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
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>
Source: brycewang-stanford/Awesome-Journal-Skills → Engineering-Technology-Journal-Skills/skills/ieee-transactions-on-robotics/SKILL.md
1---2name: ieee-transactions-on-robotics3description: Use when targeting IEEE Transactions on Robotics (T-RO) or deciding whether a robotics manuscript fits this venue. Encodes the journal's fit, the complete-and-experimentally-validated-contribution bar, real-robot evidence rigor, the T-RO-vs-IJRR routing, house style, official-submission re-check, and desk-reject heuristics.4---567# IEEE Transactions on Robotics (ieee-transactions-on-robotics)89## Journal positioning1011IEEE Transactions on Robotics (T-RO), published jointly by the IEEE Robotics and12Automation Society and partnering societies, is a flagship archival venue for13**complete, rigorously validated robotics contributions**: manipulation,14locomotion, motion planning, control, perception-for-action, estimation, and15mechanism/system design. The defining expectation is a self-contained advance16demonstrated through **experiments on real robots or high-fidelity simulation**,17with quantitative evaluation — not a preliminary idea or a method shown only on a18toy. Compared with its sibling `the-international-journal-of-robotics-research`,19T-RO favors complete, well-validated results, while IJRR leans to longer,20conceptually framed archival treatments; route by depth-of-framing vs.21completeness-of-validation. This skill is a **fit / venue-selection / re-framing**22tool. It does not replace the journal's current official author information.23Before submitting, re-check the live IEEE T-RO author guidance and submission system.2425## When to trigger2627- The author names T-RO for a manipulation, locomotion, planning, control, or28 perception-for-action manuscript and wants a fit/framing check.29- A result must be re-framed from "a method that works in simulation" into a30 complete contribution with real-robot or high-fidelity experimental validation.31- The author is choosing between T-RO and `the-international-journal-of-robotics-research`,32 or between T-RO and a conference-paper extension.33- The author needs T-RO's experimental-validation bar and desk-reject heuristics.3435## Scope & topic fit3637- Manipulation and grasping: dexterous and contact-rich manipulation, planning and38 control of manipulators, tactile/force-based interaction.39- Legged, wheeled, aerial, and underwater locomotion: dynamics, gait, and control40 demonstrated on physical platforms or validated high-fidelity simulation.41- Motion and task planning: sampling-based, optimization-based, and learning-based42 planning with analysis and demonstrated performance.43- Robot control and estimation: whole-body control, state estimation, SLAM-for-control,44 and learning-based control with real-system evaluation.45- Perception for action: closing the loop from sensing to robot behavior, where the46 robotics contribution (not the vision algorithm alone) is central.47- Mechanism, actuator, and system design: novel robot designs validated by48 characterization and task demonstration.4950## Method & evidence bar5152- **Experiments on real robots** are the norm; high-fidelity simulation is53 acceptable when justified, but pure toy simulation rarely clears the bar.54- Evaluation must be quantitative and statistically meaningful: report trials,55 success rates, error metrics, and timing, with appropriate baselines.56- The contribution must be complete — formulation, method, analysis (where relevant),57 and a convincing experimental campaign — not a preliminary proof-of-concept.58- Compare against the closest robotics baselines under matched conditions; ablate to59 show which component drives the gain.60- For learning-based methods, address sim-to-real transfer, generalization, and61 robustness, not just one trained instance on one setup.62- Provide reproducibility detail: platform, parameters, and ideally a supplementary63 video and code/data per current policy.6465## Structure & house style6667- IEEE double-column format; T-RO publishes full-length **Papers** (substantial,68 archival) — match the contribution to that scope and re-check current article types69 and length policy on the live guide.70- The introduction frames the robotics problem and the gap, then states the complete71 contribution; conference-to-journal extensions must add substantial new content.72- Figures are load-bearing: system/method diagrams, experimental setups, result73 plots with error bars, and frames from the accompanying video.74- A thorough experimental-results section is central; tables summarize quantitative75 comparisons across baselines and conditions.76- A supplementary video is strongly expected for hardware results.7778## Official-submission checklist7980- Before giving submission-ready advice, read `../../resources/source-basis.md` and81 `../../resources/official-source-map.md`; start from the IEEE Author Center82 anchors, then cite the current T-RO-specific page you checked.83- Search the live site for "IEEE Transactions on Robotics information for authors"84 and follow the current ScholarOne/IEEE version.85- Re-check article types, page/length limits and overlength policy, and the IEEE86 double-column template.87- Confirm video, code/data, and reproducibility submission requirements.88- Re-check ORCID, competing-interests, funding, author-contribution, and AI-use89 disclosure requirements, and IEEE open-access options.90- If the live official instructions conflict with this skill, the official91 instructions win.9293## Pre-submission self-check9495- [ ] The contribution is a complete robotics advance, not a preliminary idea or single toy demo.96- [ ] Validation is on real robots (or justified high-fidelity simulation) with quantitative metrics.97- [ ] Results report trials/success rates/errors with appropriate baselines and ablations.98- [ ] Learning-based claims address transfer, generalization, and robustness beyond one setup.99- [ ] Any conference precursor is substantially extended with new content.100- [ ] A supplementary video and reproducibility detail accompany hardware results; length fits current limits.101102## Common desk-reject triggers103104- Method shown only in toy simulation with no real-robot or high-fidelity validation.105- Preliminary proof-of-concept lacking a complete formulation, analysis, or convincing experiments.106- Incremental conference extension with little new content beyond the prior paper.107- A computer-vision or learning paper with a robot used only as a label, no robotics contribution.108- Quantitative evaluation without baselines, trials, or statistics; cherry-picked single runs.109110## Re-routing decision111112- Longer, conceptually framed, foundational archival robotics → `the-international-journal-of-robotics-research`.113- Control-theoretic result with guarantees as the core → `ieee-transactions-on-automatic-control` / `automatica`.114- Industrial robot deployment with hardware-system focus → `ieee-transactions-on-industrial-electronics`.115- Medical/surgical-robotics imaging contribution → `ieee-transactions-on-medical-imaging` / `ieee-transactions-on-biomedical-engineering`.116- Focused, timely result → a robotics letters venue or conference.117118## Output format119120```text121[Fit] High / Medium / Low (one-line reason)122[Target] IEEE Transactions on Robotics123[Topic tags] <2–3 closest robotics subtopics>124[Contribution] <the complete robotics advance in one line>125[Method/evidence] <does the real-robot / high-fidelity validation clear T-RO's completeness bar?>126[Top risk] <the single most likely reason for rejection>127[Article type] Paper128[Official items to re-check] <article type / length / template / video-code-data / disclosures>129[Re-route suggestion] <if not a fit, a better-matched venue>130```131132---133134**Source:** [`brycewang-stanford/Awesome-Journal-Skills`](https://github.com/brycewang-stanford/Awesome-Journal-Skills) → `Engineering-Technology-Journal-Skills/skills/ieee-transactions-on-robotics/SKILL.md`