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For the Inventor, By the Inventor

Palo Alto, CA, United States of America

Bartholomeus C Nabbe

This inventor holds 9 USPTO granted patents and 1 published patent application and 2 EPO patents. Top assignees: Aurora Operations, Inc., Aurora Innovation, Inc.. Active years: 2020-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Bartholomeus C Nabbe. Retrieved from https://idiyas.com/inventor/bartholomeus-c-nabbe

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

USPTO Granted Patents = 9 

% Patents Active = 100.0

 

Average Co-Inventor Count = 6.0

ph-index = 2

Forward Citations = 35(Granted Patents)


Company Filing History:

goldMedal7 out of 340 
 
Aurora Operations, Inc.
 patents
silverMedal2 out of 18 
 
Aurora Innovation, Inc.
 patents

Years Active: 2020-2026

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9 patents (USPTO):Explore Patents
1. 12535594 - Control of autonomous vehicle based on environmental object classification determined using phase coherent LIDAR data (2026-01-27),
2. 12304494 - Control of autonomous vehicle based on determined yaw parameter(s) of additional vehicle (2025-05-20),
3. 11964663 - Control of autonomous vehicle based on determined yaw parameter(s) of additional vehicle (2024-04-23),
4. 11933902 - Control of autonomous vehicle based on environmental object classification determined using phase coherent LIDAR data (2024-03-19),
5. 11654917 - Control of autonomous vehicle based on determined yaw parameter(s) of additional vehicle (2023-05-23),
6. 11550061 - Control of autonomous vehicle based on environmental object classification determined using phase coherent LIDAR data (2023-01-10),
7. 11358601 - Training machine learning model based on training instances with: training instance input based on autonomous vehicle sensor data, and training instance output based on additional vehicle sensor data (2022-06-14),
8. 10906536 - Control of autonomous vehicle based on determined yaw parameter(s) of additional vehicle (2021-02-02),
9. 10676085 - Training machine learning model based on training instances with: training instance input based on autonomous vehicle sensor data, and training instance output based on additional vehicle sensor data (2020-06-09),

Title: The Innovations of Bartholomeus C Nabbe

Introduction

Bartholomeus C Nabbe is a prominent inventor based in Palo Alto, California. He holds a total of eight patents, showcasing his significant contributions to the field of autonomous vehicle technology. His work focuses on enhancing the control and safety of autonomous vehicles through innovative methods.

Latest Patents

One of Nabbe's latest patents involves the control of autonomous vehicles based on determined yaw parameters of additional vehicles. This patent describes a method for determining an instantaneous vehicle characteristic, such as yaw rate, of an additional vehicle that is not being controlled autonomously. The autonomous vehicle can adapt its steering, acceleration, and deceleration based on the determined characteristics of the additional vehicle. The technology utilizes data from advanced Light Detection and Ranging (LIDAR) components, including phase coherent LIDAR monopulse and frequency-modulated continuous wave (FMCW) LIDAR components.

Career Highlights

Throughout his career, Nabbe has worked with notable companies in the autonomous vehicle sector, including Aurora Operations, Inc. and Aurora Innovation, Inc. His experience in these organizations has allowed him to develop cutting-edge technologies that push the boundaries of vehicle automation.

Collaborations

Nabbe has collaborated with talented individuals in the industry, including Warren Smith and Ethan Eade. These partnerships have contributed to the advancement of his innovative projects and patents.

Conclusion

Bartholomeus C Nabbe's work in the field of autonomous vehicles exemplifies the impact of innovation on transportation technology. His patents and collaborations highlight his commitment to improving vehicle safety and control through advanced methodologies.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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