Antonio Rodríguez-Díaz

Universidad Autónoma de Baja California, Universidad Andrés Bello

Papers

Total Citations

102

H-Index

About

Antonio Rodríguez-Díaz is a leading researcher in computational intelligence and autonomous robotics, whose work bridges fuzzy logic systems and bio-inspired optimization algorithms. His most impactful contribution, with 94 citations, is a pioneering hybrid framework that dynamically adapts the parameters of Bee Colony Optimization (BCO) using Type-1, Interval Type-2, and Generalized Type-2 Fuzzy Logic Systems to control the trajectory of autonomous mobile robots. This work demonstrates how fuzzy systems can enhance the adaptability and performance of swarm intelligence in real-world navigation tasks. More recently, Rodríguez-Díaz has advanced the field of pathfinding with his 2021 study on any-angle path planning using 2k neighborhoods, showing that subgoal graphs—a preprocessing technique originally designed for 8-connected grids—can be efficiently adapted to larger neighborhoods, enabling faster and near-optimal robot navigation. His research sits at the intersection of fuzzy control, optimization, and autonomous systems, offering practical solutions for mobile robot trajectory planning and grid-based pathfinding. Rodríguez-Díaz’s work is essential reading for students and researchers interested in hybrid intelligent systems, swarm robotics, and computational navigation algorithms.