Jayesh Patil

Indian Institute of Information Technology Allahabad

Papers

Total Citations

H-Index

About

Jayesh Patil’s research lies at the intersection of robotics and machine learning, with a focused interest in autonomous navigation and goal-seeking behavior. His most-cited work, “Learning the Goal Seeking Behaviour for Mobile Robots” (2018), addresses a critical gap in the literature: while machine learning has been extensively applied to obstacle avoidance and region-based navigation, its use for precise, goal-directed movement remains underexplored. Patil’s contribution introduces novel learning-based frameworks that enable mobile robots to navigate accurately toward defined targets, bridging the divide between reactive obstacle avoidance and deliberate goal achievement. Though his citation count is modest—3 citations for this key paper—his work is foundational for researchers seeking to integrate reinforcement learning and neural architectures into real-world robotic systems. Patil’s research is particularly valuable for students and engineers working on autonomous vehicles, service robots, and intelligent agents, as it provides a clear methodology for teaching machines not just to wander, but to purposefully seek and reach specific destinations. His efforts highlight a promising direction for more precise, adaptive, and intelligent robotic navigation.