Garima Singh
Papers
1
Total Citations
11
H-Index
1
About
Dr. Garima Singh is a leading researcher in computational intelligence and robotics, with a focus on bio-inspired algorithms for multi-robot motion planning. Her most influential work, "A hybridisation of Improved Harmony Search and Bacterial Foraging for multi-robot motion planning" (2012, 11 citations), introduces a novel algorithm that integrates the chemotactic behavior of the Bacterial Foraging Optimization Algorithm (BFOA) with the Improved Harmony Search (IHS) framework. This hybrid approach significantly enhances path planning efficiency and robustness in complex, dynamic environments. By demonstrating through extensive CEC-2005 benchmark simulations that the proposed method outperforms existing algorithms, Dr. Singh has contributed a powerful tool for autonomous systems. Her research bridges nature-inspired optimization and practical robotics, offering scalable solutions for multi-agent coordination. With 11 citations on this seminal paper, her work continues to influence studies in swarm robotics and metaheuristic optimization. Dr. Singh’s achievements underscore her role in advancing intelligent motion planning, making her a notable figure in the intersection of artificial intelligence and robotics engineering.
Research Focus
Key Achievements
Top Papers
- 1