MENLO
PARK, Calif., Sept. 4,
2024 /PRNewswire/ -- Cyngn Inc. (the "Company" or
"Cyngn") (Nasdaq: CYN) today announced the official granting of a
new patent, U.S. Patent No. 12,032,099, which introduces a method
to maintain the accuracy of data collected by an autonomous
vehicle's sensors as the vehicle moves.
At its core, the patent optimizes sensor data processing by
integrating advanced LiDAR and image technologies. By initially
capturing comprehensive environmental data, the system then
calculates and adjusts for any time delay between data acquisition
and processing. Crucially, it dynamically generates a motion model
based on real-time sensor movements across multiple axes, ensuring
precise predictions of future positions.
The significance of this patent lies in its ability to
significantly enhance the reliability and precision of sensor data
in autonomous vehicles and robotics by effectively compensating for
motion during data processing. This capability enables these
systems to operate with utmost accuracy in dynamic environments,
ultimately enhancing safety, efficiency, and empowering
better-informed decisions based on precise environmental data.
"The granting of our 20th U.S. patent underscores Cyngn's
ongoing commitment to advancing autonomous vehicle technologies,"
said Lior Tal, Chairman and Chief
Executive Officer of Cyngn. "Following the 16 U.S. patents granted
in 2023, this achievement reflects our team's commitment to
building out a robust patent portfolio to protect our intellectual
property."
The grant of this patent marks a significant milestone in
Cyngn's intellectual property strategy, further bolstering its
position in the AV industry. This success follows Cyngn's recent
patent issuance announcement for Patent 19.
Cyngn provides its customers a seamless way to adopt
self-driving technology into their operations without high upfront
costs.
Previous patents include:
|
Patent
Number
|
Title
|
Publication
Date
|
|
20.
|
US-12,032,099-B2
|
ADAPTIVE MOTION
COMPENSATION OF PERCEPTION CHANNELS
|
07/09/2024
|
|
19.
|
US-11,851,074-B2
|
SYSTEM AND METHODS OF
LARGE-SCALE AUTONOMOUS DRIVING VALIDATION
|
12/26/2023
|
|
18.
|
US-11,837,090-B2
|
SYSTEM AND METHODS OF
ADAPTIVE TRAFFIC RULE-BASED DECISION MAKING FOR AUTONOMOUS
DRIVING
|
12/5/2023
|
|
17.
|
US-11,837,089-B2
|
MODULAR EXTENSIBLE
BEHAVIORAL DECISION SYSTEM FOR AUTONOMOUS DRIVING
|
12/5/2023
|
|
16.
|
US-11,767,034-B2
|
SYSTEM AND METHOD OF
COMPUTATION ACCELERATION FOR AUTONOMOUS DRIVING SYSTEMS
|
9/26/2023
|
|
15.
|
US-11,760,368-B2
|
SYSTEM AND METHOD OF
SAME-LOOP ADAPTIVE SIMULATION FOR AUTONOMOUS DRIVING
|
9/19/2023
|
|
14.
|
US-11,747,454-B2
|
GRANULARITY-FLEXIBLE
EXISTENCE-BASED OBJECT DETECTION
|
9/5/2023
|
|
13.
|
US-11,745,762-B2
|
SYSTEM AND METHODS OF
ADAPTIVE TRAJECTORY PREDICTION FOR AUTONOMOUS DRIVING
|
9/5/2023
|
|
12.
|
US-11,745,747-B2
|
SYSTEM AND METHOD OF
ADAPTIVE DISTRIBUTION OF AUTONOMOUS DRIVING COMPUTATIONS
|
9/5/2023
|
|
11.
|
US-11,745,750-B2
|
SYSTEM AND METHOD OF
LARGE-SCALE AUTOMATIC GRADING IN AUTONOMOUS DRIVING USING A
DOMAIN-SPECIFIC LANGUAGE
|
9/5/2023
|
|
10.
|
US-11,679,726-B2
|
VEHICLE SENSOR
SYSTEMS
|
6/20/2023
|
|
9.
