AGV Warehouse Patents: Who Leads, Where the Gaps Are 2026
- Concentrated but not locked up. The top 5 assignees hold 30.2% of all 1,949 records in scope, and the top 10 hold 38.5% — leadership exists but there is room below it.
- Filing has cooled from its peak. After peaking at 198 records in 2021, filings fell to 141 by 2024, a -29% change over that span; 2025-2026 figures are still filling in as publications lag filing.
- Navigation and control dominate the claim space. G05D (control of non-electric variables) touches 58.1% of records and B25J (manipulators & robots) touches 26.8%, leaving positioning and data-processing classes comparatively open.
Filing growth compares 2021 (198 records) with 2024 (141) — 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 1,949 records in scope (CR5), not by the ranked leaders only.
What this dataset covers
This landscape draws on 1,949 published patent records filed between 2015 and mid-2026 that combine automated guided vehicle, autonomous mobile robot or automated pallet truck terminology with a specific operational capability — natural feature navigation, fleet traffic control, load presence detection, docking accuracy, safety laser scanning or obstacle avoidance. That intersection narrows the field to warehouse-relevant deployments rather than every mobile robotics filing on record.
Records are drawn from receiving offices spanning the United States, Europe, China, the WIPO PCT route, India and Germany, giving a reasonably global view of where applicants choose to seek protection rather than only where they are headquartered.
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Filing trend and technology mix
Two views of the same 1,949 records: how filing volume has moved year over year, and which IPC subclasses the claims actually sit in.
Filings rose to a 2021 peak, then eased
Annual filings climbed from 128 in 2017 to a peak of 198 in 2021, then declined to 141 by 2024 — a -29% move over that three-year window. 2025 and 2026 counts are shown for completeness but will keep rising as publication catches up with filing, so they should not be read as a real slowdown yet.
Control and manipulation classes dominate
G05D (control of non-electric variables) appears in 58.1% of records and B25J (manipulators & robots) in 26.8%, reflecting the core navigation-and-arm-control nature of the field. Positioning-related classes (G01S at 11.5%, G01C at 8.6%) and data-processing (G06F at 7.3%) are present but far less saturated, and adjacent classes like A47L (cleaning appliances) and B66F (jacks & lifting) show the technology's spread into specific vehicle types.
Shares are the percentage of the 1,949 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Automated Guided Vehicles in Warehouses with Eureka
This page is one run against one query. Ask Eureka your own question about automated guided vehicles in warehouses and every answer comes back with the patent numbers behind it.
Try EurekaRepresentative and most-cited filings
Autonomous mobile robot and operating method thereof (US20250123631A1)
An autonomous mobile robot with a movement module, detection module, control module and interaction module. The control module's determination unit checks whether an obstacle sits on or near a predetermined path using environment information, and its navigation unit then selects an obstacle-avoidance strategy — such as moving along a side path or stopping — based on the obstacle's type.Filed by Delta Electronics Int'l (Singapore), published 2025-04-17.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20070192910A1 | Companion robot for personal interaction | 992 |
| 2 | US20080027591A1 | Method and system for controlling a remote vehicle | 856 |
| 3 | US20110288684A1 | Mobile Robot System | 647 |
| 4 | US20070156286A1 | Autonomous Mobile Robot | 588 |
| 5 | US4777416A | Recharge docking system for mobile robot | 587 |
| 6 | US20140277691A1 | Automated warehousing using robotic forklifts | 517 |
| 7 | US20120197439A1 | Interfacing with a mobile telepresence robot | 470 |
| 8 | US5652489A | Mobile robot control system | 400 |
| 9 | US20120182392A1 | Mobile Human Interface Robot | 381 |
| 10 | US20070244610A1 | Autonomous coverage robot navigation system | 381 |
Citation counts accumulate over time, so older filings are structurally favoured; treat them as markers of influence on later work, not as a signal of what matters today.
Each row carries its publication number; clicking a row searches Eureka by that number.
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Browse MCP servers →What the numbers mean for a filing decision
Three findings that shape where a new application is likely to face crowded prior art versus open claim space.
Leadership is real but not exclusive
The top 5 assignees combined account for 30.2% of all records, and the top 10 for 38.5%. That leaves roughly six in ten filings spread across a long tail of single- or few-filing entrants — a structure where a well-drafted claim can still find room outside the leaders' core positions.
