Collaborative Robot Patent Landscape in 2026
Collaborative Robot Patent Landscape in 2026
The collaborative robot field spans 3,705 patent families and is in a Growth stage, with a 31% increase over the recent filing window and China leading as the top filing jurisdiction. FANUC Ltd holds the largest position among established players, while the technology mix is heavily concentrated in manipulator and robot mechanics, with emerging activity across AI, vision, and control systems.
FANUC leads a moderately concentrated field with active challengers
FANUC Ltd ranks first with 124 patent families among the top hundred filers, followed closely by Digital Global Systems Inc and ABB (Schweiz) AG, each with 102 patent families. BAE Systems PLC and Strong Force VCN Portfolio 2019 LLC round out the top five.
The top five filers together account for 25% of the combined output of the hundred largest filers, indicating moderate concentration — no single player commands a dominant share, and challengers such as Neuromeka, Shenzhen Hans Robot, and Lincoln Global are building meaningful positions in the 35–45 patent family range.
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 1 | FANUC Ltd | 124 | |
| 2 | Digital Global Systems Inc | 102 | |
| 3 | ABB (Schweiz) AG | 102 | |
| 4 | BAE Systems PLC | 66 | |
| 5 | Strong Force VCN Portfolio 2019 LLC | 64 | |
| 6 | French Alternative Energies and Atomic Energy Commission (CEA) | 49 | |
| 7 | Lincoln Global Inc | 43 | |
| 8 | Neuromeka | 38 | |
| 9 | Shenzhen Hans Robot Co Ltd | 37 | |
| 10 | Intel Corporation | 35 |
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 11 | Yaskawa Electric Corporation | 34 | |
| 12 | The Boeing Company | 30 | |
| 13 | Illinois Tool Works Inc | 28 | |
| 14 | SCHAEFFLER TECHNOLOGIES AG & CO KG | 27 | |
| 15 | Exonetik Inc | 26 | |
| 16 | Robotiques 3 Dimensions | 25 | |
| 17 | Suzhou Elite Robotics Co Ltd | 24 | |
| 18 | Neura Robotics GmbH | 24 | |
| 19 | LG Electronics Inc | 24 | |
| 20 | Chef Robotics Inc | 23 |
FANUC and ABB’s positions reflect long-standing industrial robotics franchises extending into collaborative applications, while the presence of portfolio-holding entities (Digital Global Systems, Strong Force VCN Portfolio) and defense-oriented players (BAE Systems) signals that the competitive landscape spans operating companies, IP specialists, and cross-sector entrants.
Filings from roughly the past 18–24 months are subject to publication lag and will likely be revised upward as applications publish; treat the most recent data points as preliminary. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
Sustained multi-year growth led by manipulator mechanics, with AI and vision gaining share
The annual filing trend and technology composition together reveal a field that has expanded strongly since 2017 and is technically diversifying beyond core robot hardware into software, sensing, and AI-driven control.
Annual filing trend
Annual filings grew from 139 in 2017 to a peak of 545 in 2022, followed by modest easing in 2023 and 2024. The 2025 and 2026 figures are substantially under-counted due to publication lag and should not be read as a decline — the field’s 31% recent-window growth confirms continued expansion on a multi-year basis.
↗ Hover for values · click a bar to ask EurekaTechnology composition
B25J (Manipulators & robots) is the dominant branch by a wide margin, reflecting the hardware-centric nature of cobot innovation. The next-largest branches — G05B (Control & regulating systems), G05D (Control of non-electric variables), G06F (Electric digital data processing), and G06N (Computing based on AI models) — are each considerably smaller, signaling that software, AI, and sensing layers remain relatively underdeveloped relative to the mechanical core.
↗ Hover for values · click a bar to ask EurekaHighly cited patent families surfaced by the query
Citation-heavy patent families returned by the query. Use this section as citation context, not as a curated list of the most topic-specific patents.
Collaborative robot (COBOT) assistance
Real-time images of individuals and items on shelves of a store are analyzed for behaviors of the individuals and stocking levels of the items on the shelves. An autonomous Collaborative Robot (COBOT) is dispatched to aid the individuals based on the behaviors. The COBOT also restocks the shelves with the items when the stocking levels fall below predefined… (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | Obstacle recognition method for autonomous robots | 728 |
| 2 | Home robot using supercomputer, and home network s… | 351 |
| 3 | Robot Fleet Management for Value Chain Networks | 322 |
| 4 | Job Parsing in Robot Fleet Resource Configuration | 311 |
| 5 | Light weight and real time slam for robots | 259 |
| 6 | Home robot using home server, and home network sys… | 257 |
| 7 | Versatile mobile platform | 241 |
| 8 | Method of lightweight simultaneous localization an… | 196 |
Ranked by total forward citations. Citation counts favour older and broadly cited patent families, and broad or adjacent patents may appear when they match the search scope. Treat this section as citation context, not as a curated list of the most topic-specific patents. Some patent titles may be shown in their original, non-English language where an accurate translation could not be guaranteed.
What the patent structure means for R&D investment decisions
Four structural dimensions — maturity, concentration, collaboration, and geography — shape where R&D effort is best directed and where competitive risk is highest.
Growth stage with multi-year momentum intact
The lifecycle evidence classifies collaborative robots as Growth stage, with annual filings rising across the multi-year window and a 31% recent-window increase. The field has not yet entered a consolidation or saturation phase, meaning white-space capture is still actionable. Hardware-layer patents are maturing faster than software and AI sub-domains, creating differentiated timelines within the same field.
Growth stageModerate concentration with a competitive mid-tier
With the top five filers holding 25% of the hundred largest filers’ combined output, no single player commands a decisive share. FANUC’s lead of 124 patent families is meaningful but not prohibitive. The mid-tier — spanning roughly 25–65 patent families — is populated by diverse players including portfolio entities, industrial incumbents, and specialists, which means freedom-to-operate analysis is non-trivial across multiple sub-domains.
Moderate concentrationNo co-applicant activity identified in current evidence
The collaboration evidence is pending — no co-applicant filings were identified in the current dataset. This may reflect the competitive and proprietary nature of cobot hardware IP, or a data scope limitation. R&D teams should independently verify whether academic-industry or cross-company joint filings exist in adjacent sub-domains such as AI control or medical robotics before concluding that the ecosystem is entirely closed.
Evidence pendingChina and the United States are the primary filing battlegrounds
China leads all jurisdictions, followed by the United States, with Europe (EPO) and WIPO (PCT) filings indicating applicants seeking broad international coverage. Germany and South Korea are the next-largest national offices, reflecting the industrial robot manufacturing bases in those countries. India’s presence signals early-stage market interest. Teams targeting commercial deployment should prioritize freedom-to-operate clearance in China and the United States first.
China · US leadGo beyond the landscape: Eureka’s TRIZ Solution agent breaks down an R&D problem and returns patented concept solutions, each with a technical approach and cited patent & literature evidence.
Co-filing pairs, ranked by the number of jointly-filed patent families.
FANUC and ABB lead on manipulator mechanics; newer entrants skew toward AI and fleet control
The top two established industrial players dominate the mechanical manipulation branch, while newer entrants and portfolio holders are carving out positions in control, data processing, and fleet orchestration.
FANUC Ltd
FANUC Ltd holds 124 patent families, the largest position in the corpus. Its portfolio is concentrated almost entirely in B25J manipulator and robot sub-classes, reflecting a deep focus on physical robot mechanics and kinematics. Recent momentum shows a –68% decline in new filings versus the prior three-year window, suggesting the company may be shifting filing strategy, consolidating its portfolio, or redirecting R&D spend — a trend worth monitoring for signal on competitive priorities.
families: 124ABB (Schweiz) AG
ABB (Schweiz) AG holds 102 patent families, tied for second place, with its portfolio anchored in B25J manipulator mechanics and complemented by G05B control systems coverage — a broader technical scope than FANUC’s. Recent momentum shows a –40% decline versus the prior three-year window, a less severe pullback than FANUC’s, and ABB’s dual focus on hardware and control positions it as the stronger threat in integrated cobot system patents.
