Omkar Chaubal

Narsee Monjee Institute of Management Studies

Papers

Total Citations

H-Index

About

Omkar Chaubal is a researcher in robotics and machine learning, with a focus on integrating computer vision and autonomous manipulation. His most-cited work, "Robotic Hand-Eye System Using Machine Learning" (2019), introduces a novel framework that combines deep learning algorithms with robotic control to enable precise, adaptive hand-eye coordination. This contribution addresses a key challenge in robotics: enabling systems to dynamically interpret visual data and adjust grasping or assembly actions in real time. While his citation count is currently modest (2 citations for this paper), the work lays a foundational approach for scalable, learning-based robotic interaction in unstructured environments. Chaubal’s research bridges theoretical machine learning models with practical hardware implementation, offering a pathway toward more intelligent and flexible automation. His efforts are particularly relevant for students and researchers exploring sensorimotor integration, reinforcement learning in robotics, or the deployment of AI in industrial and service robots. As the field advances, Chaubal’s early work signals a promising trajectory in developing robust, real-world robotic systems that learn from their surroundings.