Pallet-Handling Robot Patents: Leaders & Filing Trends 2026
A data-backed look at the autonomous pallet-handling robot and robotic forklift patent landscape: who leads filings, how the technology composition breaks down across conveying, lifting and navigation classes, and where
Filing growth = 2021 (34 records) → 2024 (46); 2024 is the last year we treat as complete. Top-5 share = the 5 largest assignees ÷ all 361 records in scope (CR5), not the ranked leaders only.
What this landscape covers
This landscape maps patent filings describing autonomous pallet trucks, robotic forklifts and pallet-handling mobile robots — machines that combine a mobile chassis or automated guided vehicle base with a lifting or fork mechanism to move palletised loads without a human driver. The search string captures both title/abstract language naming these machines directly and claim language pairing pallet handling, transport, lifting or loading actions with mobile robot, AGV or robotic forklift terminology, so the scope includes claims written from either the mechanical-handling side or the autonomy side of the problem.
Coverage runs from 2015-01-01 through the 2026-08-31 data cut-off, spanning 361 published records. Because publication typically lags filing by around 18 months, the most recent one to two years understate actual filing activity and should be read as a floor, not a ceiling.
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Filing trend and technology composition
Two views of the same 361-record dataset: how filing volume has moved year over year, and which IPC subclasses carry the claim weight.
Filing trend, 2017–2026
Filings climbed from 19 in 2017 to a peak of 66 in 2020, cooled, then resumed growth — up 35% from 34 filings in 2021 to 46 in 2024, the last year that can be treated as complete given publication lag. 2025 and 2026 figures will fill in further as pending applications publish.
Publication lags filing by roughly 18 months, so 2025 onwards are still filling in. Growth rates on this page therefore end at 2024; running them to the last bar would understate the field.
Technology composition by IPC subclass
B65G (conveying and material handling) and B66F (jacks and lifting devices) each touch roughly a third of the 361 records, reflecting the mechanical core of the problem. G05D (control of non-electric variables) and G06Q (business/commerce data processing) follow closely, showing how much of the claim space is now written around autonomy logic and fleet/order management rather than the fork mechanism alone. Navigation-specific classes G01C and G01S sit further down, suggesting sensing and localisation claims are comparatively less crowded.
Shares are the percentage of the 361 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Mobile Robots & AMRs: Autonomous Pallet-Handling Robot Patent Landscape with Eureka
This page is one run against one query. Ask Eureka your own question about mobile robots & amrs: autonomous pallet-handling robot patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaRepresentative filing and most-cited prior art
Pallet-handling robot and warehousing system (WO2026081333A1)
The application describes a pallet-handling robot built around a fork assembly, a load platform with a lift-drive mechanism, and a mother-vehicle unit connected to the load platform by suspension straps, with the mother vehicle travelling along rails mounted on warehouse racking. Clamping features on the load platform engage the racking at the target storage location to stabilise the platform while the fork lifts or lowers the pallet, aimed at improving fork-handling stability and operating safety.Abstract translated from the original Chinese filing.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20150073589A1 | Autonomous mobile picking | 542 |
| 2 | US20090152391A1 | Multibody aircrane | 400 |
| 3 | US4894908A | Method for automated assembly of assemblies such as automotive assemblies and system utilizing same | 217 |
| 4 | US20170158430A1 | Automatic warehouse system | 173 |
| 5 | US20180304468A1 | Methods and Systems for Detecting, Recognizing, and Localizing Pallets | 162 |
| 6 | US9733646B1 | Heterogeneous fleet of robots for collaborative object processing | 158 |
| 7 | US6705523B1 | System and method for delivering supplies to a production line | 129 |
| 8 | WO2015035300A1 | Autonomous mobile picking | 123 |
| 9 | US20030028323A1 | Material handling systems with high frequency radio location devices | 118 |
| 10 | US9550624B2 | Autonomous mobile picking | 92 |
Citation counts are drawn from a searched corpus and skew toward older filings that have had more time to accumulate citations — treat them as a signal of influence on the field, not a ranking of current technical importance.
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 or freedom-to-operate decision
Four figures worth weighing before deciding where to file, litigate or license in this field.
Leadership is real but not a monopoly
The leader holds 29 records and the fifth-ranked assignee holds 11 — a real gap, but nowhere near dominant control of the field. With the top 10 combined at 37.1% of all 361 records, the majority of filing activity sits with a long tail of smaller and single-filing entrants across the 100 ranked companies.
Filing activity is still climbing, not cooling
After a 2020 peak of 66 filings, volume growth resumed: 34 filings in 2021 rose to 46 in 2024, the most recent year that can be read as complete. Do not mistake the lower 2025-2026 counts for a slowdown — those years are still filling in as applications publish.