families: 102| Applicant | Recent (3 yrs) | Trend |
|---|---|---|
| FANUC Ltd | 19 | ▼ -68% |
| Digital Global Systems Inc | 3 | ▲ new entrant |
| ABB (Schweiz) AG | 26 | ▼ -40% |
| BAE Systems PLC | 8 | ▼ -85% |
| Strong Force VCN Portfolio 2019 LLC | 63 | ▲ new entrant |
| Universal Robots A/S | 9 | ▼ -72% |
| French Alternative Energies and Atomic Energy Commission (CEA) | 4 | ▲ new entrant |
| Lincoln Global Inc | 43 | ▲ new entrant |
Control systems, AI, and vision are under-served relative to the manipulator core
Five branches adjacent to the dominant B25J class show substantially lower patent density, representing areas where the technology gap between hardware capability and software/sensing sophistication may offer entry points for differentiated R&D.
G06N · Computing based on AI models
G06N accounts for a small share of the corpus relative to B25J, despite AI-driven motion planning, adaptive control, and human-robot interaction being widely cited as the next frontier for cobot capability. The technical value is clear: AI models that enable safe, flexible collaboration without hard-coded programming are a known commercial need. Entry paths include reinforcement learning for manipulation, anomaly detection for safety, and foundation model integration for task generalization — all areas where software-first companies can compete without replicating incumbents’ mechanical IP.
Search this in Eureka →G06T · Image data processing & generation
G06T (image data processing and generation) and the related G06V (image/video recognition) branch are both sparse relative to the manipulator core, despite vision being a critical enabler of unstructured-environment operation. Real-time 3D scene understanding, object pose estimation, and visual servoing for cobots are technically mature in academic settings but remain thinly covered in the patent corpus. Companies with computer vision or machine perception capabilities could extend into cobot-specific vision pipelines, particularly for bin-picking, assembly verification, and human proximity detection.
Search this in Eureka →How leading applicants differ across technology branches
Strength of each leader across the main technology routes.
| Player | B25J 9 · Manipulators & robots | B25J 19 · Manipulators & robots | B25J 13 · Manipulators & robots | B25J 11 · Manipulators & robots | B25J 15 · Manipulators & robots |
|---|---|---|---|---|---|
| FANUC Ltd | Strong · 94 | Moderate · 47 | Strong · 49 | Absent | Absent |
| BAE Systems PLC | Strong · 65 | Moderate · 24 | Moderate · 25 | Moderate · 18 | Moderate · 17 |
| ABB (Schweiz) AG | Strong · 84 | Moderate · 20 | Emerging · 12 | Absent | Emerging · 7 |
| Digital Global Systems Inc | Strong · 75 | Absent | Absent | Absent | Absent |
| Lincoln Global Inc | Strong · 43 | Absent | Absent | Moderate · 18 | Absent |
| Yaskawa Electric Corporation | Strong · 32 | Moderate · 11 | Moderate · 14 | Absent | Absent |
| Neuromeka | Strong · 36 | Absent | Absent | Strong · 19 | Absent |
Frequently asked questions
The corpus covers 3,705 patent families in scope globally, with China and the United States as the two leading filing jurisdictions.
FANUC Ltd leads with 124 patent families among the top-ranked filers, ahead of Digital Global Systems Inc and ABB (Schweiz) AG, which are tied at 102 patent families each.
The field is classified as Growth stage, supported by a 31% increase in filings over the recent window. Multi-year filing momentum remains positive, though the most recent 18–24 months are under-counted due to publication lag.
B25J (Manipulators & robots) is the dominant branch by a wide margin. G05B (Control & regulating systems), G05D (Control of non-electric variables), G06F (Electric digital data processing), and G06N (Computing based on AI models) are the next-largest branches but each hold a considerably smaller share.
G06N (AI models), G06T (image data processing), and G05D (control of non-electric variables) are adjacent branches with lower patent density relative to the manipulator core, and represent areas where the gap between hardware capability and software/sensing coverage is most pronounced.
China leads all filing offices, followed by the United States, Europe (EPO), and WIPO (PCT). Germany and South Korea are the next-largest national offices, reflecting key manufacturing bases for industrial robotics.
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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.
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