Monica Sood

Papers

Total Citations

H-Index

About

Monica Sood is a researcher specializing in computational intelligence and optimal path planning, with a focus on swarm intelligence and hybrid metaheuristic algorithms. Her work addresses the critical challenge of determining collision-free, shortest, and efficient paths across diverse fields including robotics, transportation, bioinformatics, virtual reality, and computer-aided design. Sood’s major contributions lie in developing hybrid optimization techniques that combine algorithms such as the Bat Algorithm and Cuckoo Search to enhance path planning performance, as demonstrated in her most-cited 2019 paper, "Optimal Path Planning Using Swarm Intelligence Based Hybrid Techniques," which has garnered 29 citations. Her 2018 study on hybrid Bat and Cuckoo Search methods, with 10 citations, further advances this approach by improving solution quality and convergence speed. In her 2020 analysis of computational intelligence techniques for path planning (8 citations), she systematically evaluates various methods, providing a valuable resource for researchers. Sood’s work has significant implications for autonomous systems, simulation, and animation, establishing her as a key contributor to intelligent path planning solutions.