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The agent works the prompt against patents and technical literature, citing every source.
Run your analysis now →Filing growth compares 2021 (4 records) with 2024 (1) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field. Top-5 share is the combined record count of the five largest assignees divided by all 48 records in scope (CR5), not by the ranked leaders only.
This dataset tracks published patent families at the intersection of humanoid, bipedal and legged robots with visual SLAM, localization and mapping, and terrain-aware navigation, filtered to the IPC classes covering control of non-electric variables (G05D1/02), navigation and gyroscopes (G01C21/16) and manipulator/robot structure (B25J9/16). It spans filings from 2015 through the 2026 data cut-off, with 48 total records forming the basis of every ranking and chart on this page.
Publication typically lags filing by around 18 months, so the 2025 and 2026 counts in the trend chart understate actual filing activity in those years. Treat the most recent two data points as a floor, not a ceiling.
Pick a task. Every answer cites the patents behind it.
Two views of the same 48-family dataset: how filing activity has moved year over year, and which IPC subclasses carry the claim density.
Filings rose from 3 in 2017 to a peak of 12 in 2025, passing through 7 at the 2022 midpoint. The 2026 figure of 2 is partial by definition, but even adjusting for lag, the shape is a plateau rather than sustained growth — this is a field with an established filing base, not one in a land-grab phase.
B25J (manipulators & robots, 25 records) and G05D (control of non-electric variables, 24 records) dominate, with B62D (motor vehicles & steering, 13) close behind. Navigation-specific classes — G01C (6), G01S (5) and G06T (3) — are comparatively thin, suggesting perception and mapping claims are less crowded than the mechanical and control layers built around them.
Shares are the percentage of the 48 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
This page is one run against one query. Ask Eureka your own question about humanoid robot slam and navigation and every answer comes back with the patent numbers behind it.
Try EurekaThe invention relates generally to a mobile robot, e.g. a humanoid robot, configured to provide reality capture and metrology grade geometric measurement, e.g. to generally support infrastructure surveillance and/or to support workflows in the field of metrology. Aspects of the mobile robot, inter alia, relate to providing increased accuracy of metrology grade devices to overcome deficiencies in mobile reality capture. On the other hand, benefits of mobility provided by mobile robots are transformed to the field of metrology while maintaining metrology grade accuracy.Filed by Hexagon Technology Center GmbH, published 2024-06-13.


| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20210387346A1 | Humanoid robot for performing maneuvers like humans | 53 |
| 2 | CN107085422A | 一种基于Xtion设备的多功能六足机器人的远程控制系统 | 41 |
| 3 | US20200333790A1 | Control device, and control method, program, and mobile body | 20 |
| 4 | US20200387162A1 | Control device and control method, program, and mobile object | 15 |
| 5 | WO2019131198A1 | Control device, control method, program, and mobile body | 14 |
| 6 | WO2019111701A1 | Control device, control method, program, and moving body | 9 |
| 7 | CN120558242A | 一种人形机器人惯性导航与视觉融合定位方法、装置及设备 | 8 |
| 8 | WO2019098082A1 | Control device, control method, program, and moving body | 7 |
| 9 | US11592829B2 | Control device and control method, program, and mobile object | 6 |
| 10 | CN118330672A | 一种足式机器人隧道三维测图方法及装置 | 4 |
Citation counts reflect influence within this searched corpus and skew toward older filings; they are not a proxy for current commercial relevance.
Patent titles are shown in the language they were filed in, not translated, so that each record stays verifiable against the original filing — a translated title will not match in Eureka or in any national register. Each row carries its publication number; clicking a row searches Eureka by that number.
When you want the answer in the next five minutes.
The agent works the prompt against patents and technical literature, citing every source.
Run your analysis now →When it has to run inside your own pipeline.
Patent search, landscape analysis and assignee resolution as MCP tools. Drop them into any agent framework, or call REST directly.
Browse MCP servers →Three read-throughs from the filing trend, the IPC split and the citation table, translated into decisions rather than descriptions.
A rise from 3 filings in 2017 to a 2025 peak of 12, passing through 7 at the midpoint year, describes a field that built a filing base over a decade rather than one now in rapid expansion. Treat any 2025–2026 dip as partly a lag artefact, not proof of retreat.
The two largest IPC subclasses cover manipulator/robot structure and non-electric control — the mechanical and control-loop layers of a humanoid platform. Navigation-specific classes trail well behind, which is where the claim space is comparatively open.
