Mugdha Bakhale
Papers
1
Total Citations
11
H-Index
1
About
Mugdha Bakhale is a researcher in swarm robotics and computational intelligence, with a focus on optimizing multi-robot systems through bio-inspired algorithms. Her most cited work, "A Dynamic Inertial Weight Strategy in Micro PSO for Swarm Robots" (2019, 11 citations), introduces an adaptive particle swarm optimization (PSO) technique that dynamically adjusts inertial weights to improve the coordination and efficiency of miniature swarm robots. This contribution addresses a critical challenge in swarm robotics—balancing exploration and exploitation in real-time, resource-constrained environments. By refining PSO for micro-robotic platforms, Bakhale’s work has implications for applications ranging from environmental monitoring to disaster response. Her research bridges theoretical algorithm design and practical robotic deployment, offering scalable solutions for decentralized systems. With a growing citation footprint, Bakhale’s innovative approach to dynamic parameter tuning continues to influence studies in adaptive robotics and collective behavior. Her work stands as a valuable resource for students and researchers exploring the intersection of evolutionary computation and physical swarm intelligence.
Research Focus
Key Achievements
Top Papers
- 1A Dynamic Inertial Weight Strategy in Micro PSO for Swarm Robots11 citations · 2019