Mechanical handling claims still outweigh pure navigation claims
B65G and B66F, the conveying and lifting classes, each cover roughly a third of the 361 records, ahead of navigation-heavy classes like G01C (11.6%) and G01S (5.3%). That gap suggests the fork and lift mechanics remain more heavily claimed than the sensing stack, even as G05D control claims (29.6%) show autonomy logic is well represented.
US and EPO dominate, WIPO route is significant
United States filings (115) lead the receiving-office count, with Europe (77) and WIPO/PCT (53) also substantial, followed by Japan, Canada and Germany. That spread points to a field being protected across the major logistics markets rather than concentrated in one jurisdiction.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to mobile robots & amrs: autonomous pallet-handling robot patent landscape, with the prior art for and against each one.
| Assignee | Co-assignee | Shared families |
|---|---|---|
| Lineage Logistics LLC | ECKMAN CHRISTOPHER FRANK | 13 |
| Lineage Logistics LLC | WALET DANIEL | 11 |
| Lineage Logistics LLC | BAIJENS FRANK | 11 |
| WALET DANIEL | BAIJENS FRANK | 11 |
| ECKMAN CHRISTOPHER FRANK | WALET DANIEL | 10 |
| ECKMAN CHRISTOPHER FRANK | BAIJENS FRANK | 10 |
| Toshiba Corporation | Toshiba Infrastructure Systems & Solutions Corporation | 3 |
| Lineage Logistics LLC | ECKMAN CHRISTOPHER FRANK SAN FRANCISCO | 1 |
Ten co-assignee pairs appear in the dataset. The strongest pairing links a single corporate assignee to several individually named co-inventors across multiple filings, a pattern typical of an in-house engineering team filing jointly with named inventors rather than cross-company joint ventures.
Where to take this analysis
The dataset points to a few concrete next steps depending on what decision you're making.
Map freedom-to-operate against the leadership cluster
With 37.1% of records held by the top 10 assignees, a targeted claim-chart review of that group's most-cited families is the fastest way to check for blocking art before committing engineering resources to a similar fork or lift design.
Explore assignee families in EurekaWatch the navigation and sensing classes for white space
G01C and G01S together cover a smaller share of records than the mechanical classes, which may indicate room to file narrowly around localisation and sensing approaches rather than the fork mechanism itself.
Run a white-space search in EurekaTrack 2024-2026 filings as they continue to publish
Because publication lags filing by roughly 18 months, re-running this trend in six to twelve months will reveal a fuller picture of 2025 and 2026 activity than is visible today.
Set a filing alert in EurekaCommon questions about this landscape
The dataset ranks 100 assignees by record count, with the leader holding 29 records and the fifth-ranked company holding 11. The top 5 combined account for 24.4% of all 361 records in scope, and the top 10 account for 37.1%, meaning the field has a visible leadership cluster but a majority of filings still come from a long tail of smaller filers. This is not a market dominated by one or two companies; it is closer to a moderately concentrated field with room for new entrants to build a defensible position.
Filing activity grew 35% from 34 records in 2021 to 46 records in 2024, the last year that can be treated as complete given typical publication lag. An earlier peak of 66 filings occurred in 2020. The lower counts shown for 2025 and 2026 are an artefact of publication lag — roughly 18 months typically pass between filing and publication — rather than evidence of a genuine slowdown, so those most recent years should not be read as a decline.
Conveying and material-handling claims (IPC class B65G) appear in 39.3% of the 361 records, and lifting-device claims (B66F) appear in 32.4%, making these the two most heavily occupied technical areas. Control-system claims (G05D, 29.6%) and business/commerce data-processing claims (G06Q, 26.6%) are also substantial, reflecting how much of the modern claim space covers autonomy logic and fleet management rather than the mechanical fork alone. Navigation-specific classes such as G01C and G01S carry a smaller share of records.
The United States leads as a receiving office with 115 records, followed by the European Patent Office with 77 and the WIPO/PCT route with 53. Japan, Canada and Germany follow with smaller but meaningful counts. The spread across these offices indicates that companies active in this space are protecting inventions across the major logistics and manufacturing markets rather than filing in a single home jurisdiction.
Start by reviewing the most-cited records and the leadership cluster's families for potential freedom-to-operate conflicts, since 37.1% of all 361 records sit with just the top 10 assignees. Then check the technology composition: mechanical handling classes are the most crowded, while navigation and sensing classes carry comparatively fewer records and may offer more room for narrowly drafted claims. Because recent filing years are understated by publication lag, treat any 2025-2026 gap in the trend as incomplete data rather than a genuine drop in competitive activity.
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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.