Samar Bhattacharya

Jadavpur University

Papers

8

Total Citations

151

H-Index

7

About

Samar Bhattacharya is a prominent robotics researcher whose work centers on multi-robot systems, swarm robotics, and autonomous navigation. His research has made significant contributions to the fields of formation control, path planning, and obstacle avoidance, establishing him as a key voice in cooperative mobile robotics. Bhattacharya's most influential work, "Leader-Follower Formation Control Using Artificial Potential Functions" (2012, 37 citations), introduced a novel kinematic approach for coordinating groups of differentially driven wheeled mobile robots — a foundational contribution that continues to inform modern formation control strategies. Building on this, he pioneered virtual-region-based shape control methodologies, enabling robot swarms to navigate dynamically through unknown, obstacle-occluded environments with remarkable adaptability, as demonstrated across multiple highly cited studies from 2018 to 2021. His integration of bio-inspired evolutionary algorithms — including Bacterial Foraging Optimization and Particle Swarm Optimization — into swarm coordination reflects his commitment to intelligent, nature-inspired solutions for complex robotic challenges. His 2019 work further advanced the field by incorporating sliding mode control for robust non-holonomic robot formations. With a growing citation record exceeding 150 across his top publications, Bhattacharya's research offers invaluable frameworks for students and engineers working on autonomous multi-robot systems in real-world environments.

Research Focus

Key Achievements

7
H-Index
8
Papers
151
Total Citations
19
Avg Citations/Paper
🏆 Most Cited Paper
Leader-follower formation control using artificial potential functions: A kinematic approach
37 citations · 2012
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Jadavpur University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago