Robot Vacuum Navigation Patents: Who Leads, Where the Gaps Are 2026
- Filing activity peaked in 2024 at 17 families and has already begun to soften — this is a field past its first filing wave, not one still accelerating.
- China and the United States each account for 29 filings at the receiving office, putting the two jurisdictions in a dead heat rather than one dominating.
- Core cleaning-appliance claims (A47L) cover 84 of 95 records while AI-model and vision subclasses each sit in single digits, marking where claim density is thin.
What the patent record shows
Robot vacuum navigation and cleaning sits at the intersection of mechanical appliance design and mobile robotics control. The dataset behind this page covers 95 patent families published between 2015 and mid-2026, filtered to documents that combine navigation or mapping language with claim elements around obstacle recognition, carpet detection, dock-and-self-empty behaviour, coverage efficiency or mop control. That filter is deliberately narrow: it captures the functional claims that actually decide whether a product can ship, not every document that merely mentions a robot and a floor.
Filing activity rose through the late 2010s, reached a peak of 17 families in 2024, and shows signs of flattening rather than continuing to climb — the 2022 midpoint of 8 sits well below peak, and the most recent partial year should be read with the usual publication lag in mind. Because publication trails filing by roughly eighteen months, the 2025 and 2026 figures in the underlying trend are undercounts, not evidence of an actual slowdown yet.
Let an AI agent run this analysis on your own technology
Pick a task. Every answer cites the patents behind it.
Filing trends and technology composition
Two views of the same 95 families: how filing volume has moved year over year, and which IPC subclasses carry the claim weight.
A filing wave that has already crested
Volume climbed from zero in 2017 to a peak of 17 families in 2024, then eased — consistent with an early wave of foundational filings giving way to narrower, incremental claims as the core mechanics settle.
Claim weight concentrated in the appliance class
A47L (cleaning and washing appliances) appears in 84 of 95 records, with G05D (control of non-electric variables) a distant second at 26. Vision (G06V, G06T) and AI-model (G06N) subclasses each sit at single-digit counts, which is where the claim space is least occupied relative to how central those functions are to modern navigation.
Shares are the percentage of the 95 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Robot Vacuum Navigation and Cleaning with Eureka
This page is one run against one query. Ask Eureka your own question about robot vacuum navigation and cleaning and every answer comes back with the patent numbers behind it.
Try EurekaA representative filing
Cleaning robot, control method for same, and cleaning robot system
A cleaning robot with a housing, a moving module and a control module that drives the robot between a work execution position and a maintenance position. A wiping unit contacts the working surface directly or indirectly during cleaning, and the robot switches between a work execution state and a maintenance state as it transitions to and from its maintenance position — covering the mechanical basis for automated dock-and-maintenance behaviour.Filed by Positec Power Tools (Suzhou); published 2021-07-29.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20220026920A1 | Light weight and real time slam for robots | 265 |
| 2 | KR1020060081131A | Robot Cleaner and Cleaning Method using Robot Cleaner | 84 |
| 3 | US20200077858A1 | Base station and cleaning robot system | 78 |
| 4 | CN111035327A | 清洁机器人、地毯检测方法及计算机可读存储介质 | 49 |
| 5 | US20200097012A1 | Cleaning robot and method for performing task thereof | 38 |
| 6 | JP1992328607A | Cleaning robot | 35 |
| 7 | EP3542695A1 | Base station and cleaning robot system | 31 |
| 8 | US20210228050A1 | Cleaning robot, control method for same, and cleaning robot system | 24 |
| 9 | US20210149411A1 | Method, apparatus and storage medium for detecting small obstacles | 22 |
| 10 | KR100711995B1 | Robot Cleaner and Cleaning Method using Robot Cleaner | 21 |
Citation counts favour older records simply because they have had more years to accumulate citations within the searched corpus — read them as a signal of influence on the field, not of 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.
Put your own technology through the same analysis
Eureka on the web
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 →MCP server & REST API
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 →What the data means for filing strategy
Three patterns stand out once family counts, IPC composition and receiving-office data are read together.
The first wave has crested
Volume rose from nothing in 2017 to a peak of 17 families in 2024 before easing. That pattern is typical of a field where the core mechanical and navigation claims have already been staked out, and later filers are narrowing rather than pioneering.
No single jurisdiction dominates filing
China and the United States each show 29 filings at the receiving office, with Europe, South Korea, Singapore and India well behind. Freedom-to-operate work has to clear both jurisdictions independently rather than treating one as a proxy for the other.
Appliance mechanics are the densest prior art
A47L claims — the physical cleaning appliance itself — appear in the large majority of records. G05D control claims are the next most common but at less than a third of the volume, and vision, AI and manipulator subclasses are all in single digits.
Filing is mostly solo, with a few dense clusters
Only 10 co-assignee pairs appear across the dataset, and they cluster around a small number of named inventors rather than being spread evenly, suggesting most applicants file independently rather than through joint development arrangements.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to robot vacuum navigation and cleaning, with the prior art for and against each one.
