • Supplementary Materials carry extended methods, fabrication protocols, additional experimental data, and video captions.

Official-submission checklist

  • Before giving submission-ready advice, read ../../resources/source-basis.md and ../../resources/official-source-map.md; start from the official source anchors for this journal family, then cite the current journal-specific page you checked.
  • Search the live AAAS site for "Science Robotics information for authors" and follow the current version.
  • Re-check article type (Research Article, Review, Research Resource, Focus, Perspective), length, and figure limits.
  • Prepare supplementary video(s) meeting current format and size requirements; include video captions.
  • Confirm data availability statement and any requirements for hardware design files or code.
  • Complete AAAS ethics, competing-interest, and author-contribution disclosures.
  • Check AI-use disclosure requirements.
  • If the live official instructions conflict with this skill, the official instructions win.

Pre-submission self-check

  • One sentence stating what robotics capability this paper enables that was not possible before, and why it matters broadly.
  • Central performance claims are supported by repeated experiments with quantified statistics, not single demonstrations.
  • Physical hardware demonstrations are the primary evidence; simulation results (if any) are positioned as supporting analysis.
  • Supplementary video is prepared and directly substantiates the key performance claims.
  • The paper positions its advance against the most capable prior robotic systems with quantitative comparisons.
  • Fabrication/hardware details are sufficient for the community to assess reproducibility.

Common desk-reject triggers

  • Incremental improvement on an existing robotic system without a novel capability or conceptual advance.
  • Primary evidence from simulation alone, with no physical demonstration or compelling argument for why physical results are unnecessary.
  • Performance claims not supported by repeated trials and statistical characterization.
  • Missing or low-quality supplementary video for experimental claims.
  • Narrow technical robotics contribution without articulated broader significance beyond the immediate sub-community.

Re-routing decision

Robotics papers with strong ML/AI framing and broader AI significance → nature-machine-intelligence. Computer vision or perception methods not tightly tied to physical robotic performance → ieee-transactions-on-pattern-analysis-and-machine-intelligence. Excellent robotics methods work that is rigorous but narrower in significance → IEEE Transactions on Robotics or the International Journal of Robotics Research. Soft-materials or actuator advance without full robotic system integration → nature-materials or advanced materials venues.

Output format

[Fit] High / Medium / Low (one-line reason)
[Target] Science Robotics
[Topic tags] <2–3 closest topics>
[Method/evidence] <does the demonstrated physical capability and significance clear the AAAS bar?>
[Top risk] <the single most likely reason for rejection>
[Official items to re-check] <article type / length / video supplementary / data-code / ethics / disclosures>
[Re-route suggestion] <if not a fit, a better-matched venue>

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