Sudipta Mukhopadhyay

About

Sudipta Mukhopadhyay is a researcher in robotics and artificial intelligence, with a primary focus on multi-robot systems, path planning, and behavior-based control architectures. His most notable contribution is a robust cooperative multi-robot path-planning approach designed for noisy environments, realized through particle swarm optimization. This work, published in 2010 and cited 6 times, demonstrates both centralized and distributed solutions, highlighting the resilience of his methods under real-world uncertainty. Mukhopadhyay also contributed to the theoretical foundations of behavior-based robotics, offering a comparative analysis of the Subsumption Architecture and Motor Schema Theory in the context of autonomous exploration. His 2009 paper, though with 2 citations, provides valuable insight into the ongoing shift from traditional Sense-Plan-Act paradigms to more adaptive, behavior-based systems. Through these works, Mukhopadhyay has helped advance the practical deployment of multi-robot teams in challenging, unpredictable settings, making his research relevant for students and engineers working on autonomous navigation and swarm intelligence.

Research Focus

Key Achievements

Top Papers

1. 1
   A robust cooperative multi-robot path-planning in noisy environment

   6 citations · 2010
2. 2
   A brief comparison between the Subsumption Architecture and Motor Schema Theory in light of Autonomous Exploration by Be- havior Based Robots

   2 citations · 2009

Key Collaborators

Contact & Links