Robot Trajectory Planning Patents: Top Companies & Trends 2026
- Filing has plateaued, not grown. activity peaked in 2021 at 71 families and has since drifted down through the 2022 midpoint of 64 toward 26 in the most recent (partial) year — a sign the core claim space is filling in rather than expanding.
- China now dominates the filing venue. 335 of 603 records were filed at the Chinese receiving office versus 143 in the United States, meaning freedom-to-operate analysis that skips China is analysing the wrong docket.
- Collaboration is rare and lopsided. only 4 co-assignee pairs exist across 603 families, and one pairing — Amada America, Inc. and Amada Co., Ltd. — accounts for 15 of those joint filings, dwarfing every other collaboration combined.
Filing growth compares 2021 (71 records) with 2024 (66) — 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 603 records in scope (CR5), not by the ranked leaders only.
What this landscape covers
This landscape tracks patent families at the intersection of trajectory planning, robot kinematics and motion planning, filtered to documents that explicitly claim joint-space or Cartesian-space formulations, inverse kinematics, singularity avoidance or collision avoidance, and classified under the core manipulator and industrial-control IPC groups. It spans 603 published families filed between 2015 and mid-2026, giving a reasonably complete view of how the claim space around robot motion control has been staked out over the past decade.
The picture that emerges is one of a mature, densely occupied field rather than an emerging one: filing volume rose through the late 2010s, peaked in 2021, and has since flattened. Because publication typically lags filing by around 18 months, the most recent year's count is understated and should not be read as an actual decline in filing activity.
Filing trend and technology composition
Two views of the same 603-family dataset: how filing volume has moved year over year, and which IPC subclasses carry the claim weight.
A decade of filings that has already crested
Volume climbed from 29 families in 2017 to a peak of 71 in 2021, sat at 64 by the 2022 midpoint, and has since declined toward 26 in the latest partial year. Read this as a maturing field consolidating around established claim language, not as a shrinking market — the underlying installed base of industrial and service robots keeps expanding even as the rate of new motion-planning claims slows.
Manipulator claims dominate; software and AI classes are secondary
B25J (manipulators & robots) appears in 563 of 603 records, confirming this is fundamentally a mechanical-and-control-systems field rather than a pure software one. G05B (control and regulating systems) trails at 81, with G06F, G05D and G06N — the data-processing, non-electric-control and AI-model classes — each in the 20–36 range. Sheet-metal working (B21D) and web/sheet handling (B65H) show up as smaller adjacent clusters, pointing to sheet-metal bending and material-handling robots as recurring application niches rather than the field's centre of gravity.
Shares are the percentage of the 603 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Robot Trajectory Planning and Kinematics with Eureka
This page is one run against one query. Ask Eureka your own question about robot trajectory planning and kinematics and every answer comes back with the patent numbers behind it.
Try EurekaA representative claim and the most-cited prior art
US12151379B2 — Method of robot dynamic motion planning and control (FANUC)
A method and system for motion planning for robots with a redundant degree of freedom. The technique computes a collision avoidance motion plan for a robot with a redundant degree of freedom, without artificially constraining the extra degree of freedom. The motion planning is formulated as a quadratic programming optimization calculation having a multi-component objective function and a collision avoidance constraint function. The formulation is efficient enough to compute the motion plan in real time at every robot control cycle. The collision avoidance constraint ensures clearance of all parts of the robot from both static and dynamic obstacles.Granted November 2024 — recent enough that its claim scope is still fully live and worth checking against any redundant-DOF motion planner under development.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US6577925B1 | Apparatus and method of distributed object handling | 266 |
| 2 | US20160016311A1 | Real-Time Determination of Object Metrics for Trajectory Planning | 250 |
| 3 | US6004016A | Motion planning and control for systems with multiple mobile objects | 238 |
| 4 | US6076030A | Learning system and method for optimizing control of autonomous earthmoving machinery | 227 |
| 5 | US6493607B1 | Method for planning/controlling robot motion | 203 |
| 6 | US6643563B2 | Trajectory planning and motion control strategies for a planar three-degree-of-freedom robotic arm | 164 |
| 7 | US20090118864A1 | Method and system for finding a tool center point for a robot using an external camera | 159 |
| 8 | US5969973A | Intelligent system for generating and executing a sheet metal bending plan | 138 |
| 9 | US20190184560A1 | A Trajectory Planning Method For Six Degree-of-Freedom Robots Taking Into Account of End Effector Motion Error | 128 |
| 10 | US20030108415A1 | Trajectory planning and motion control strategies for a planar three-degree-of-freedom robotic arm | 124 |
Citation counts favour older filings simply by virtue of having had more time to accumulate citations within this searched corpus — treat the ranking as a measure of historical influence, not of which patents matter most today.
Each row carries its publication number; clicking a row searches Eureka by that number.
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Browse MCP servers →What the numbers say about where this field stands
Three signals worth acting on before drafting or filing in this space.
Growth has already flattened
The field grew steadily through the late 2010s, crested in 2021, and has been declining since the 2022 midpoint of 64. Combined with the 18-month publication lag, this looks like a claim space that is filling in rather than one still opening up.
