Company Filing History:
Years Active: 2025
Title: Durgesh Kalwar: Innovator in Robotic Navigation
Introduction
Durgesh Kalwar is a notable inventor based in Thane West, India. He has made significant contributions to the field of robotics, particularly in the area of reinforcement learning and robotic navigation. His innovative approach has the potential to enhance the efficiency and effectiveness of mobile robots in various applications.
Latest Patents
Durgesh Kalwar holds a patent titled "Method and system for reinforcement learning and dual channel action embedding based robotic navigation." This patent presents a Reinforcement Learning (RL) based architecture designed to efficiently learn action embeddings in a low-dimensional space. The system is capable of receiving a goal for a mobile robot to reach while obtaining its current location. It utilizes RL techniques to gather current transition dynamics associated with multiple directional actuators. The architecture computes a plurality of embeddings based on the robot's current location and transition dynamics using a trained Dual Channel Training (DCT) based autoencoder decoder model. Ultimately, it calculates a displacement vector for the robot's navigation based on these embeddings.
Career Highlights
Durgesh Kalwar is currently employed at Tata Consultancy Services Limited, where he applies his expertise in robotics and artificial intelligence. His work focuses on developing advanced systems that leverage machine learning techniques to improve robotic functionalities. His innovative contributions have positioned him as a key player in the field.
Collaborations
Durgesh has collaborated with talented coworkers such as Harshad Khadilkar and Hardik Meisheri. Their combined efforts contribute to the advancement of technology in their respective projects.
Conclusion
Durgesh Kalwar's work in robotic navigation through reinforcement learning showcases his innovative spirit and dedication to advancing technology. His contributions are paving the way for more efficient robotic systems in the future.