The most-cited records in this corpus are earlier filings on humanoid maneuver control and mobile-body control devices. High citation counts here signal foundational influence within the searched set, not that these are the filings most relevant to today's design decisions.
Only one co-assignee pair rises above single-filing frequency, and it links a university to a state rail operator rather than two robotics firms. Cross-assignee collaboration is not yet a defining feature of this landscape.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to humanoid robot slam and navigation, with the prior art for and against each one.
No assignee in the recent-momentum table shows positive year-on-year growth in the latest period, and several show declines from a low base — a sign this landscape has not yet consolidated around a clear leader.
With one filing in the latest tracked year against a prior-year decline of 83%, this assignee remains active but at a fraction of earlier output — worth monitoring rather than treating as a bellwether.
Neither shows filings in the most recent tracked year, though zero does not mean exit — it may reflect the publication lag on 2025–2026 filings rather than a strategic withdrawal.
A full year-on-year decline to zero filings, despite holding the representative record in this dataset (WO2024120607A1), suggests the metrology-robotics push may have moved to a different filing cycle or jurisdiction not yet visible in this window.
| Assignee | Recent year | YoY |
|---|---|---|
| Digital Artificial Intelligence Corporation | 1 | -83% |
| Sony Group Corporation | 0 | — |
| Hexagon Technology Center GmbH | 0 | -100% |
| Tencent Technology (Shenzhen) Company Limited | 0 | — |
| Hexagon Robotics Limited | 0 | — |
| SoftBank Robotics Europe | 0 | — |
| Shenzhen University | 0 | — |
| Zhejiang University | 0 | — |
The trend and composition data point to specific next steps depending on whether the goal is freedom-to-operate, whitespace filing, or competitive tracking.
The five highest-cited filings in this corpus, led by a humanoid maneuver-control patent at 53 citations, define the prior art baseline that any new mapping or control claim will be measured against.
Run a freedom-to-operate check in EurekaG01C, G01S and G06T carry far fewer records than B25J or G05D, which is where a narrowly drafted first claim is more likely to clear a clean prior-art search.
Draft and stress-test claims in EurekaThis dataset identifies 48 published patent families matching humanoid, bipedal or legged robot terms combined with visual SLAM, localization and mapping, or terrain-aware navigation language, filtered to the relevant IPC classes. That is a modest, specialized corpus rather than a sprawling one, which is consistent with a technology area still built around a handful of active filers. The true figure filed but not yet published is higher, since publication lags filing by roughly 18 months.
No single assignee shows sustained positive filing momentum in the most recent tracked year; the recent-momentum data shows flat or declining activity across every tracked name, including large firms like Sony and Tencent's Shenzhen entity. Hexagon Technology Center holds the representative filing in this dataset, a wheeled/tracked articulated-leg humanoid design, but its own filing rate has dropped to zero year-on-year. This points to a field without an entrenched leader, where competitive position can still shift.
In this corpus, IPC class G01C (distance, navigation and gyroscopes) and G01S (radar, sonar and positioning) carry far fewer records than B25J (manipulator/robot structure) or G05D (non-electric control), meaning perception and mapping-specific claims are comparatively less crowded than mechanical and control-loop claims. A SLAM-specific claim typically covers sensor fusion, loop closure or localization algorithms, while navigation claims here more often cover path planning or terrain-response control built on top of that perception layer. Drafting in the thinner classes carries a better chance of a clean prior-art position, though it also means less established precedent to build on.
The filing trend in this dataset rose from 3 records in 2017 to a peak of 12 in 2025, passing through 7 at the 2022 midpoint — a pattern of steady build-up followed by a plateau rather than acceleration. The 2026 figure of 2 is partial and understated because of publication lag, so it should not be read as a sudden drop-off. Taken together, the shape suggests a maturing filing base rather than an emerging land-grab.
WO2024120607A1, filed by Hexagon Technology Center GmbH and published 2024-06-13, covers a humanoid-form mobile robot with articulated legs fitted with wheels or tracks, aimed at metrology-grade reality capture and infrastructure surveillance. Its scope centres on the wheel/track-leg hybrid locomotion structure paired with high-accuracy measurement capability, not on visual SLAM algorithms or generic terrain navigation. Designs using purely legged locomotion without the metrology-measurement framing, or using different sensor fusion approaches for localization, sit outside its core claim scope, though a full claim chart is needed before relying on that as a legal conclusion.
Go past this page: query the whole humanoid robot slam and navigation corpus yourself, in your own scope.
Every answer comes back with patent numbers you can open.
Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company's registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.