Service Robots Patents: Top Companies & Filing Trends 2026
- Concentrated but not locked up. the top five assignees hold 190 of 646 records in scope (29.4%), and the top ten hold 272 (42.1%) — leaving a long tail of single- and few-filing entrants.
- Filing has cooled from its peak. activity peaked in 2023 at 94 records, and the complete-year comparison shows 2021's 63 filings falling to 44 by 2024, a 30% decline over that span.
- Navigation and manipulation dominate the classes. G05D (control of non-electric variables) and B25J (manipulators & robots) appear in 39.6% and 33.6% of records respectively, far ahead of AI-model classes like G06N at 8.7%.
Filing growth compares 2021 (63 records) with 2024 (44) — 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 646 records in scope (CR5), not by the ranked leaders only.
What this landscape covers
This landscape draws on 646 published patent records filed between 2015 and 2026 that combine service-robot terminology with core enabling functions: position estimation, motion trajectory, environment sensing, actuator control, autonomous navigation and robotic actuation. The search string requires both a service-robot framing and at least one of these technical mechanisms, which narrows the set to records that describe how a robot senses, plans or moves rather than every mention of robotics in general.
Publication naturally lags filing by roughly eighteen months, so the most recent one or two years in any trend line will look smaller than they eventually become once the backlog clears. Family-level counting, used throughout this ranking, reduces the distortion that comes from aggressive continuation filing or filing the same invention across multiple jurisdictions.
Filing trend and technology composition
Two views of the same 646 records: how filing volume has moved year over year, and which IPC subclasses carry the claim density.
Filing trend, 2017–2026
Filings rose from 53 in 2017 to a peak of 94 in 2023, then declined across the last complete comparison window — 63 in 2021 down to 44 in 2024, a 30% drop. Treat 2025 and 2026 figures as provisional given publication lag.
IPC subclass composition
G05D and B25J anchor the field, each appearing in roughly a third or more of records, while G06N (AI-based computing) and G06T (image processing) sit under 10% — evidence that navigation and physical manipulation claims still outweigh AI-model claims in this corpus. Shares are calculated against all 646 records and sum to more than 100% because records can carry multiple classes.
Shares are the percentage of the 646 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Service Robots Patent Landscape with Eureka
This page is one run against one query. Ask Eureka your own question about service robots patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaRepresentative filing and most-cited records
Method for Detecting Physical Forbidden Zone and Global Relocating of Service Robot
The filing (US20230244239A1, assigned to Longto (Suzhou) Co., Ltd, published 2023-08-03) presets an identification marker at the edge of a physical zone a service robot must not enter, then constantly checks for that marker during operation. On detecting it, the robot confirms its position and heading relative to the marker and adjusts its motion trajectory accordingly — a low-cost approach to boundary enforcement and relocalisation that avoids dependence on a pre-built map.Abstract condensed from the published filing.


| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20220066456A1 | Obstacle recognition method for autonomous robots | 763 |
| 2 | US20210089040A1 | Obstacle recognition method for autonomous robots | 457 |
| 3 | US20160170996A1 | Crowd-based scores for experiences from measurements of affective response | 333 |
| 4 | US20160300252A1 | Collection of Measurements of Affective Response for Generation of Crowd-Based Results | 320 |
| 5 | US20160224803A1 | Privacy-guided disclosure of crowd-based scores computed based on measurements of affective response | 316 |
| 6 | US20160134932A1 | Camera System API For Third-Party Integrations | 271 |
| 7 | US20220026920A1 | Light weight and real time slam for robots | 267 |
| 8 | US11199853B1 | Versatile mobile platform | 252 |
| 9 | US20220187841A1 | Method of lightweight simultaneous localization and mapping performed on a real-time computing and battery op… | 206 |
| 10 | US11037320B1 | Method for estimating distance using point measurement and color depth | 166 |
Citation counts reflect influence within this searched corpus and skew toward older filings; they are not a measure of current commercial importance.
Each row carries its publication number; clicking a row searches Eureka by that number.
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Four patterns stand out once the raw counts are set against each other.
The top of the field is real but not exclusive
The five leading assignees account for 190 of 646 records, and the top ten for 272 — a meaningful concentration, but well short of a closed field. A large share of the remaining assignees appear only once or twice in the ranking.
Volume has passed its peak, on the complete-year data
The last fully comparable window shows filings falling from 63 in 2021 to 44 in 2024, a 30% decline. Because publication lags filing by about eighteen months, 2025-2026 figures should not yet be read as a continuation of that decline.
Control and manipulation outweigh AI-model claims
G05D (non-electric variable control) and B25J (manipulators & robots) lead the class breakdown, each present in over a third of records. G06N, the AI-model class, trails at 8.7% — claim activity is still concentrated on the mechanical and control layer rather than the learning layer.
