Simranjit Singh

Bennett University

Papers

1

Total Citations

20

H-Index

1

About

Simranjit Singh is a researcher at the forefront of human-robot collaboration, with a primary focus on enhancing the perceptual capabilities of collaborative robots (cobots). His work centers on developing efficient, real-time surface detection algorithms that allow robots to safely and intuitively interact with their environment and human coworkers. Singh’s most-cited paper, "Efficient surface detection for assisting Collaborative Robots" (2022), has garnered 20 citations, establishing a foundational technique for improving robotic spatial awareness in shared workspaces. This contribution is critical for advancing Industry 5.0, where seamless human-robot teamwork is essential. By enabling cobots to dynamically recognize and adapt to surfaces, Singh’s research directly addresses key challenges in manufacturing safety and precision. His work is notable for bridging computer vision and robotics, offering practical solutions that reduce computational load while maintaining high accuracy. As a rising voice in collaborative robotics, Singh’s innovations are paving the way for more responsive and trustworthy robotic assistants, making his research a valuable resource for students and engineers aiming to build the next generation of intelligent, human-aware automation systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
20
Total Citations
20
Avg Citations/Paper
🏆 Most Cited Paper
Efficient surface detection for assisting Collaborative Robots
20 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Bennett University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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