Alejandra Mancilla
Instituto Tecnológico de Tijuana, Tecnológico Nacional de México
Papers
4
Total Citations
45
H-Index
3
About
Alejandra Mancilla is a researcher specializing in intelligent control systems, computational intelligence, and autonomous robotics, with a particular focus on the intersection of fuzzy logic and population-based metaheuristics. Her work addresses one of the central challenges in modern robotics: designing controllers that are both high-performing and interpretable to human operators. Mancilla's most impactful contribution, "Optimal Fuzzy Controller Design for Autonomous Robot Path Tracking Using Population-Based Metaheuristics" (2022), has garnered 32 citations and demonstrates how evolutionary and swarm-based optimization techniques can automate the design of linguistically intuitive fuzzy controllers for autonomous vehicle path tracking. Building on this foundation, her subsequent research explores distributed and asynchronous computing frameworks to overcome the computational bottlenecks inherent in population-based optimization, reducing the burden of time-intensive simulations for engineers. Her 2023 work on distributed bioinspired methods with randomized parameters further pushes the boundaries of scalable controller optimization. Across her growing body of work, Mancilla consistently advances the practical deployment of intelligent, self-optimizing control systems, making her an emerging voice in autonomous systems research and bio-inspired computation.
Research Focus
Key Achievements
Top Papers
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