Agricultural Robot Pest Detection Patents: Leaders & White Space 2026
A patent landscape review of agricultural robot pest detection technology: filing trends, leading assignees, IPC composition, and where claim space remains open through 2026.
Filing growth = 2021 (2 records) → 2024 (4); 2024 is the last year we treat as complete. Top-5 share = the 5 largest assignees ÷ all 23 records in scope (CR5), not the ranked leaders only.
A small, early-stage field with no established leader
Agricultural robot pest detection sits at the intersection of field robotics and vision-based classification: a mobile platform (B25J manipulators, G05D non-electric control) carries an inspection and treatment payload built around pest and vermin control claims (A01M). The scope in this dataset is small — 23 published records — and young: filing activity was effectively zero before 2017 and only began compounding meaningfully from 2021 onward.
The assignee base is fragmented. Thirty-nine companies and institutions appear in the ranking, the leader holds only 2 records, and the top 5 combined account for 30.4% of all records in scope. That pattern — a wide field of single- or double-filing entrants rather than a dominant incumbent — points to a technology area where the core claim space is still being staked out rather than defended.
Filing trend and technology composition
Two views of the same 23-record dataset: how filing volume has moved year over year, and how records distribute across IPC subclasses. Because a single record can carry several IPC codes, the composition shares add up to more than 100% of the record total.
Filing trend: quiet start, compounding growth
Filings sat at zero as recently as 2017. From 2021's 2 filings to 2024's 4, the field grew 100% over three years — the most recent complete-year comparison this dataset supports. 2026 shows 8 records, the highest of any year, but publication lag of roughly 18 months means the true count for 2025 and 2026 filings is still arriving and should not be read as a peak or a slowdown either way.
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.
IPC composition: pest control claims dominate, robotics is the vehicle
A01M (pest & vermin control) appears in 78.3% of the 23 records, making it the field's dominant claim category, with B25J (manipulators & robots) close behind at 52.2%. AI-driven classification (G06N, 30.4%) and image recognition (G06V, 21.7%) trail well behind pest-control and robotics claims, suggesting that the detection logic itself is less contested than the mechanical and control-system implementation around it.
Shares are the percentage of the 23 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Agricultural Robot Pest Detection Patent Landscape with Eureka
This page is one run against one query. Ask Eureka your own question about agricultural robot pest detection patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaKey patents in agricultural robot pest detection
Semi-automatic tracked mobile manipulator cum agricultural robotic system for vision-based disease detection and spraying pesticides
The present invention discloses a mobile manipulator cum agricultural robotic system comprising a tracked mobile manipulator with vision-based inspection module of the diseased leaves and vegetables, and module for spraying of appropriate pesticides to the diseased leaves and vegetables. The tracked mobile manipulator includes a tracked vehicle, a serial manipulator, a flow control of pesticides tanks, spraying module of pesticides, a gripper of the manipulator, vision system and a battery pack.Filed by Indian Institute of Technology Kharagpur, published 2024-09-20.
View full record| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | KR1020150124305A | Agricultural robot | 37 |
| 2 | CN118202987A | 基于增强现实远程控制的视觉喷洒机器人的施药方法 | 13 |
| 3 | CN118587475A | 一种适用于农作物害虫的检测方法及处理系统 | 4 |
| 4 | CN112677132A | 一种农田农作物药物自动检测机器人 | 2 |
| 5 | CN211019920U | 一种农用多功能智能机器人 | 2 |
| 6 | CN113575107A | 一种多功能智能农业机器人 | 1 |
Citation counts favour older records within this searched corpus; treat them as a signal of influence rather than of current technical importance.
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. Publication numbers are shown where the record carries one (6 of 6 rows); clicking a row searches Eureka by that number.
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Three read-outs from the underlying dataset that matter for deciding where to file and who to watch.
No incumbent controls the core claims
The leading assignee holds only 2 records, and the top 5 combined account for 30.4% of all 23 records in scope. That is a fragmented field for its size: freedom-to-operate risk from any single filer is low, but so is the certainty of what 'the standard approach' looks like.
