Icra Reproducibility

ICRA Reproducibility

Reproducibility at a robotics conference means something different than at an ML venue: no reader can rerun your hardware trials without your robot, your room, and your objects. The achievable standard is therefore two-tier — rerunnable (code, simulation, analysis) and auditable (hardware evidence logged well enough that a skeptic can verify you did what you claim). ICRA papers earn trust by being explicit about which tier each result sits in.

The specification ledger

A robotics result is unreproducible if the platform is underspecified. The paper (body, since there is no appendix escape) plus released materials should pin:

Standard object sets (YCB and similar) exist precisely so that "graspable household objects" can be a checkable claim; use them or publish the object specs.

Logging: the rosbag is the lab notebook

• Record every hardware session — including failed ones — with topic-complete rosbags (or vendor-equivalent logs) plus an untouched camera view.
• One log per trial, named by protocol: trial_<cond>_<idx>_<date>.bag; the analysis pipeline should consume these logs, so paper numbers regenerate from raw data with one command.
• Keep a session sheet: date, operator, firmware state, anomalies. Two months later, this distinguishes "the gripper was recalibrated between Tables II and III" from unexplainable drift.
• The video attachment should be cut from these recorded sessions, which guarantees footage corresponds to logged, reported trials.

Determinism where it exists, honesty where it doesn't

Hardware trials are not seed-reproducible — contact, cables, lighting, and thermal drift see to that. Split the claims accordingly:

• Deterministic tier: training runs, simulation experiments, and analysis scripts get pinned seeds, pinned dependency versions, and containerized environments. State seeds and repetition counts.
• Stochastic tier: hardware trials get protocol reproducibility — the documented procedure another lab could follow — plus dispersion reporting.
• Never write "results are fully reproducible" over a hardware table; write "code and simulation reproduce Tables I-II; hardware protocol and logs for Tables III-IV are released for audit."

Release scaffold

repo/
├── README.md            # claim → command map (Table III = run_hw_analysis.sh)
├── env/                 # Dockerfile or rosdep/lockfiles, pinned
├── sim/                 # simulation experiments, seeds fixed
├── control/             # controllers/planners as ROS packages
├── hw_protocol.md       # step-by-step trial procedure, success criterion,
│                        #   reset procedure, safety notes
├── logs/                # rosbags or download script (size!), session sheets
├── analysis/            # regenerates every figure/table from logs/
└── video/               # raw clips ↔ trial IDs mapping

Anonymize the repository for review under the double-anonymous policy (2026 cycle onward): anonymized hosting or an artifact stripped of names — an org URL is an identity leak (see icra-submission).

Compute and latency reporting

Robotics adds a real-time dimension absent from ML reproducibility norms:

• Report where each computation ran (on-board CPU/embedded GPU vs off-board workstation) and the link between them; an off-board 3090 over gigabit wire is a materially different system than on-board inference.
• State end-to-end latency per pipeline stage (sensing → perception → decision → actuation) at least once; "runs in real time" is unverifiable without it.
• Training compute (GPU-hours, hardware) belongs in the paper for learned components — cheap to report, increasingly expected by review forms.

Availability statement patterns

Honest, specific statements outperform boilerplate promises:

• "Code, simulation environments, and trial logs: (anonymized for review; public on acceptance)."
• "The gripper design files are released; the arm is commercial (UR5e)."
• "Raw rosbags total 1.2 TB; per-trial extracted features and a 40 GB sample are hosted, full logs on request."
• Avoid: "code will be released upon publication" with nothing at review time — reviewers discount unverifiable promises, and some cycles ask availability questions directly on the review form (verify the current form).

Pre-submission reproducibility pass

1. Specification ledger complete in-paper (table above, compressed)?
2. Every reported number regenerates from logs via one documented command?
3. Seeds/versions pinned for the deterministic tier; container builds clean?
4. Hardware protocol written so a stranger could run trial 1 tomorrow?
5. Release scaffold anonymized; links leak-checked?
6. Availability statement matches what actually exists today?

Output format

[Tier split] rerunnable: <tables/figs> | auditable: <tables/figs>
[Spec ledger] missing rows: <list or none>
[Log coverage] trials logged <n>/<n>, analysis regenerates: y/n
[Determinism] seeds/versions pinned for sim+training: y/n
[Release] scaffold complete? anonymized? size plan?
[Statement] honest-specific / boilerplate-risk — rewrite: <line>

Source: brycewang-stanford/Awesome-Journal-Skills → ICRA-Skills/skills/icra-reproducibility/SKILL.md