Tokyo, Japan

Yoji Uno

This inventor holds 1 USPTO granted patent. Top assignee: Atr Auditory and Visual Perception Research Laboratories. Active years: 1991.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Yoji Uno. Retrieved from https://idiyas.com/inventor/yoji-uno

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

Calculating rank

% Patents Active = 100.0

Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 98(Granted Patents)


Company Filing History:


Years Active: 1991

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1 patent (USPTO):Explore Patents

Title: Yoji Uno: Innovator in Movement Trajectory Generation

Introduction

Yoji Uno is a prominent inventor based in Tokyo, Japan. He has made significant contributions to the field of dynamical systems through his innovative patent. His work focuses on generating movement trajectories using advanced neural network techniques.

Latest Patents

Yoji Uno holds a patent for a "Movement trajectory generating method of a dynamical system." This invention utilizes neural network units, which include a cascade connection of multiple layers, to learn a vector field of differential equations that represent the forward dynamics of a controlled object. The system ensures smooth movement while minimizing energy dissipation, allowing for effective trajectory formation and control input.

Career Highlights

Uno is associated with Atr Auditory and Visual Perception Research Laboratories, where he applies his expertise in neural networks and dynamical systems. His innovative approach has positioned him as a key figure in the research community.

Collaborations

Yoji Uno has collaborated with notable researchers, including Mitsuo Kawato and Yoshiharu Maeda. These partnerships have further enhanced his work and contributed to advancements in the field.

Conclusion

Yoji Uno's contributions to movement trajectory generation highlight his innovative spirit and dedication to advancing technology. His work continues to influence the field of dynamical systems and neural networks.

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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