Lluvia Morales
Papers
1
Total Citations
7
H-Index
1
About
Lluvia Morales is a researcher specializing in computational intelligence, robotics, and optimization algorithms, with a particular focus on path planning for autonomous systems. Her most-cited work, "Path Planning for a Mobile Robot using Genetic Algorithm and Artificial Bee Colony" (2017, 7 citations), makes a significant contribution by systematically comparing two meta-heuristic techniques—Artificial Bee Colony (ABC) and Genetic Algorithm (GA)—for solving complex path planning problems. In this study, Morales validated both algorithms across ten distinct 2D maps featuring varied obstacle geometries and densities, providing critical insights into their relative performance in terms of efficiency and solution quality. This comparative analysis offers practical guidance for selecting appropriate optimization methods in real-world robotic navigation. Her research bridges theoretical algorithm development and applied robotics, demonstrating how nature-inspired approaches can enhance autonomous decision-making. While her citation count reflects the emerging nature of this work, the paper serves as a foundational reference for researchers exploring evolutionary and swarm-based path planning. Morales’ contributions are particularly valuable for students and engineers seeking to understand trade-offs between different optimization techniques in mobile robotics.
Research Focus
Key Achievements
Top Papers
- 1