Kavita Choudhary
Papers
2
Total Citations
22
H-Index
2
About
Kavita Choudhary’s research focuses on the intersection of metaheuristic optimization and robotic path planning, where she develops intelligent algorithms to help robots navigate from source to destination efficiently. Her major contributions lie in applying and comparing nature-inspired metaheuristic techniques—such as Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Bat Algorithm, and Cuckoo Search—to solve complex path planning problems. Her most-cited work, "A hybrid ACO-PSO technique for path planning" (2015), has garnered 15 citations and demonstrates how combining these algorithms can minimize travel distance, time, and the number of turns and moves. In a related study, she compared Bat Algorithm and Cuckoo Search for the same task, achieving 7 citations. Choudhary’s research is notable for its practical focus on real-world robotic navigation, offering computationally efficient solutions that guide the search process toward optimal paths. Her work is particularly valuable for students and researchers in robotics and swarm intelligence, providing clear benchmarks for algorithm performance. Through these contributions, she has established herself as a thoughtful investigator in the field of metaheuristic-based path optimization.
Research Focus
Key Achievements
Top Papers
- 1A hybrid ACO-PSO technique for path planning15 citations · 2015
- 2A Comparison between Bat Algorithm andCuckoo Search for Path Planning7 citations · 2015