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Run your analysis now →https://www.patsnap.com/resources/blog/rd-blog/automated-guided-vehicle-simulation-and-modeling-patent-landscape/ · Patsnap · data cut-off 2026-07-31 · downloaded from the live page
Robotics & Automation · Patent LandscapeAutomated Guided Vehicle Simulation and Modeling Patents
- China dominates the filing office count by a wide margin, with 34 of 45 families receiving filings there against single-digit counts everywhere else, including the US and Europe.
- Filing activity peaked in 2025 at 15 families after a flat 2022 midpoint of 11, suggesting the field accelerated late rather than growing steadily — watch whether 2026's partial count catches up.
- Co-assignment is almost nonexistent, with only two university-industry pairs across the whole dataset, pointing to mostly solo filing strategies rather than joint R&D programmes.
45
Published Records
27%
Top-5 Share of All Records
0%
Filing Growth 2021→2024
CN
Leading Jurisdiction
Filing growth compares 2021 (4 records) with 2024 (4) — 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 45 records in scope (CR5), not by the ranked leaders only.
Published byPatsnap Research··6 min readSourced from Patsnap Eureka
Overview
What this landscape covers
This dataset tracks patent families at the intersection of automated guided vehicle (AGV) operation and simulation techniques — fleet simulation, traffic simulation, digital twin modelling, and layout simulation — filtered to G05D1/02, G06F30, and G06Q10 classifications. It captures how manufacturers and research institutions are using virtual models to plan, schedule, and validate AGV deployments before or alongside physical operation. The scope excludes general AGV hardware and navigation patents that do not reference a simulation, twin, or modelling claim.
Coverage runs from 2015-01-01 through the 2026-07-31 cut-off, with 45 published records forming 45 distinct families — a one-to-one ratio that indicates little continuation filing or multi-jurisdiction duplication in this niche. Publication normally lags filing by around 18 months, so the 2026 count in particular should be read as a floor, not a ceiling.
Filing activity and technology composition
Source: Patsnap Eureka. Assignee ranking and totals. Derived from a Patsnap search on Automated Guided Vehicle Simulation and Modeling covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
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The Data
Filing trends and technology composition
Two views of the same 45-family dataset: how filing volume has moved year over year, and which IPC subclasses carry the claim weight.
Filing trend, 2017–2026
Filings sat at zero in 2017 and built slowly, reaching a midpoint of 11 in 2022 before peaking at 15 in 2025. The 2026 figure of 4 is partial by definition given the cut-off date, so the apparent drop should not yet be read as a decline.
IPC subclass distribution
G06Q (business, commerce & admin data processing) leads with 33 of the records, ahead of G06F (18) and G06N (14, AI-related computing). Core motion-control classes G05B and G05D sit lower at 8 and 7 respectively — a sign that most claims in this dataset are framed around scheduling, data processing, and modelling logic rather than the vehicle's control loop itself.
Shares are the percentage of the 45 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Source: Patsnap Eureka. Filing trend and technology composition. Derived from a Patsnap search on Automated Guided Vehicle Simulation and Modeling covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.
Go deeper on Automated Guided Vehicle Simulation and Modeling with Eureka
This page is one run against one query. Ask Eureka your own question about automated guided vehicle simulation and modeling and every answer comes back with the patent numbers behind it.
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Most-cited records and a recent filing
Representative recent filing
US20260037682A1 — Logistics transportation digital twin system for modular cleanroom
LOCUS CELL CO., LTD
A logistics transportation digital twin system for a modular cleanroom comprises a three-dimensional model computation module that constructs models of the cleanroom and an AGV, a perception data processing module covering multiple cleanrooms built from rapidly assembled partition panels, and a digital twin module that combines sensed cleanroom and AGV operational data into a live virtual representation.Filed by LOCUS CELL CO., LTD, published 2026-02-05 — one of the few non-Chinese-office filings in the dataset.
Highest-citation families in this dataset
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | CN114037352A | 基于数字孪生的自动化集装箱码头多AGV动态调度方法 | 26 |
| 2 | CN116050122A | 基于汽车柔性装配产线的数字孪生推演系统及方法 | 17 |
| 3 | CN115933684A | 基于AGV的数字孪生车间智能动态调度物流系统 | 17 |
| 4 | CN113792406A | 一种基于数字孪生的AGV小车仿真系统 | 17 |
| 5 | CN115310936A | 基于数字孪生的智慧物流工厂可视化与数据服务技术系统 | 10 |
| 6 | CN120145663A | 一种基于数字孪生的智慧港口调度与能效优化方法 | 9 |
| 7 | CN109725641A | 一种管理多辆AGV的交通避让方法 | 9 |
| 8 | CN118706124A | 一种基于数字孪生的仓储系统AGV出库导航规划方法 | 8 |
| 9 | CN115713175A | 基于数字孪生的AGV小车运输路径规划方法 | 8 |
| 10 | US20230325746A1 | AGV scheduling control system and method | 7 |
Citation counts favour older filings that have had more time to accumulate references within the searched corpus; treat them as a measure of influence, 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.
Source: Patsnap Eureka. Citation counts and representative records. Derived from a Patsnap search on Automated Guided Vehicle Simulation and Modeling covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
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What the numbers indicate
Three read-throughs from the filing, citation, and classification data that matter for anyone deciding where to file or partner next.
Geographic concentration
34 of 45
families via Chinese receiving office
Filing activity is concentrated in one jurisdiction
China accounts for the large majority of receiving offices in this dataset, with the US, Europe, India, Taiwan, and Germany each in single digits. Anyone assessing freedom-to-operate outside China should treat the non-Chinese counts as too thin to draw firm conclusions from yet.
