Monimoy Bujarbaruah

University of California, Berkeley

Papers

3

Total Citations

10

H-Index

3

About

Monimoy Bujarbaruah is a robotics researcher whose work lies at the critical intersection of human-robot collaboration, safe autonomy, and learning-based control. His research focuses on enabling robots to operate safely and effectively alongside humans in shared, dynamic environments. Bujarbaruah’s major contributions include developing a decentralized leader-follower framework for collaborative robotics, where robots can sense and react to obstacles without explicit communication, and a trust-driven role adaptation strategy for human-robot teams that ensures safe transportation of objects while respecting each agent’s constraints. He has also tackled complex manipulation tasks, such as learning to play the cup-and-ball game from noisy camera observations, demonstrating how learning-based control can handle nonlinear dynamics and precise positioning. With over 10 citations across his most-cited works, Bujarbaruah’s research is gaining traction for its practical approach to real-world robotics challenges. His work on trust-driven adaptation is particularly notable for its potential to make human-robot collaboration more intuitive and reliable, paving the way for safer industrial and service robotics applications.

Research Focus

Key Achievements

3
H-Index
3
Papers
10
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Learning Environment Constraints in Collaborative Robotics: A Decentralized Leader-Follower Approach
4 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: University of California, Berkeley

Top Papers

  1. 1
  2. 2
  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago