Company Filing History:
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Years Active: 2019-2023
Title: Shun Suyama: Innovator in Robotics and Machine Learning
Introduction
Shun Suyama is a prominent inventor based in Yamanashi, Japan, known for his contributions to robotics and machine learning. With a total of six patents to his name, Suyama has made significant advancements in the field, particularly in the development of drive mechanisms and machine learning devices for robotic systems.
Latest Patents
One of Suyama's latest patents is a drive mechanism for a transfer tool. This innovative mechanism is designed to drive a swing axis and tilt the workpiece. It includes a motor, a speed reducer with an output shaft arranged in parallel to the swing axis, and a link mechanism that couples the swing axis with the output shaft. The link mechanism consists of multiple link portions that work together to facilitate the operation of the transfer tool.
Another notable patent is a machine learning device, robot system, and machine learning method for learning object picking operations. This device is capable of learning how a robot can pick up various objects placed randomly, including in a bulk-loaded state. It features a state variable observation unit that monitors the robot's state, an operation result obtaining unit that records the results of the picking operation, and a learning unit that correlates the robot's state with the outcomes of its actions.
Career Highlights
Suyama has worked with notable companies in the technology sector, including Fanuc Corporation and Preferred Networks, Inc. His experience in these organizations has allowed him to refine his skills and contribute to cutting-edge innovations in robotics and automation.
Collaborations
Throughout his career, Suyama has collaborated with talented individuals such as Takashi Yamazaki and Takumi Oyama. These partnerships have fostered a creative environment that has led to the development of groundbreaking technologies.
Conclusion
Shun Suyama is a distinguished inventor whose work in robotics and machine learning continues to influence the industry. His innovative patents and collaborations highlight his commitment to advancing technology and improving robotic systems.