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ieee-transactions-on-robotics

Use when targeting IEEE Transactions on Robotics (T-RO) or deciding whether a robotics manuscript fits this venue. Encodes the journal's fit, the co…

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IEEE Transactions on Robotics (ieee-transactions-on-robotics)

Journal positioning

IEEE Transactions on Robotics (T-RO), published jointly by the IEEE Robotics and

Automation Society and partnering societies, is a flagship archival venue for

complete, rigorously validated robotics contributions: manipulation,

locomotion, motion planning, control, perception-for-action, estimation, and

mechanism/system design. The defining expectation is a self-contained advance

demonstrated through experiments on real robots or high-fidelity simulation,

with quantitative evaluation — not a preliminary idea or a method shown only on a

toy. Compared with its sibling the-international-journal-of-robotics-research,

T-RO favors complete, well-validated results, while IJRR leans to longer,

conceptually framed archival treatments; route by depth-of-framing vs.

completeness-of-validation. This skill is a fit / venue-selection / re-framing

tool. It does not replace the journal's current official author information.

Before submitting, re-check the live IEEE T-RO author guidance and submission system.

When to trigger

  • The author names T-RO for a manipulation, locomotion, planning, control, or

perception-for-action manuscript and wants a fit/framing check.

  • A result must be re-framed from "a method that works in simulation" into a

complete contribution with real-robot or high-fidelity experimental validation.

  • The author is choosing between T-RO and the-international-journal-of-robotics-research,

or between T-RO and a conference-paper extension.

  • The author needs T-RO's experimental-validation bar and desk-reject heuristics.

Scope & topic fit

  • Manipulation and grasping: dexterous and contact-rich manipulation, planning and

control of manipulators, tactile/force-based interaction.

  • Legged, wheeled, aerial, and underwater locomotion: dynamics, gait, and control

demonstrated on physical platforms or validated high-fidelity simulation.

  • Motion and task planning: sampling-based, optimization-based, and learning-based

planning with analysis and demonstrated performance.

  • Robot control and estimation: whole-body control, state estimation, SLAM-for-control,

and learning-based control with real-system evaluation.

  • Perception for action: closing the loop from sensing to robot behavior, where the

robotics contribution (not the vision algorithm alone) is central.

  • Mechanism, actuator, and system design: novel robot designs validated by

characterization and task demonstration.

Method & evidence bar

  • Experiments on real robots are the norm; high-fidelity simulation is

acceptable when justified, but pure toy simulation rarely clears the bar.

  • Evaluation must be quantitative and statistically meaningful: report trials,

success rates, error metrics, and timing, with appropriate baselines.

  • The contribution must be complete — formulation, method, analysis (where relevant),

and a convincing experimental campaign — not a preliminary proof-of-concept.

  • Compare against the closest robotics baselines under matched conditions; ablate to

show which component drives the gain.

  • For learning-based methods, address sim-to-real transfer, generalization, and

robustness, not just one trained instance on one setup.

  • Provide reproducibility detail: platform, parameters, and ideally a supplementary

video and code/data per current policy.

Structure & house style

  • IEEE double-column format; T-RO publishes full-length Papers (substantial,

archival) — match the contribution to that scope and re-check current article types

and length policy on the live guide.

  • The introduction frames the robotics problem and the gap, then states the complete

contribution; conference-to-journal extensions must add substantial new content.

  • Figures are load-bearing: system/method diagrams, experimental setups, result

plots with error bars, and frames from the accompanying video.

  • A thorough experimental-results section is central; tables summarize quantitative

comparisons across baselines and conditions.

  • A supplementary video is strongly expected for hardware results.

Official-submission checklist

  • Before giving submission-ready advice, read ../../resources/source-basis.md and

../../resources/official-source-map.md; start from the IEEE Author Center

anchors, then cite the current T-RO-specific page you checked.

  • Search the live site for "IEEE Transactions on Robotics information for authors"

and follow the current ScholarOne/IEEE version.

  • Re-check article types, page/length limits and overlength policy, and the IEEE

double-column template.

  • Confirm video, code/data, and reproducibility submission requirements.
  • Re-check ORCID, competing-interests, funding, author-contribution, and AI-use

disclosure requirements, and IEEE open-access options.

  • If the live official instructions conflict with this skill, the official

instructions win.

Pre-submission self-check

  • [ ] The contribution is a complete robotics advance, not a preliminary idea or single toy demo.
  • [ ] Validation is on real robots (or justified high-fidelity simulation) with quantitative metrics.
  • [ ] Results report trials/success rates/errors with appropriate baselines and ablations.
  • [ ] Learning-based claims address transfer, generalization, and robustness beyond one setup.
  • [ ] Any conference precursor is substantially extended with new content.
  • [ ] A supplementary video and reproducibility detail accompany hardware results; length fits current limits.

Common desk-reject triggers

  • Method shown only in toy simulation with no real-robot or high-fidelity validation.
  • Preliminary proof-of-concept lacking a complete formulation, analysis, or convincing experiments.
  • Incremental conference extension with little new content beyond the prior paper.
  • A computer-vision or learning paper with a robot used only as a label, no robotics contribution.
  • Quantitative evaluation without baselines, trials, or statistics; cherry-picked single runs.

Re-routing decision

  • Longer, conceptually framed, foundational archival robotics → the-international-journal-of-robotics-research.
  • Control-theoretic result with guarantees as the core → ieee-transactions-on-automatic-control / automatica.
  • Industrial robot deployment with hardware-system focus → ieee-transactions-on-industrial-electronics.
  • Medical/surgical-robotics imaging contribution → ieee-transactions-on-medical-imaging / ieee-transactions-on-biomedical-engineering.
  • Focused, timely result → a robotics letters venue or conference.

Output format

[Fit] High / Medium / Low (one-line reason)
[Target] IEEE Transactions on Robotics
[Topic tags] <2–3 closest robotics subtopics>
[Contribution] <the complete robotics advance in one line>
[Method/evidence] <does the real-robot / high-fidelity validation clear T-RO's completeness bar?>
[Top risk] <the single most likely reason for rejection>
[Article type] Paper
[Official items to re-check] <article type / length / template / video-code-data / disclosures>
[Re-route suggestion] <if not a fit, a better-matched venue>

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原文件路径Engineering-Technology-Journal-Skills/skills/ieee-transactions-on-robotics/SKILL.md

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