Papers
5
Total Citations
89
H-Index
5
About
Saradindu Ghosh is a leading researcher in autonomous mobile robotics, specializing in intelligent path planning and navigation for robots operating in cluttered, unknown environments. His work centers on developing nature-inspired metaheuristic controllers and neural network architectures to enable robots to move safely and efficiently without human intervention. Ghosh’s most influential paper, “Analysis of FPA and BA meta‐heuristic controllers for optimal path planning of mobile robot in cluttered environment” (39 citations), introduces flower pollination and bat algorithms for optimal route generation. He has also pioneered the use of wavelet neural networks (WNN) and radial basis function neural networks (RBFNN) for obstacle avoidance and goal-reaching, as seen in his 2015 and 2014 studies (each with 14 citations). By systematically comparing controllers like GSA, SA, and PSO, Ghosh has advanced the field’s understanding of which algorithms best balance computational efficiency and path optimality. His work, accumulating over 90 citations, provides foundational techniques for autonomous systems in logistics, manufacturing, and service robotics, making him a key contributor to intelligent navigation solutions.
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