LiDAR-Camera Calibration Patents: Who Leads, Where the Gaps Are 2026
Filing growth compares 2021 (3 records) with 2024 (3) — 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.
What this landscape covers
LiDAR-camera extrinsic calibration is the step that establishes a fixed geometric relationship between a vehicle’s ranging sensors and its cameras, so that point-cloud data and image data can be fused into a single coordinate frame. This dataset tracks 21 published patent records filed against search terms covering LiDAR-camera calibration, extrinsic sensor calibration, camera-LiDAR alignment and multimodal sensor calibration, filtered to autonomous and automated vehicle applications. The scope runs from 2015 through the 2026-07-31 cut-off.
Because the field is narrow and recent, the record count is small enough that a single company's filing pattern or a single well-cited application can shift the picture. Read the rankings and shares below as directional signals inside a young, still-consolidating claim space rather than as a mature, saturated one.
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Filing trend and technology composition
Two views of the same 21 records: how filing has moved year over year, and which IPC subclasses the claims actually sit in.
Filing trend, 2017-2026
Filing was at zero in 2017, rose to a peak of 10 records in 2022, and the 2021-to-2024 span shows 0% growth (3 records in 2021, 3 in 2024). Treat 2025 and 2026 as undercounted: publication lags filing by roughly 18 months, so recent-year totals will keep rising as more applications publish.
IPC subclass composition
G01S (radar, sonar and positioning) covers 71.4% of the 21 records, by far the densest single class. B60W (joint vehicle control) and G06V (image/video recognition) each cover 23.8%, G06T (image data processing) 19.0%, with G01C, G05D, G01B and G05B each under 10%. Because records can carry multiple classes, these shares add to more than 100% and should not be summed.
Shares are the percentage of the 21 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Autonomous Driving — LiDAR–Camera Extrinsic Calibration Patent Landscape with Eureka
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Try EurekaRepresentative filing and most-cited records
Sensor calibration during transport (US20230166758A1, GM Cruise Holdings)
Systems and methods are provided for calibrating vehicle sensors while a vehicle is being transported from one location to another. In particular, instead of using a dedicated calibration facility, systems and methods are provided for using mapped features to perform extrinsic sensor calibration while transporting the vehicle on an open-bed truck, train, or other open-bed vehicle hauler. During transport, a known distance between the vehicle sensor and a mapped target is determined, and compared to a measured distance between the vehicle sensor and the mapped target. The vehicle sensor is calibrated based on the comparison.Filed by GM Cruise Holdings, published 2023-06-01.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20210190922A1 | Automatic autonomous vehicle and robot lidar-camera extrinsic calibration | 35 |
| 2 | US20210239793A1 | High precision multi-sensor extrinsic calibration via production line and mobile station | 30 |
| 3 | US20230145082A1 | System and method for automated extrinsic calibration of lidars, cameras, radars and ultrasonic sensors on ve… | 9 |
| 4 | US20240144694A1 | Systems and methods for calibration and validation of non-overlapping range sensors of an autonomous vehicle | 9 |
| 5 | US20240142588A1 | Systems and methods for calibration and validation of non-overlapping range sensors of an autonomous vehicle | 7 |
| 6 | US20240142587A1 | Systems and methods for calibration and validation of non-overlapping range sensors of an autonomous vehicle | 7 |
| 7 | US11892560B2 | High precision multi-sensor extrinsic calibration via production line and mobile station | 7 |
| 8 | US20230166758A1 | Sensor calibration during transport | 5 |
| 9 | US11520024B2 | Automatic autonomous vehicle and robot LiDAR-camera extrinsic calibration | 5 |
| 10 | WO2023081870A1 | System and method for automated extrinsic calibration of lidars, cameras, radars and ultrasonic sensors on ve… | 3 |
Citation counts inside this searched corpus favour older filings and should be read as a signal of influence, not of current commercial weight.
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Browse MCP servers →What the numbers mean for a filing decision
Three read-throughs from the trend, the class composition and the citation table.
Filing has held steady, not fallen
The 2021-to-2024 span shows flat filing at 3 records each end, with a peak of 10 in 2022 in between. Because publication lags filing by roughly 18 months, the low counts in 2025 and 2026 are an artefact of the cut-off, not evidence of a cooling field.
Positioning claims dominate the class map
G01S — radar, sonar and positioning — touches more than seven in ten of the 21 records. Joint vehicle control (B60W) and image recognition (G06V) each sit near a quarter of records, meaning most activity clusters around a small set of adjacent classes rather than spreading evenly.
Two early filings anchor the citation graph
The most-cited record, on lidar-camera extrinsic calibration for autonomous vehicles and robots, draws 35 citations; a second record on production-line multi-sensor calibration draws 30. Both predate the 2022 filing peak, consistent with older records accumulating more citations simply by being searchable longer.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to autonomous driving — lidar–camera extrinsic calibration patent landscape, with the prior art for and against each one.
Where to take this analysis
The dataset points to a few concrete next steps for teams deciding where to file or partner.
Map claims against the G01S cluster
Before drafting new positioning or ranging claims, check them against the 71.4% of records already sitting in G01S — the densest single class in this landscape.
Explore IPC overlap in Eureka →Track the leading filer's continuations
The top-ranked assignee holds 6 of 21 records; monitoring its continuation and divergent filings is the fastest way to anticipate where its claim scope moves next.
Set up assignee tracking →Revisit the trend after the lag window closes
2025 and 2026 filings are still publishing. Re-run the trend analysis in 12-18 months to see the true trajectory past the 2022 peak.
Save this search in Eureka →Common questions on this landscape
This landscape tracks 21 published patent records against a search combining LiDAR-camera calibration, extrinsic sensor calibration, camera-lidar alignment and multimodal sensor calibration terms, filtered to autonomous and automated vehicle applications. The scope runs from 2015 through a 2026-07-31 cut-off. It is a narrow, purpose-built search rather than a count of every sensor-calibration patent in the automotive field, so broader searches will return larger numbers.
The dataset returns a ranking of 9 companies, with the leading assignee holding 6 records and the fifth-placed company holding 2. The named filers span traditional automakers, an autonomous-vehicle unit, a heavy-vehicle maker, a robotics-calibration specialist and technology suppliers, indicating the field is being staked out by a mix of incumbents and specialists rather than dominated by one type of player. There is no basis in this data for a stated concentration percentage, so treat the leader's position as a lead, not a lock.
Filing peaked at 10 records in 2022 and the comparable 2021-to-2024 span shows 0% growth, holding at 3 records at each end. Because publication typically lags filing by around 18 months, the lower counts visible in 2025 and 2026 reflect applications still working through the pipeline rather than a genuine drop in activity. A fair read is that filing has plateaued after its 2022 peak rather than declined.
G01S, covering radar, sonar and positioning, appears in 71.4% of the 21 records and is by far the densest class in this landscape. B60W (joint vehicle control) and G06V (image/video recognition) each appear in 23.8%, with G06T (image data processing), G01C (navigation and gyroscopes), G05D, G01B and G05B trailing behind. Because a single record can carry several IPC classes, these shares add to more than 100% and should be read individually, not summed.
Relative to the dense G01S positioning cluster, sub-areas such as non-overlapping field-of-view sensor validation, in-transit or transport-based calibration workflows, joint radar-camera-ultrasonic extrinsic solving, and production-line mobile calibration stations carry comparatively few filings in this dataset. These are plausible areas for a first-mover claim, though the small overall record count means a competitor could close the gap with a single well-drafted filing, so any freedom-to-operate view here should be revisited regularly.
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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.