Pittsburg, PA, United States of America

Shivam Vats


Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Innovations of Shivam Vats in Robotic Manipulation

Introduction

Shivam Vats is an accomplished inventor based in Pittsburg, PA (US). He has made significant contributions to the field of robotics, particularly in the area of controlling robotic manipulators. His innovative approach combines hierarchical reinforcement learning with practical applications in robotic control.

Latest Patents

Shivam Vats holds a patent for a "System and method for controlling a robotic manipulator based on hierarchical reinforcement learning of control policies." This patent describes a feedback controller designed to manage a robotic manipulator's tasks effectively. The controller utilizes a hierarchical reinforcement learning (HRL) neural network that includes both a nominal control policy and a recovery control policy. The recovery control policy is trained using a recovery policy reward, which is influenced by the nominal policy reward. This innovative system allows the robotic manipulator to perform tasks by selecting actions based on the trained policies, enhancing its operational efficiency. He has 1 patent to his name.

Career Highlights

Shivam Vats is currently employed at Mitsubishi Electric Research Laboratories, Inc. His work focuses on advancing robotic technologies and improving the functionality of robotic systems. His expertise in reinforcement learning has positioned him as a key player in the development of intelligent robotic solutions.

Collaborations

Shivam collaborates with fellow inventor Devesh Jha, contributing to innovative projects in the field of robotics. Their combined efforts aim to push the boundaries of what robotic systems can achieve.

Conclusion

Shivam Vats is a notable inventor whose work in robotic manipulation showcases the potential of hierarchical reinforcement learning. His contributions are paving the way for more advanced and efficient robotic systems.

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