Geetanjali Singh
Papers
1
Total Citations
5
H-Index
1
About
Geetanjali Singh is a researcher in robotics and computational intelligence, with a primary focus on path planning and optimization algorithms. Her most cited work, "Shuffled teaching learning-based algorithm for solving robot path planning problem" (2020, 5 citations), introduces a novel metaheuristic approach that enhances the efficiency of autonomous navigation in complex environments. By adapting the teaching-learning-based optimization (TLBO) framework with a shuffled strategy, Singh addresses critical challenges in robot motion planning, such as obstacle avoidance and energy minimization. This contribution is particularly valuable for applications in industrial automation, search-and-rescue missions, and autonomous vehicles. Despite the early stage of her citation impact, her work demonstrates a strong potential for advancing practical robotics solutions. Singh’s research bridges theoretical optimization methods with real-world robotic systems, offering a scalable and computationally efficient alternative to traditional path planning techniques. Her achievements highlight a promising trajectory in the intersection of artificial intelligence and robotics, making her a notable emerging voice in the field.
Research Focus
Key Achievements
Top Papers
- 1