A pressure test, not a market census
The sample contains three integrated or networked actuators, three robot stereo/depth cameras, three 3D LiDAR sensors, three embedded compute platforms and three battery or cell records. Products were selected to make unlike architectures collide with one schema—not to estimate market share or declare category leaders.
For each comparison, RCI fixed six decision fields before checking the records. A field counted as filled only when the selected official source supported a model-level value or bounded description. A filled cell does not mean the value is comparable; it only means a traceable public claim exists.
The percentages below describe this 15-product audit sample and selected source set as checked on 2026-08-09. They must not be generalized to every product from the same manufacturer or to the whole market.
Public records fill 75 of 90 selected cells
| Comparison | Records | Filled cells | Completeness | Fields with at least one gap |
|---|---|---|---|---|
| Integrated joint actuator evidence table | 4 | 19 / 24 | 79% | Continuous / rated torque; Speed claim; Mass; Reduction ratio |
| Robot stereo and depth camera evidence table | 4 | 22 / 24 | 92% | Published range; Accuracy / precision |
| Robot 3D LiDAR evidence table | 3 | 14 / 18 | 78% | Channels; Power; Synchronization |
| Robot main-compute platform evidence table | 7 | 29 / 42 | 69% | CPU; AI acceleration claim; Memory; Camera I/O; Power envelope; Software baseline |
| Robot battery and cell evidence table | 4 | 19 / 24 | 79% | Energy; Discharge current; Pack communication; Safety / transport evidence |
| Robot USB-to-CAN interface evidence table | 2 | 12 / 14 | 86% | CAN FD support; Driver / API baseline |
The actuator and depth-camera samples each fill 16 of 18 selected cells. LiDAR and compute each fill 14. The power sample fills 15. The apparent completeness is deceptive: many populated cells still use incompatible labels, operating modes or boundaries.
The larger problem is not missing numbers—it is missing equivalence
All three actuator records publish a headline torque and speed, but one headline is peak torque, one is stall torque and one is peak torque paired with a separate rated value. Only two selected records provide a continuous or rated field, and the visible source conditions are not identical. Converting every torque to N·m would produce a numerically tidy but technically false comparison.
The same pattern appears in perception. Camera records use ideal, optimal and product-mode language; LiDAR records distinguish reflectivity-conditioned range, instrument range and maximum range. Resolution and frame-rate maxima frequently belong to different modes. A product-family page may publish the highest channel count or point rate without proving that every orderable variant has it.
Compute fields are even more architecture-dependent. NVIDIA publishes an INT8 sparse TOPS figure. The selected Qualcomm brief describes heterogeneous accelerators but not a directly comparable TOPS figure. Raspberry Pi publishes CPU, memory, I/O and a long production commitment without a built-in NPU claim. “Unknown” in the TOPS cell is therefore a documentation result, not a zero.
All 89 launch claims still begin as manufacturer evidence
| Evidence state | Count | Meaning in this release |
|---|---|---|
| M · Manufacturer claimed | 157 | Transcribed from an official product page, manual or data sheet. |
| D · RCI derived | 1 | One nominal-energy calculation with formula and limitation shown. |
| V · Independently verified | 0 | No launch claim has yet passed the independent verification gate. |
| C · Conflicting | 1 | No formal conflict group is published yet. |
| U · Unknown | 0 | Unknowns are rendered as absent cells rather than synthetic claim rows in v0.1.0. |
This is the most important result of the audit. Official manufacturer documents are appropriate sources for identity and reported specifications, but they do not independently validate performance. RCI therefore does not describe the launch catalog as verified hardware performance.
The next release should invest in conditions and integrations
Adding more model names would increase page count without solving the evidence problem. The next actuation sprint will prioritize duty-cycle curves, thermal assumptions, exact bus implementation, output sensing, bearing-load limits and revision identity. The non-joint tracks will prioritize camera/LiDAR test conditions, carrier-board sensor combinations, compute power modes, battery communication and pack-level safety evidence.
Independent evidence will be added claim by claim from reproducible papers, public BOMs, certification listings and disclosed laboratory tests. A third-party source will not be labeled verification merely because it repeats a vendor table.
- Expand actuation from three to 25–50 audited records after the schema remains stable.
- Add 5–10 further samples each for vision/LiDAR, compute and power before declaring their comparison fields mature.
- Create explicit conflict groups when revisions or credible sources disagree.
- Request factual review from manufacturers without granting editorial control.
Download and reproduce the audit
The complete product, manufacturer, claim, source, condition and comparison records are available in JSON and flattened CSV. The public methodology defines the evidence states and publication gate.
Suggested citation: Robot Component Index, “15 Robot Components Audited: What Public Product Records Publish — and Omit,” dataset v0.1.0, 2026-08-09.