Assignee landscape and momentum
Filing activity spans large appliance makers, robotics specialists and a long tail of individual inventors and smaller entities, with recent-year momentum concentrated in only a few names.
Recent activity is thin across the board
In the most recent year captured, Samsung Electronics shows a single filing and most other tracked assignees, including previously active filers, show none. That is consistent with a field mid-pause rather than one seeing an active new entrant surge.
A dense individual-inventor cluster
The strongest co-assignee pairing in the dataset — Brian Highfill and Ali Ebrahimi Afrouzi — recurs across five shared filings, with related pairings involving other Ebrahimi Afrouzi and Fath names close behind, pointing to a tight-knit filing group rather than a single corporate lab.
Some established filers have gone quiet
At least one previously active assignee shows a full year-over-year drop to zero in the latest year. A pause like this can mean a filing program has matured and moved to maintenance, or that activity has shifted to trade secret or product iteration instead of new claims.
| Assignee | Recent year | YoY |
|---|---|---|
| Samsung Electronics Co., Ltd. (Korea) | 1 | — |
| Yunjing Intelligent Innovation (Shenzhen) Co., Ltd. | 0 | — |
| Yunjing Intelligent (Shenzhen) Co., Ltd. | 0 | — |
| HIGHFILL BRIAN | 0 | — |
| EBRAHIMI AFROUZI ALI | 0 | — |
| Beijing Roborock Innovation Technology Co., Ltd. | 0 | -100% |
| LG Electronics Inc. | 0 | — |
| Positec Power Tools (Suzhou) Co., Ltd. | 0 | — |
Where to take this analysis
The dataset points to specific next steps depending on whether the goal is freedom-to-operate, portfolio strategy, or spotting acquisition targets.
Check freedom-to-operate against dual anchors
With China and the US each holding 29 filings, a clearance search limited to one jurisdiction misses roughly half the relevant claim space. Run both in parallel rather than sequentially.
Explore in EurekaTarget the thin IPC subclasses for new filings
Vision, AI-model and manipulator subclasses each sit in single digits against 84 A47L records. Claims combining navigation software with the physical cleaning mechanism are less contested than pure appliance mechanics.
Explore in EurekaWatch the quiet incumbents
A previously active assignee showing a full year-over-year drop to zero is worth monitoring for either a strategy shift or a forthcoming filing catch-up once the publication lag clears.
Explore in EurekaCommon questions about this landscape
The dataset shows filing concentrated among a mix of established appliance and robotics companies alongside a cluster of individually named inventors, rather than one clear dominant holder. Recent-year momentum has been thin across nearly every tracked assignee, with only Samsung Electronics showing a filing in the latest captured year. Because publication lags filing by around eighteen months, the true current leader in newly filed (but not yet published) applications cannot be read directly from this data — a live monitoring search is needed to catch up-to-date filings.
Carpet detection claims are one of the specific functional elements this dataset was filtered on, and they appear across a subset of the 95 tracked families rather than as a dominant single category. One highly cited record, CN111035327A, focuses specifically on cleaning robots and carpet detection methods with a computer-readable storage medium claim. Because carpet detection sits inside the broader A47L cleaning-appliance class that covers 84 of 95 records, most claims in this area are drafted as part of a larger cleaning-robot system rather than as standalone carpet-sensing patents.
Yes — the IPC composition shows heavy concentration in A47L (84 of 95 records) and comparatively thin coverage in G06V, G06T and G06N, the vision and AI-model subclasses, each in single digits. That gap matters because modern navigation increasingly depends on machine-learning-based scene understanding, not just mechanical sensing, so claims that tie a specific AI navigation method to the physical cleaning mechanism face less prior art. Multi-floor map persistence and fleet coordination across multiple robots are two other functional areas that show up rarely relative to how commercially important they are.
The two jurisdictions are essentially tied at the receiving-office level, with 29 filings each, ahead of Europe at 12, South Korea and Singapore at 6 apiece, and India at 4. This near-parity means a competitive or freedom-to-operate review that only checks one country will miss roughly half the relevant filings. It also suggests that companies active in this field are treating both markets as core rather than treating either as secondary.
Filing volume rose from zero in 2017 to a peak of 17 families in 2024, with the 2022 midpoint at 8 — a pattern of growth that has flattened rather than one still accelerating. The most recent one to two years in any patent trend are understated because publication trails filing by roughly eighteen months, so the apparent slowdown after 2024 should be treated cautiously until later data fills in. Combined with several assignees showing zero filings in the latest tracked year, the evidence points to a field that has passed its first filing wave and is now in a narrower, incremental phase.
Research Robot Vacuum Navigation and Cleaning in depth with Eureka
Go past this page: query the whole robot vacuum navigation and cleaning 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.