Receiving office counts, this dataset
Classification mix
33 vs 7
G06Q records vs G05D records
Claims skew toward scheduling and data logic, not motion control
G06Q (business/admin data processing) outnumbers G05D (control of non-electric variables) by a wide margin. That split suggests most applicants are protecting the simulation and scheduling layer around AGV fleets rather than the underlying vehicle control algorithms.
IPC subclass counts, this dataset
Collaboration pattern
2 pairs
co-assignee pairs across 45 families
Joint filings are rare
Only two co-assignee pairs appear across the entire dataset, both pairing a university with an industrial partner. The dominant pattern is single-assignee filing, which may reflect internal R&D programmes rather than formal joint ventures.
Co-assignee pairs, this dataset
Citation leaders
26 citations
top-cited family (CN114037352A)
The most-cited work centres on container terminal scheduling
The highest-cited record addresses digital-twin-based dynamic scheduling for multi-AGV automated container terminals, with the next tier covering flexible assembly lines and warehouse logistics twins. Influence in this corpus clusters around large-scale industrial scheduling problems.
Citation counts, this dataset
Eureka AI Agent
Looking for what nobody has claimed yet?
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to automated guided vehicle simulation and modeling, with the prior art for and against each one.
Source: Patsnap Eureka. Co-assignee relationships and derived observations. Derived from a Patsnap search on Automated Guided Vehicle Simulation and Modeling covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
Players
Who is filing, and where the field is still open
Assignee activity in this dataset is fragmented, with no single filer showing sustained late-year momentum — a signal worth checking against the under-claimed branches below.
Momentum check
0 in latest year
across every listed assignee
No assignee shows current-year momentum
Every assignee tracked for recent-year activity — including battery and research-institution filers — recorded zero filings in the latest year, with some showing a -100% YoY drop. This is consistent with the dataset's overall late-2025 peak followed by a partial 2026.
Recent-year momentum, this dataset
Filer type
Mixed
industrial and academic assignees
Universities appear alongside industrial filers
Institutions such as Northwestern Polytechnical University and Chongqing University sit in the same assignee pool as battery and logistics technology firms, though joint filings between the two groups remain rare.
Assignee composition, this dataset
Long tail
45 families
total dataset size
A long tail of single-filing entrants
With only 45 families total and citation influence concentrated in a handful of records, most assignees in this space appear to hold one or two filings rather than a defensible portfolio.
Family count, this dataset
Recent-year filing momentum by assignee
| Assignee | Recent year | YoY |
|---|---|---|
| Contemporary Amperex Technology Co., Ltd. (CATL) | 0 | — |
| Hong Kong CATL New Energy Technology Co., Limited | 0 | — |
| Northwestern Polytechnical University | 0 | -100% |
| Leka Renewable Technology Co., Ltd. | 0 | -100% |
| Wei Xiaolan | 0 | — |
| Chongqing Humi Network Technology Co., Ltd. | 0 | — |
| Chongqing Tiancheng Digital Manufacturing Technology Co., Ltd. | 0 | -100% |
| Chongqing University | 0 | -100% |
Source: Patsnap Eureka. Assignee-level momentum. Derived from a Patsnap search on Automated Guided Vehicle Simulation and Modeling covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
What's Next
Where to take this
The dataset points to a scheduling-and-twin-construction core that is well claimed in China, with thinner coverage elsewhere and in adjacent sensing and networking branches.
Model the white space before drafting
Run the under-claimed branches above against a fuller claim-chart search in Eureka to see whether the thin counts reflect genuine white space or simply narrower search terms.
Explore in EurekaWatch non-Chinese filings closely
With only single-digit counts outside China, a small number of new filings in the US, Europe, or elsewhere could meaningfully shift freedom-to-operate assessments there.
Track new filingsSource: Patsnap Eureka. Forward-looking reading of the same dataset. Derived from a Patsnap search on Automated Guided Vehicle Simulation and Modeling covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
FAQ
Common questions on AGV simulation patents
This landscape includes patent families that combine automated guided vehicle terminology with a simulation, digital twin, traffic simulation, or layout simulation claim element, filtered to classifications covering control systems, computer-aided design, and business/admin data processing. It excludes pure AGV hardware or navigation patents that do not reference a simulation or modelling layer. The intent is to isolate the virtual-modelling side of AGV deployment rather than the vehicle itself.
The dataset shows a fragmented field with no single assignee holding a large, sustained lead; most listed assignees, including established battery and logistics technology firms, show zero filings in the most recent tracked year. Citation influence instead clusters around a handful of specific records covering container terminal scheduling and flexible assembly line twins. A reader should treat this as an open field rather than one dominated by an incumbent.
Of the 45 families tracked, 34 received filings through the Chinese patent office, far ahead of the US, Europe, India, Taiwan, and Germany, each in single digits. This likely reflects both the concentration of AGV manufacturing and factory automation deployment in China and the dataset's classification and keyword scope. It does not necessarily mean the underlying technology originates only in China, since many applicants file domestically first and expand later.
Filing volume grew from zero in 2017 to a midpoint of 11 in 2022 and peaked at 15 in 2025, but the 2026 count of 4 is partial because of the mid-2026 data cut-off and an 18-month typical publication lag. So the apparent slowdown in the most recent year likely understates true filing activity. A clearer read on 2026 will only be possible once later filings finish publishing.
The classification split shows heavy claim density in scheduling and business-process data processing (G06Q) relative to core control classifications (G05D, G05B), suggesting under-claimed opportunity in motion-control-integrated simulation. Cross-referenced branches touching wireless network-aware fleet simulation and vision-based layout calibration also show thinner representation. These are starting points for a deeper claim-chart search rather than confirmed gaps.
Answers are grounded in the same dataset. Derived from a Patsnap search on Automated Guided Vehicle Simulation and Modeling covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
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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.