Kanchan Bakade

Narsee Monjee Institute of Management Studies

Papers

Total Citations

H-Index

About

Kanchan Bakade is a researcher whose work bridges robotics, machine learning, and intelligent systems. Her most-cited paper, "Robotic Hand-Eye System Using Machine Learning" (2019), introduces a novel framework that integrates computer vision and adaptive control to enhance robotic manipulation. This work, which has garnered 2 citations, demonstrates her early contributions to developing more autonomous and responsive robotic systems—a foundational step toward real-world applications in manufacturing and assistive technologies. Bakade’s research focuses on enabling machines to perceive and interact with their environments more naturally, leveraging machine learning algorithms to improve hand-eye coordination in robotic platforms. While her citation count is modest, her work represents a critical exploration of how learning-based approaches can overcome traditional limitations in robotic precision and adaptability. For students and researchers interested in the intersection of robotics and AI, Bakade’s study offers a clear, practical example of applying machine learning to solve complex sensorimotor challenges. Her contributions highlight the growing importance of data-driven methods in robotics, setting the stage for future innovations in autonomous systems.