M. Seetharama Bhat
Papers
2
Total Citations
13
H-Index
2
About
M. Seetharama Bhat is a researcher in robotics and motion planning, with a focus on sampling-based algorithms that enable autonomous systems to navigate complex environments. His work centers on improving the efficiency and reliability of probabilistic roadmap methods (PRM) and random walk strategies, which are fundamental to robot path planning in cluttered spaces. In his most-cited paper, "Analysis of Obstacle based Probabilistic RoadMap Method using Geometric Probability" (2014, 9 citations), Bhat provides a rigorous theoretical framework for understanding how obstacles affect the connectivity and success rates of PRM planners, offering insights that help practitioners design more robust navigation systems. His earlier work, "An Efficient Random Walk Strategy for Sampling Based Robot Motion Planners" (2010, 4 citations), introduces novel sampling techniques that reduce computational overhead while maintaining path quality. Though his citation counts are modest, Bhat’s contributions are valued for their analytical depth and practical relevance, particularly in advancing the theoretical underpinnings of motion planning. His research is a resource for students and engineers seeking to understand the geometric and probabilistic foundations of autonomous robot navigation.
Research Focus
Key Achievements
Top Papers
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- 2