Modular / Reconfigurable Cobot Patent Snapshot 2026
The formal patent corpus for modular and reconfigurable collaborative robots is embryonic, with only 3 patent families on record, all filed in 2025–2026, and dominated by academic institutions. This nascent state signals both that the field is largely uncontested by commercial players and that prior-art density is minimal — conditions that favor early strategic filing.
Academic institutions hold every position in a three-family corpus
All three applicants in the ranked corpus — Dayananda Sagar College of Engineering, Sanskrithi School of Engineering, and Zhejiang University — hold one patent family each, placing them in a perfect three-way tie at the top of the ranking.
The top five filers account for 100% of the combined output of the ranked applicants visible in this query, which in this case collapses to just three academic institutions. There is no visible tier gap between a visible commercial leader and challengers; the field has not yet attracted identifiable industrial assignees.
| # | Applicant | Patent families | Share |
|---|---|---|---|
| 1 | Dayananda Sagar College of Engineering | 1 | |
| 2 | Sanskrithi School of Engineering | 1 | |
| 3 | Zhejiang University | 1 |
The absence of corporate assignees at this stage suggests that modular/reconfigurable cobot IP is not yet a priority for established robotics OEMs, leaving the evidence snapshot open for either academic spin-outs or first-mover industrial entrants to establish foundational positions.
The most recent filings fall within the publication lag window; the corpus total of 3 patent families should be treated as a floor, not a ceiling, as additional applications from 2025–2026 may not yet have published. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
All activity concentrated in 2025–2026; robotics manipulation dominates the technology mix
The annual filing trend and technology composition charts together reveal a field that emerged abruptly in the most recent filing window, with a technology profile anchored in core robotics IPC classes and supplemented by AI, vision, and control branches.
Annual filing trend
Zero filings were recorded from 2017 through 2024; two families appeared in 2025 and one in 2026. Because both years fall inside the standard publication lag window, this apparent two-year burst may undercount actual activity — the true trough-to-activity inflection should be confirmed as more applications publish.
↗ Hover for values · click a bar to ask EurekaTechnology composition
B25J (Manipulators & robots) covers all three families and is the clear anchor class. Secondary classes — G05D (control), G06F (digital data processing), G06N (AI models), G06T (image processing), G06V (image/video recognition), and G09B (educational aids) — each appear once, indicating that individual filers are differentiating through sensing, AI, and human-interaction layers rather than competing in the same sub-class.
↗ 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.
Self-adaptive identification method for nonlinear …
Provided is a self-adaptive identification method for nonlinear dynamic parameters of a reducer, which belongs to the design field of a reducer. The method includes: modeling a harmonic reducer corresponding to a flexible joint as a concatemer of a rigid reducer and an elastic torsion spring, and carrying out dynamic theoretical modeling and parameter… (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | Self-adaptive identification method for nonlinear … | 9 |
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.
Assignee snapshot from the current evidence set
The applicants below are visible in this query result. Because the evidence set is relatively small, read this section as a directional snapshot rather than a full competitive ranking.
Dayananda Sagar College of Engineering
Dayananda Sagar College of Engineering holds 1 patent family with a technology emphasis spanning B25J 9 (manipulators and robots), G06F 3 (digital data processing / human-interface), and G06T 7 (image data processing and generation) — suggesting a vision-guided, human-interactive cobot design. Applicant momentum data is not available due to the absence of comparable prior-period filings.
families: 1Zhejiang University
Zhejiang University holds 1 patent family focused on B25J 9 (manipulators and robots) and has secured a United States filing — the only non-Indian jurisdiction represented in the corpus — indicating an intent to establish IP in a major commercial market. Its single-class focus contrasts with the more multi-class profiles of the two Indian institutions. Momentum data is not available.
families: 1Frequently asked questions
The current corpus contains 3 patent families in scope. All were filed in 2025–2026, and because both years fall within the standard publication lag window, this figure should be treated as a minimum; additional applications may not yet have published.
The three ranked applicants are Dayananda Sagar College of Engineering, Sanskrithi School of Engineering, and Zhejiang University, each holding 1 patent family. All are academic institutions; no commercial robotics company appears in the current corpus.
India leads with 2 patent records, followed by the United States with 1 record. No filings from Europe, China (domestic), Japan, or Korea appear in the current corpus.
B25J (Manipulators and robots) covers all 3 families and is the visible class. Secondary classes — G05D, G06F, G06N, G06T, G06V, and G09B — each appear once, reflecting individual filer choices in control, AI, vision, and human-interaction layers.
No co-applicant relationships are present in the current corpus. Each of the three families was filed by a single institution independently. Structured R&D partnerships have not yet formed around modular/reconfigurable cobot IP.
Zero families were recorded from 2017 through 2024; activity emerged only in 2025 (2 families) and 2026 (1 family). The corpus is too small and too recent to establish a reliable trend, and both active years fall within the publication lag window.
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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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