Volume has eased from its 2021 peak
Annual filings rose from 128 in 2017 to 198 in 2021, then fell to 141 by 2024. Because publication lags filing by roughly 18 months, the 2025-2026 numbers are still incomplete and should not be read as an accelerating decline.
Navigation control is the crowded core
G05D and B25J together cover the majority of records, meaning core path-control and manipulator claims sit on dense prior art. Positioning (G01S, G01C) and general data processing (G06F) are touched by far fewer records, which is where more specific claim language has a better chance of standing apart.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to automated guided vehicles in warehouses, with the prior art for and against each one.
Who is filing, and where the gaps sit
The ranked list spans 100 companies across robotics specialists, industrial equipment makers and diversified electronics groups, with filing activity concentrated in a handful of names and thinning quickly after that.
One filer sits well ahead of the field
The leading assignee's record count is more than ten times the tenth-place count of 28, indicating a long-running, deliberate filing program rather than incidental activity in this space.
A sharp drop after the leader
Filing volume falls quickly from the leader to fifth place, which sits at 36 records — a reminder that most of the concentration in the top 5 figure comes from one or two names, not an even cluster.
Co-filing is limited and name-specific
Only 10 co-assignee pairs appear in the dataset, with the strongest pairings clustered around one leading robotics filer and named individual inventors — suggesting most applicants file independently rather than through joint ventures.
| Assignee | Recent year | YoY |
|---|---|---|
| SICK AG | 1 | — |
| iRobot Corp | 0 | -100% |
| Jabil Inc | 0 | -100% |
| Boomerang Systems Inc | 0 | — |
| Huawei Technologies Co., Ltd. | 0 | — |
| Robart GmbH | 0 | — |
| Crown Equipment Corp | 0 | — |
| LingDong Technology (Beijing) 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 benchmarking or identifying a filing opportunity.
Check freedom-to-operate against the leader's claims
With one assignee holding 431 records, a design-around review of its core navigation and control claims is a reasonable first step before committing to a filing strategy in this space.
Run a claims comparison in EurekaWatch the under-claimed branches
Fleet traffic arbitration, docking calibration and load-presence sensing for irregular loads show lower filing density than the core control classes, making them worth a closer novelty search.
Explore white space in EurekaCommon questions about this landscape
This dataset identifies 1,949 published patent records filed between 2015 and mid-2026 that combine AGV, autonomous mobile robot or automated pallet truck terminology with a specific warehouse-relevant capability such as navigation, fleet control or obstacle avoidance. The true figure for the broader field is larger, since this search string deliberately narrows to operational capability terms rather than every mobile robotics filing. Because publication lags filing by roughly 18 months, the most recent one to two years will keep growing as more applications publish.
Filing is concentrated at the top: the five most active assignees together account for 30.2% of all 1,949 records, and the top ten account for 38.5%. One assignee leads clearly, with 431 records compared with 28 at tenth place, indicating a long-standing and deliberate filing program rather than a crowded, evenly matched field. Below the top ten, activity spreads across a long tail of companies with far fewer filings each.
Annual filings grew from 128 in 2017 to a peak of 198 in 2021, then eased to 141 by 2024 — a -29% change over that three-year window, which is the last period with complete data. Filing counts for 2025 and 2026 appear lower still, but that reflects publication lag rather than an actual drop in activity, since patent applications typically publish around 18 months after filing. Treat the 2021-2024 comparison as the reliable read on momentum, not the more recent partial years.
G05D, the control-of-non-electric-variables classification, touches 58.1% of the 1,949 records, and B25J, covering manipulators and robots, touches 26.8% — together these describe the bulk of navigation and motion-control claims in the field. Positioning-related classes such as G01S (radar, sonar and positioning) and G01C (distance and navigation) appear in far fewer records, at 11.5% and 8.6% respectively. That gap suggests core path-control claim space is dense, while specific sensor-fusion or positioning-accuracy claims have more room.
US20250123631A1, filed by Delta Electronics International (Singapore), describes an autonomous mobile robot whose control module determines whether an obstacle sits on or near a planned path and then selects an avoidance strategy — such as moving along a side path or stopping — based on the obstacle's type. It is a representative example of how current filings frame obstacle avoidance as a decision process tied to obstacle classification rather than simple distance-based stopping. Anyone drafting claims in this area should check how their avoidance logic differs in the decision criteria and strategy selection, since that is where this filing's specificity lies.
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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.