|
US-11,673,577-B2
|
SYSTEM AND METHODS OF
ADAPTIVE RELEVANCY PREDICTION FOR AUTONOMOUS DRIVING
|
6/13/2023
|
|
8.
|
US-11,668,833-B2
|
OBSTACLE DETECTION
SYSTEMS
|
6/6/2023
|
|
7.
|
US-11,651,583-B2
|
MULTI-CHANNEL OBJECT
MATCHING
|
5/16/2023
|
|
6.
|
US-11,614,527-B2
|
SELF-ADAPTIVE
LIDAR-CAMERA SYNCHRONIZATION SYSTEM
|
3/28/2023
|
|
5.
|
US-11,592,565-B2
|
FLEXIBLE MULTI-CHANNEL
FUSION PERCEPTION
|
2/28/2023
|
|
4.
|
US-11,555,928-B2
|
THREE-DIMENSIONAL
OBJECT DETECTION WITH GROUND REMOVAL INTELLIGENCE
|
1/17/2023
|
|
3.
|
US-11,372,115-B2
|
VEHICLE
LOCALIZATION
|
6/28/2022
|
|
2.
|
US-11,186,234-B2
|
VEHICLE SENSOR
SYSTEMS
|
11/30/2021
|
|
1.
|
US-11,169,271-B2
|
OBSTACLE DETECTION
SYSTEMS
|
11/9/2021
|
|
|
|
|
For a comprehensive view of Cyngn's patents focused on
modularity and flexibility of autonomous vehicle systems with
multiple sensor modalities and configurations, please visit the
USPTO.
About Cyngn
Cyngn develops and deploys scalable, differentiated autonomous
vehicle technology for industrial organizations. Cyngn's
self-driving solutions allow existing workforces to increase
productivity and efficiency. The Company addresses significant
challenges facing industrial organizations today, such as labor
shortages, costly safety incidents, and increased consumer demand
for eCommerce.
Cyngn's DriveMod Kit can be installed on new industrial vehicles
at end of line or via retrofit, empowering customers to seamlessly
adopt self-driving technology into their operations without high
upfront costs or the need to completely replace existing vehicle
investments.
Cyngn's flagship product, its Enterprise Autonomy Suite,
includes DriveMod (autonomous vehicle system), Cyngn Insight
(customer-facing suite of AV fleet management, teleoperation, and
analytics tools), and Cyngn Evolve (internal toolkit that enables
Cyngn to leverage data from the field for artificial intelligence,
simulation, and modeling).
Find Cyngn on:
- Website: https://cyngn.com
- Twitter: http://twitter.com/cyngn
- LinkedIn: https://www.linkedin.com/company/cyngn
- YouTube: https://www.youtube.com/@cyngnhq
Investor Contact:
Don
Alvarez
investors@cyngn.com
Media Contact:
Luke Renner
media@cyngn.com
Forward-Looking Statements
This press release contains forward-looking statements within
the meaning of the Private Securities Litigation Reform Act of
1995, Section 27A of the Securities Act of 1933, as amended, and
Section 21E of the Securities Exchange Act of 1934, as amended. Any
statement that is not historical in nature is a forward-looking
statement and may be identified by the use of words and phrases
such as "expects," "anticipates," "believes," "will," "will likely
result," "will continue," "plans to," "potential," "promising," and
similar expressions. These statements are based on management's
current expectations and beliefs and are subject to a number of
risks, uncertainties and assumptions that could cause actual
results to differ materially from those described in the
forward-looking statements, including the risk factors described
from time to time in the Company's reports to the SEC, including,
without limitation the risk factors discussed in the Company's
annual report on Form 10-K filed with the SEC on March 7,
2024. Readers are cautioned that it is not possible to predict or
identify all the risks, uncertainties and other factors that may
affect future results No forward-looking statement can be
guaranteed, and actual results may differ materially from those
projected. Cyngn undertakes no obligation to publicly update any
forward-looking statement, whether as a result of new information,
future events, or otherwise.
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