LiDAR SLAM Navigation Patents: Leaders, Trends & White Space 2026
A data-backed view of the LiDAR SLAM navigation patent landscape for mobile robots and AMRs: who is filing, where claim density concentrates, and where adjacent branches remain under-claimed.
Filing growth = 2021 (8 records) → 2024 (33); 2024 is the last year we treat as complete. Top-5 share = the 5 largest assignees ÷ all 158 records in scope (CR5), not the ranked leaders only.
What this landscape covers
LiDAR SLAM navigation sits at the intersection of localisation, mapping and motion control for mobile robots and autonomous mobile robots (AMRs). This landscape draws on 158 published records filed between 2015 and 2026, matched on claims and titles that combine LiDAR-based SLAM with navigation or guidance functions. Patent families, not raw document counts, are the fairer unit here because they neutralise aggressive continuation filing and multi-jurisdiction duplication — though this dataset’s family count and record count are the same, 158, so the two views align.
The filing curve, technology composition and assignee concentration below describe where claim space is already occupied and where it is thin. Because publication lags filing by roughly 18 months, the most recent one or two years in any trend understate true filing activity and should be read as provisional rather than as a slowdown.
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Filing trends and technology composition
Two views of the same 158 records: how filing activity has moved year over year, and how the field splits across IPC subclasses. Both are read against the full record count, not the ranked assignee list.
A field still accelerating, not levelling off
Annual filings moved from 1 in 2017 to a peak of 57 in 2025, with the 2021-2024 span alone showing +313% growth (8 to 33 records). 2026 figures (16 so far) are partial by definition given the data cut-off, and 2025's 57 should be treated as the high point of a still-rising curve rather than a ceiling.
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.
Navigation control dominates; sensing and AI classes trail
G05D (control of non-electric variables) appears in 65.2% of the 158 records, far ahead of B25J (manipulators & robots) and G01S (radar, sonar & positioning), which each sit at 21.5%. G01C (distance, navigation & gyroscopes) follows at 20.9%, while the AI- and vision-adjacent classes — G06T, G06N, G06V, G06F — each cover between 10% and 15% of records. Because records can carry multiple IPC codes, these shares add up to well over 100%; they describe overlap, not a partition of the field.
Shares are the percentage of the 158 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Mobile Robots & AMRs: LiDAR SLAM Navigation Patent Landscape with Eureka
This page is one run against one query. Ask Eureka your own question about mobile robots & amrs: lidar slam navigation patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaRepresentative filing and most-cited prior art
Clutter tidying robot utilizing floor segmentation for mapping and navigation system
A method and apparatus are disclosed for a clutter tidying robot utilizing floor segmentation for its mapping and navigation system, whereby a perception module and navigation module transform lidar and image data from lidar sensors and cameras of a robot sensing system using segmentation and pseudo-laserscan or point cloud transformations to generate global and local maps. The robot pose and maps are transmitted to a robot brain that directs an action module to produce robot action commands controlling the operation of a clutter tidying robot using the pose and map data.Filed by Clutterbot, Inc., published 2024-12-19. Multi-stage planning and obstacle avoidance are built on top of the segmentation-driven map pipeline described here.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20180253108A1 | Mobile robot system and method for generating map data using straight lines extracted from visual images | 83 |
| 2 | US20200309529A1 | Slam assisted ins | 55 |
| 3 | US20220147053A1 | Robot with perception capability of livestock and poultry information and mapping approach based on autonomou… | 36 |
| 4 | US20210364632A1 | Methods and Systems for Map Creation and Calibration of Localization Equipment in an Outdoor Environment | 28 |
| 5 | US8521418B2 | Generic surface feature extraction from a set of range data | 27 |
| 6 | US20130080045A1 | Generic surface feature extraction from a set of range data | 25 |
| 7 | US20110102545A1 | Uncertainty estimation of planar features | 17 |
| 8 | US20240419183A1 | Clutter tidying robot utilizing floor segmentation for mapping and navigation system | 11 |
| 9 | US20200307787A1 | Intelligent location awareness for unmanned systems | 11 |
| 10 | US11243081B2 | Slam assisted INS | 9 |
Citation counts favour older records simply by virtue of being searchable for longer; treat them as a signal of influence on the field rather than of current commercial importance.