China is the primary filing venue, by a wide margin
More than half of all records in this dataset were filed in China, with the United States a distant second and Europe, WIPO, India and Japan each filing in single or low double digits. Competitive monitoring and clearance work that is US-centric will miss most of the activity.
Joint filing is the exception, not the norm
Only four co-assignee pairs appear in the entire dataset, and one pairing between Amada America, Inc. and Amada Co., Ltd. accounts for 15 joint filings — far more than the other three pairs combined. Most assignees in this field file solo.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to robot trajectory planning and kinematics, with the prior art for and against each one.
Who is active, and where the gaps sit
Filing volume is concentrated among a handful of industrial-robot and university assignees, with recent-year momentum shifting between them rather than accelerating overall.
A university climbing while incumbents pull back
Harbin Institute of Technology filed 2 records in the latest year, doubling year over year, while established filers such as FANUC CORPORATION (FANUC) show 0 filings in the same year, down 100% YoY. That divergence suggests academic groups are picking up claim territory that industrial incumbents are, for now, not contesting.
One sheet-metal partnership dominates joint filing
The strongest co-assignee pair in the dataset links Amada America, Inc. (Amada America) and Amada Co., Ltd., consistent with the B21D sheet-metal-working cluster sitting alongside the core manipulator classes. No other pairing comes close in volume.
Several historically active filers show zero recent activity
Multiple assignees with meaningful filing histories — including Amada America, Inc. and X开发有限責任公司 — recorded zero filings in the latest year. Given the publication lag, some of this is reporting delay rather than a genuine stop, but it is worth confirming before assuming continued activity.
| Assignee | Recent year | YoY |
|---|---|---|
| Harbin Institute of Technology | 2 | +100% |
| South China University of Technology | 1 | — |
| FANUC CORPORATION | 0 | -100% |
| Amada America, Inc. | 0 | — |
| Realtime Robotics, Inc. | 0 | — |
| X Development LLC | 0 | — |
| Zhejiang University of Technology | 0 | -100% |
| Amada Co., Ltd. | 0 | — |
Where to take this analysis
The dataset points to three practical next steps for teams evaluating this space.
Check freedom-to-operate against the China docket first
With 335 of 603 families filed in China against 143 in the US, any clearance search that stops at USPTO and EPO records is missing the majority of the field's claim activity.
Explore the China filing setTest claim drafts against the under-claimed sub-areas
The gaps in AI-driven trajectory optimization and non-electric variable control integration are narrow enough to search directly before committing drafting resources elsewhere.
Search adjacent IPC classesWatch university filers, not just industrial incumbents
Momentum has shifted toward academic assignees like Harbin Institute of Technology while some industrial filers have gone quiet in the latest year — track both sides before assuming the competitive set is fixed.
Track assignee momentumCommon questions about this landscape
Filing in this space is led by a mix of established industrial-robot manufacturers and Chinese universities, with no single assignee holding a dominant share of the 603 families in this dataset. The clearest pattern is jurisdictional rather than corporate: China accounts for 335 of the 603 records, far more than any individual company's filing count. Recent-year momentum has also shifted, with some historically active industrial filers showing zero filings in the latest year while certain university groups show growth, so 'who leads' depends heavily on whether you weight by cumulative volume or by recent activity.
Not by filing volume — the trend peaked in 2021 at 71 families, sat at 64 by the 2022 midpoint, and has declined since, reaching 26 in the latest partial year. Because patent publication typically lags filing by about 18 months, the most recent one or two years will always look artificially low, so the true 2025–2026 filing rate is likely higher than currently visible. Even accounting for that lag, the multi-year trend from 2021 onward points to a field that has matured past its fastest growth phase rather than one still accelerating.
US12151379B2, granted to FANUC in November 2024, claims a method for motion planning on robots with a redundant degree of freedom, using a quadratic-programming formulation with a multi-component objective function and an explicit collision-avoidance constraint. Its distinguishing feature is that it avoids artificially constraining the redundant degree of freedom while still computing the plan efficiently enough for real-time execution at every control cycle. Anyone building a redundant-DOF collision-avoidance planner that also uses a real-time QP formulation should check this claim closely, since it was granted recently enough to remain fully enforceable.
The IPC composition shows a dense core in B25J (manipulators) and G05B (control systems) but comparatively thin coverage in adjacent classes: AI-model-driven trajectory optimization under G06N, non-electric variable control under G05D, and application-specific motion coordination in web/sheet handling (B65H) and electrophotography (G03G). These are not empty categories, but their record counts are a fraction of the B25J core, suggesting room for narrowly scoped claims that combine established kinematics methods with these less-contested application domains.
China holds 335 of the 603 total records in this dataset, more than double the United States' 143, which reflects both the scale of China's domestic robotics manufacturing base and a strong pattern of university-affiliated filing — several of the most active assignees in this corpus are Chinese universities and research institutes. This concentration means that competitive intelligence or freedom-to-operate work limited to USPTO, EPO or WIPO records will systematically undercount the field's actual claim density. Teams evaluating this space should treat the China receiving office as the primary docket, not a secondary check.
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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.