Abhinav Khare

Indian Institute of Information Technology Allahabad

Papers

Total Citations

H-Index

About

Abhinav Khare’s research lies at the intersection of machine learning and autonomous robotics, with a particular focus on goal-seeking navigation for mobile robots. 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. Khare’s contribution proposes a learning-based framework that enables robots to navigate toward a defined target while dynamically avoiding obstacles, bridging the gap between reactive control and goal-oriented planning. Though his citation count is modest—with 3 citations for his leading paper—his work is foundational for researchers seeking to integrate reinforcement learning and path planning in real-world robotic systems. By tackling the challenge of precise goal-seeking behavior, Khare has opened avenues for more intelligent, adaptive mobile robots capable of operating in cluttered, unstructured environments. His research is especially relevant for students and engineers working on autonomous navigation, offering a clear, implementable approach to a problem that remains central to modern robotics.