Denver, CO, United States of America

Harrison A Brown

This inventor holds 1 USPTO granted patent. Top assignee: Raytheon Company. Active years: 2024.


% Patents Active = 100.0

Average Co-Inventor Count = 2.0

ph-index = 1


Company Filing History:


Years Active: 2024

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1 patent (USPTO):Explore Patents

Title: Innovations of Harrison A. Brown in Machine Learning for Trajectory Planning

Introduction

Harrison A. Brown is an accomplished inventor based in Denver, CO. He has made significant contributions to the field of machine learning, particularly in trajectory planning. His innovative approach has led to the development of a patent that enhances the efficiency of orbital maneuvers.

Latest Patents

Harrison A. Brown holds a patent for a method involving machine learning for trajectory planning. This patent discusses devices, systems, and methods aimed at improving trajectory planning. The method includes providing two of the following inputs: a first value indicating a change in velocity to alter an orbit of a first object to a transfer orbit, a second value indicating a range between the first object and a second object, or a third value indicating an altitude of the first object relative to a celestial body. The method utilizes a machine learning model to predict a holdout value, which is then provided to an orbital planner.

Career Highlights

Harrison is currently employed at Raytheon Company, where he applies his expertise in machine learning and trajectory planning. His work at Raytheon has positioned him as a key player in advancing technologies that support aerospace and defense applications.

Collaborations

Harrison collaborates with various professionals in his field, including his coworker Darrell Young. Their combined efforts contribute to the innovative projects at Raytheon Company.

Conclusion

Harrison A. Brown's contributions to machine learning and trajectory planning exemplify the impact of innovation in technology. His patent reflects a significant advancement in the field, showcasing the potential of machine learning to enhance orbital planning.

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