The US and Europe carry most of the volume
The United States (271) and EPO (104) are the largest receiving offices tracked, with India (70), WIPO/PCT (54), China (37) and Germany (27) making up the remainder. This spread suggests most applicants are prioritising US and European protection before broader PCT filing.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to service robots patent landscape, with the prior art for and against each one.
Who is filing, and where they are pulling back
The assignee ranking covers 100 companies counted in records — the full set the data endpoint returns, not a curated top list. Recent-year momentum data shows several previously active filers, including some of the largest, recording zero filings in the latest tracked year, which is consistent with the publication-lag effect rather than a sudden exit.
One assignee leads by a clear margin
The top-ranked assignee holds 67 records, well ahead of fifth place at 22 and tenth place at 13 — a steep drop-off that signals one applicant has built a substantially deeper portfolio than any single competitor.
Co-assignment is limited and clustered
Only ten co-assignee pairs appear in the dataset, with the strongest pairing recorded 15 times. This points to a field where most filing is done by single entities rather than joint ventures or cross-licensed development.
Several established filers show no recent activity
Multiple assignees that appear high in the historical ranking, including large diversified technology firms, show zero filings in the latest tracked year. Given the roughly eighteen-month publication lag, this likely reflects filings still working through the pipeline rather than a confirmed halt.
| Assignee | Recent year | YoY |
|---|---|---|
| Seegrid Corp | 0 | -100% |
| Google LLC | 0 | — |
| ARISTOCRAT TECHNOLOGIES INC | 0 | -100% |
| EBRAHIMI AFROUZI ALI | 0 | -100% |
| Bar-Ilan University | 0 | — |
| Robert Bosch GmbH | 0 | — |
| iRobot Corp | 0 | — |
| HIGHFILL BRIAN | 0 | -100% |
Where to take this next
The landscape points to specific next steps depending on whether the goal is freedom-to-operate, portfolio benchmarking or identifying a filing gap.
Check freedom-to-operate against the leader's portfolio
With one assignee holding 67 records against a field where fifth place sits at 22, any new filing in navigation or actuator control should be checked specifically against that leader's claim set before drafting.
Explore assignee portfolios in Eureka →Test claims in the under-10% classes
G06N, G06T and H04L all sit under 10% of the 646 records despite being adjacent to the core G05D and B25J activity — a first claim combining service-robot navigation with one of these lighter-claimed functions is worth drafting and searching before committing.
Run a white-space search in Eureka →Common questions about the service robots patent landscape
One assignee leads the ranking with 67 records, noticeably ahead of the fifth-placed filer at 22 and the tenth-placed filer at 13. The top five assignees together account for 190 of the 646 records in scope, or 29.4%, and the top ten account for 272, or 42.1%. That leaves well over half the field spread across a long tail of assignees with only one or a handful of filings each, so the space is concentrated at the top but not closed to new entrants.
Filing volume peaked in 2023 at 94 records and, on the last fully comparable window, fell from 63 filings in 2021 to 44 in 2024 — a 30% decline. Because patent publication typically lags filing by about eighteen months, the 2025 and 2026 figures in any dataset will look artificially low and should not yet be read as confirmation the decline is continuing. The safest reading is that filing has passed its 2023 peak and is normalising, not that the technology area is losing investment.
The two largest IPC subclasses are G05D, control of non-electric variables, at 39.6% of the 646 records, and B25J, manipulators and robots, at 33.6%. Navigation-related G01C and data-processing G06F both sit in the low-to-mid teens, while AI-model class G06N and image-processing class G06T each account for under 10%. Because a single record can carry several classes, these shares add up to more than 100% and should be read as an indicator of where claim density sits, not as mutually exclusive buckets.
The lightest-claimed adjacent branches in this dataset are the classes sitting below 10% of the 646 records: G06N (AI-model-based computing), G06T (image data processing) and H04L (digital information transmission), all of which are technically adjacent to the dominant G05D and B25J control and manipulation claims. A first claim that ties an AI-based planning or fleet-telemetry function directly to a physical navigation or actuator-control step is more likely to land in less-crowded prior art than a pure navigation or manipulator claim on its own. This should be treated as a starting hypothesis for a targeted prior-art search, not a guarantee of allowability.
The United States leads with 271 tracked filings, followed by the European Patent Office at 104, India at 70, the WIPO/PCT route at 54, China at 37 and Germany at 27. This distribution suggests applicants are prioritising US and European protection directly, with PCT used as a secondary or bridging route rather than the primary filing strategy. Anyone benchmarking regional competitive activity should weight the US and EPO figures most heavily given their volume relative to the other offices tracked.
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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.