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Browse MCP servers →What the numbers mean for a filing decision
Three read-outs from the ranking, trend and composition data that matter more than the raw totals on their own.
A leader, but no lock on the field
The leading assignee holds 12 records and the top 5 combined account for 25.3% of all 158 records in scope; the top 10 reach 35.4%. That leaves roughly two-thirds of filings spread across a long tail of single- and few-filing entrants, including university labs and early-stage robotics ventures.
Three years of compounding, not a spike
Filings rose from 8 in 2021 to 33 in 2024, a sustained climb rather than a single-year jump. 2025's count of 57 extends that trajectory, though publication lag means the true 2025-2026 total will likely land higher once later filings publish.
Control claims, not sensing claims, are the crowded ground
G05D covers nearly two-thirds of the 158 records, well ahead of the 21.5% each held by B25J and G01S. That gap suggests navigation and motion-control logic is the more heavily claimed layer, while raw LiDAR sensing and positioning hardware claims have comparatively more room.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to mobile robots & amrs: lidar slam navigation patent landscape, with the prior art for and against each one.
Where to take this analysis
The figures above answer where the field stands today. The next questions are what a specific filing blocks, and where a new claim could still land clean.
Map a freedom-to-operate position against the top filers
Cross-reference a target claim set against the ranked assignees holding dense G05D or G01S positions before committing R&D spend to that exact mechanism.
Explore in Patsnap Eureka →Track the 2025-2026 filings as they mature
Publication lag means this year's true filing count is still forming; revisit the trend once later filings publish to confirm whether the growth curve holds.
Set up monitoring in Patsnap Eureka →Common questions on this landscape
This landscape identifies 158 published records matching LiDAR-based SLAM combined with navigation or guidance claims, filed between 2015 and the 2026 data cut-off. That figure covers records, which in this dataset also equals the family count, so continuation filings and duplicate jurisdiction filings are not inflating the number. It is not a count of all robotics patents; it is scoped specifically to the LiDAR SLAM navigation claim language described in the search string.
The ranked leader holds 12 of the 158 records, with the fifth-ranked assignee at 4 and the tenth-ranked at 3. The top 5 combined account for 25.3% of all records and the top 10 for 35.4%, which means well over half the field is filed by entities outside the ranked top 10. This is a fragmented field rather than one dominated by a handful of incumbents, so a competitive watch list needs to extend beyond the obvious names.
Yes. Filings grew from 8 in 2021 to 33 in 2024, a documented +313% increase, and the peak year so far is 2025 at 57 records. Because patent publication lags filing by roughly 18 months, 2025 and 2026 figures are still incomplete and should not be read as a slowdown; 2024 is the most recent year that can be treated as a reliable data point.
G05D, control of non-electric variables, appears in 65.2% of the 158 records and is by far the most heavily claimed class. B25J (manipulators & robots) and G01S (radar, sonar & positioning) each sit at 21.5%, with G01C (distance, navigation & gyroscopes) close behind at 20.9%. AI- and vision-related classes such as G06T, G06N and G06V each cover 10-15% of records, indicating that navigation control logic is more densely claimed than the underlying perception or AI layers.
The composition data points toward sensing- and AI-adjacent classes as comparatively less claimed: G06F, G06V and G06N each sit under 15% of the 158 records, versus 65.2% for G05D control claims. Combined with a long tail where the top 10 assignees hold only 35.4% of filings, there is room for narrowly scoped claims in perception-model integration or AI-assisted map correction that do not directly overlap the dense G05D control layer. Any specific claim should still be checked against the most-cited records in this landscape before drafting.
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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.