AMR Motion Planning Patents: Leaders, Trends & White Space 2026
Patent landscape analysis of autonomous mobile robot motion planning: filing trends from 2017 to 2026, leading assignees, IPC technology composition, and where claim space remains open.
Filing growth = 2021 (5 records) → 2024 (11); 2024 is the last year we treat as complete. Top-5 share = the 5 largest assignees ÷ all 122 records in scope (CR5), not the ranked leaders only.
What the filing record shows
Autonomous mobile robot (AMR) motion planning sits at the intersection of two IPC families: G05D, control of non-electric variables, which covers the vast majority of records, and B25J, manipulators and robots, which appears in roughly a third. This split reflects the field itself — motion planning is fundamentally a control problem, but a meaningful share of filings tie that control logic to a specific robotic manipulator or platform. Filing activity is recent: the earliest tracked year is 2017, and the field peaked so far in 2022 with 27 published records.
The picture is one of a growing but not yet consolidated field. No single assignee holds a commanding share, and filings are spread thinly across research institutes, robotics start-ups and a handful of larger technology firms. China's receiving office accounts for the majority of filings in scope, well ahead of India, the United States, South Korea, the EPO and WIPO's PCT route.
Filing trend and technology composition
Publication lags filing by roughly 18 months, so the most recent years in the trend chart understate real activity. The IPC breakdown below uses all 122 records in scope as its denominator; because a single record can carry more than one class, the shares sum to more than 100%.
A recent field, growing unevenly
Annual filings rose from 3 in 2017 to a peak of 27 in 2022, then continued at a lower but still elevated level. The 2021-to-2024 span, the most recent stretch that can be treated as complete, shows filings climbing from 5 to 11 records, a +120% increase. Treat 2025 and 2026 figures as provisional rather than a sign of slowdown.
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.
Control logic dominates the claim space
G05D (control of non-electric variables) appears in 86.1% of the 122 records, confirming that most filings frame the invention as a control-and-navigation problem rather than a mechanical one. B25J (manipulators & robots) follows at 30.3%, with G01C (navigation and gyroscopes) at 13.1%. Smaller shares in G06N (AI models), G06V (image recognition), G06Q (business data processing), A61B (diagnosis and surgery) and B60W (vehicle control) point to adjacent branches where AMR motion planning is being fused with other domains but has not yet built up dense prior art.
Shares are the percentage of the 122 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
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Try EurekaRepresentative filing and most-cited prior art
Autonomous mobile robot with real-time obstacle mapping and adaptive path planning
Filed by Mangalam College of Engineering in May 2025, this application combines LiDAR, ultrasonic and RGB-D sensing with SLAM-based localisation and a deep reinforcement learning module that adapts path planning to changing terrain and moving obstacles in real time. A sensor fusion layer is claimed to preserve obstacle avoidance without sacrificing path optimality, aimed at logistics, surveillance and industrial automation use cases.Filed close to the data cut-off; its publication itself is a sign of continuing entrant activity from academic institutions rather than only established robotics firms.
View full record| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US5911767A | Navigation system for an autonomous mobile robot | 184 |
| 2 | US5073749A | Mobile robot navigating method | 180 |
| 3 | CN105955280A | 移动机器人路径规划和避障方法及系统 | 151 |
| 4 | US20180247160A1 | Planning system and method for controlling operation of an autonomous vehicle to navigate a planned path | 92 |
| 5 | CN105629970A | 一种基于超声波的机器人定位避障方法 | 88 |
| 6 | KR1020130112507A | Safe path planning method of a mobile robot using Ｓ＊ algorithm | 83 |
| 7 | KR1020050024840A | Path planning method for the autonomous mobile robot | 71 |
| 8 | KR101539270B1 | Sensor fusion based hybrid reactive motion planning method for collision avoidance and autonomous navigation,… | 49 |
| 9 | CN112099493A | 一种自主移动机器人轨迹规划方法、系统及设备 | 45 |
| 10 | CN107065870A | 移动机器人自主导航系统及方法 | 45 |
Citation counts favour older filings within the searched corpus; treat them as a signal of influence on the field, 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.
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Three patterns stand out once the ranking, the IPC mix and the geography are read together.
Leadership is real but thin
The leading assignee holds 6 records and fifth place holds 4, yet the top 5 combined still account for only 21.3% of all 122 records in scope. That is a long tail, not a duopoly: most of the field's activity comes from single- or double-digit filers, including university labs and regional robotics vendors.
Activity is accelerating, not plateauing
Filings rose from 5 in 2021 to 11 in 2024, the last year that can be treated as complete given publication lag. Combined with a 2022 peak of 27 records, the trend reads as an emerging field still absorbing new entrants rather than one settling into a stable filing rate.
Filing activity is geographically lopsided
China's receiving office accounts for 69 of the tracked filings, well ahead of India (14), the United States (11), South Korea (9), the EPO (8) and WIPO's PCT route (6). Strategies built only around US or European filings will miss most of the documented activity in this field.
Control logic, not hardware, is where claims sit
With G05D present in 86.1% of the 122 records and B25J in 30.3%, most inventions are being claimed as navigation and control methods. Adjacent classes tied to AI models, image recognition and vehicle control each sit under 7%, marking those fusions as comparatively open.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to autonomous mobile robot motion planning patent landscape, with the prior art for and against each one.
Where to take this analysis
The dataset points to specific next questions for R&D and IP teams rather than a single conclusion.
Map the under-claimed fusions
G06N, G06V and B60W each sit at single-digit shares of the 122 records. That is where motion planning is being combined with AI perception and vehicle control but has not yet built up dense prior art.
Explore white space in EurekaTrack the long tail of filers
With the top 5 assignees holding only 21.3% of records, most competitive signal sits outside the visible leaders. A working list of the full ranked set matters more here than in a concentrated field.
Run an assignee deep-dive in EurekaWatch China-origin filings closely
69 of the tracked filings went through the China receiving office. Teams filing only in the US or Europe are working from a partial picture of the technology's development.
Compare receiving offices in EurekaCommon questions on this landscape
No single company dominates this field. The leading assignee in this dataset holds 6 of the 122 records in scope, and the top 5 assignees combined account for only 21.3% of all records. The ranking spans 100 companies and includes robotics vendors, research institutes and universities from multiple countries, so competitive tracking needs to look well beyond the top few names to get a full picture.
Filing activity climbed from 5 records in 2021 to 11 in 2024, a rise of 120% over that three-year span, which is the most recent period that can be treated as complete given typical publication lag. The field's peak year so far is 2022 with 27 published records. Figures for 2025 and 2026 are still filling in and should not be read as a slowdown.
G05D, covering control of non-electric variables, appears in 86.1% of the 122 records in scope, making it the dominant classification by a wide margin. B25J, manipulators and robots, follows at 30.3%, and G01C, navigation and gyroscopes, at 13.1%. This confirms that most filings are framed as control and navigation methods rather than purely mechanical robot designs.
China's receiving office accounts for 69 of the tracked filings, substantially more than any other jurisdiction, followed by India at 14 and the United States at 11. South Korea, the EPO and WIPO's PCT route each account for single-digit counts. A filing strategy weighted only toward the US or Europe would miss the bulk of documented activity in this dataset.
The IPC composition points to several branches with comparatively little claim density: G06N (AI-based computing models) at 6.6% of records, G06V (image and video recognition) at 5.7%, and B60W (hybrid or joint vehicle control) at 2.5%. These figures suggest that fusing motion planning with AI-driven perception or vehicle-level control systems has not yet been heavily claimed, relative to the core control-and-navigation space covered by G05D.
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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.