MENLO PARK, Calif., Sept. 4, 2024 - 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:
|
Number |
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.