Santosh Narayan
Papers
2
Total Citations
9
H-Index
2
About
Santosh Narayan is at the forefront of advancing human-robot collaboration (HRC) and autonomous manufacturing, with a focus on solving real-world challenges in high-mix, low-volume production environments. His work bridges the gap between traditional industrial robotics and flexible, intelligent automation. Narayan’s most cited paper, “A Human Robot Collaboration Framework for Assembly Tasks in High Mix Manufacturing Applications” (2023, 6 citations), introduces a pioneering framework that enables safe and efficient collaboration between humans and robots, addressing the critical need for adaptability in modern assembly lines. He further pushes the boundaries of robotic autonomy with “Physics-Informed Learning to Enable Robotic Screw-Driving Under Hole Pose Uncertainties” (2023, 3 citations), where he integrates physics-based models with machine learning to allow robots to perform precision tasks despite positional inaccuracies—a significant leap for applications in aerospace, automotive, and electronics assembly. By tackling core issues like uncertainty and task allocation, Narayan’s research directly impacts the scalability of automation in industries requiring flexibility. His contributions are shaping the next generation of smart manufacturing, making him a key voice in the field of collaborative robotics.
Research Focus
Key Achievements
Top Papers
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- 2