# Landscape doc vs How Humanoids Learn - coverage audit

*Notes from a chat with Claude, October 3–4, 2026.*

**Question:** How much of the information and data in "Open-Source Humanoid Robotics Landscape (Oct 2026)" is in, or missing from, the site "How Humanoids Learn"?

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About a fifth of the landscape doc is on the site in some form, and only a tenth of it fully. Roughly 80% is missing. The site covers the well-known core: GR00T, openpi/π0, Isaac Lab, MuJoCo, Newton and the main datasets. The open-hardware catalog and the project-tracking data are almost entirely absent.

**The numbers** (287 projects, 1,882 table cells, 547 prose sentences; the methodology section is excluded)
- **Projects:** 110 (38%) are named on the site, and 101 of those have at least one fact there. The other 177 (62%) never appear.
- **Table data:** 11% is fully on the site, 5% partly, under 1% disagrees and 83% is missing.
  - Descriptions do best: 30% are at least partly there.
  - Specs and numbers: 14%. Licenses: 10%.
  - Stars, status and last-release dates: 3%.
- **Prose:** 5% fully present, 27% partly, 2% disagrees, 67% missing.
- If a partial match counts as half, the site holds about 16% of the doc's information.

**By section** (share of facts at least partly on the site, and projects named)

| Section | Facts | Projects |
|---|---|---|
| Simulators | 54% | 13 of 18 |
| Foundation models | 37% | 14 of 24 |
| Datasets & benchmarks | 36% | 23 of 44 |
| Middleware | 33% | 5 of 13 |
| Whole-body control | 30% | 7 of 20 |
| Grippers, touch sensors, gloves | 22% | 8 of 21 |
| Stalled projects | 21% | 21 of 53 |
| Teleop systems | 17% | 4 of 10 |
| Closed-hardware humanoids | 16% | 5 of 13 |
| Activity scoreboard | 12% | 51 of 161 |
| Actuators | 10% | 1 of 7 |
| Arms | 8% | 5 of 16 |
| Dexterous hands | 3% | 4 of 14 |
| Open humanoid hardware | 3% | 1 of 14 |

The Summary (43%) and the trade-offs and recommended stacks (69%) are mostly partial matches. The site makes similar points without the doc's specifics.

**Biggest gaps**
- **Open humanoid hardware:** ToddlerBot, Berkeley Humanoid Lite, Asimov, Roboto Origin, HopeJR, OpenLoong and iCub. The height, weight, DoF and price table is entirely absent.
- **Hands and hand data:** LEAP, ORCA, RUKA, Aero Hand and AmazingHand; DexUMI, DOGlove, AirExo-2, AnySkin and 9DTact.
- **Arms and actuators:** there are no arm specs at all; the only arm figure is one OpenArm price. reBot, PAROL6, AR4, Koch, moteus, SimpleFOC, ODrive and OpenQDD are missing.
- **2026 open models, mostly Chinese:** X-VLA, RDT2, MolmoAct2, Xiaomi-Robotics-0, GigaBrain, LingBot, InternVLA, EO-1 and OpenDM. Only 1 of 44 LIBERO, SimplerEnv and download figures is there.
- **Open whole-body-control tools:** mjlab, holosoma, ProtoMotions, MimicKit, PBHC, VideoMimic, Pinocchio and Crocoddyl.
- **Tracking data:** stars, status and last release for all 161 projects, and license terms for most of them. Only Isaac Gym is called legacy, out of 22 stalled project groups.

**Where they disagree.** There are about 14 distinct points; these five matter:
1. **GR00T N1.5/N1.6 weights:** the doc says they were non-commercial until N1.7 in April 2026. The site says N1–N1.6 already allowed commercial use.
2. **GMR:** the doc calls it kinematic retargeting. The site groups it with methods that enforce contact and dynamics, which looks like a mistake on the site.
3. **SONIC on a real G1:** the doc says 100% on 50 trajectories and 19 of 20 on apple-to-plate. The site says 99.2% and 90%.
4. **Isaac Lab 3.0 early access:** the doc says Sep 16, 2026. The site says March 2026, with betas through June.
5. **RLDS, HOVER and ASAP:** the doc lists them as legacy or dormant, but the site still recommends them.

The rest are minor: LeRobotDataset v3.0 (Sep vs Oct 2025), Octo (2023 vs 2024), Galaxea Open-World (150 vs 227 tasks), SAPIEN's maintainer (Hillbot vs UCSD), and the G1 price ($16k at the 2024 launch vs from $13.5k now).

Most of the gap is catalog detail rather than missing ideas: the site explains how humanoids learn, while the doc tracks projects.

To get these numbers, I matched every project name against the site. Sub-agents then checked each fact about the 110 named projects against the site's text, players atlas, timeline and widgets, and I spot-checked their calls.

Sources:
- [Open-Source Humanoid Robotics Landscape (Oct 2026)](https://claude.ai/artifact/VyqTd5EbBqw6zbatqczFex#02732e91-8993)
- [How Humanoids Learn](https://claude.ai/artifact/JQucDQEgE64iZQAPvCbvv6)