Growth is real but the field is still small
Filings doubled from 2 in 2021 to 4 in 2024 — the last year this dataset can treat as complete. 2026's 8 records look higher still, but publication lag means that figure will keep revising upward and should not yet be read as the field's ceiling.
Filing activity is concentrated in two offices
India accounts for 13 records and China for 8, with South Korea and the Philippines each contributing a single record. Any freedom-to-operate review for this technology should prioritise Indian and Chinese filings first.
Pest control claims outweigh the vision layer
A01M appears in 78.3% of records versus 21.7% for G06V image recognition. The mechanical and dispensing side of the invention is more heavily claimed than the detection algorithm itself, which is where thinner prior art may sit.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to agricultural robot pest detection patent landscape, with the prior art for and against each one.
| Assignee | Co-assignee | Shared families |
|---|---|---|
| Lee Chul Hee | LEE CHUL HEE | 1 |
Co-assignment activity in this dataset is minimal — a single co-filing pair appears across the 23 records — reinforcing that this is largely a field of independent, single-institution filings rather than joint ventures.
Where to take this analysis
The dataset points to a fragmented, early field. These are the directions worth pursuing next.
Map the white space in vision-layer claims
G06V and G06N together sit well below A01M and B25J in claim density. A first filing narrowly drafted around a specific detection or classification method may face thinner prior art than one drafted around the mechanical platform.
Explore white space in EurekaTrack the two geographies that matter
India and China together account for 21 of the 23 records in scope. Any competitive monitoring program should set alerts on these two receiving offices first, then expand outward.
Set up monitoring in EurekaWatch for consolidation among the ranked leaders
With no assignee above 2 records, a shift to 3 or more by any single filer would be a meaningful signal of a strategic push. Worth tracking quarter over quarter rather than assuming the current fragmentation persists.
Build a tracked watchlist in EurekaCommon questions about this patent landscape
This dataset contains 23 published records filed or published between 2015 and the 2026 data cut-off, matched against IPC classes B25J, A01M and G06V. That is a small, early-stage field compared to more established agricultural robotics categories. Because publication lags filing by roughly 18 months, the true count for 2025 and 2026 will continue to rise as more records surface.
The field is fragmented: 39 companies and institutions appear in the assignee ranking, but the leading assignee holds only 2 of the 23 records. The top 5 combined account for 30.4% of all records in scope, and the top 10 for 52.2%. This is a long-tail field rather than one dominated by an established incumbent, so competitive monitoring needs to track a wide set of filers rather than one or two large portfolios.
Yes, on the complete-year evidence available: filings grew from 2 in 2021 to 4 in 2024, a 100% increase over that three-year span. 2026 shows 8 records so far, the highest single-year figure in the dataset, but that number is still incomplete because of the roughly 18-month lag between filing and publication. The safest read is that the field is growing, not that it has peaked or slowed.
India and China are the two dominant receiving offices, with 13 and 8 records respectively out of the 23 in scope. South Korea and the Philippines each contribute a single record. Anyone assessing freedom-to-operate risk or filing strategy in this space should prioritise Indian and Chinese patent offices first.
IN550470B, filed by Indian Institute of Technology Kharagpur and published 2024-09-20, covers a tracked mobile manipulator combining a vision-based inspection module for diseased leaves and vegetables with an integrated pesticide-spraying system. Its scope spans the tracked vehicle, serial manipulator, pesticide flow control, spraying module, gripper, vision system and battery pack as a combined system. Because it claims a full mechanical-plus-vision-plus-dispensing architecture rather than an isolated detection algorithm, it is most relevant to teams building integrated field robots rather than those working on standalone pest-classification software.
IPC composition shows A01M pest-control claims in 78.3% of records and B25J robotics claims in 52.2%, while G06V image recognition sits at only 21.7% and G06N AI-based computing at 30.4%. That gap suggests the vision and classification layer is comparatively under-claimed relative to the mechanical and dispensing side of these systems. A narrowly drafted filing focused on a specific detection or classification method, rather than the full robotic platform, may face less crowded prior art.
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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.