Geovanni Flores-Caballero
Instituto Politécnico Nacional, Universidad Aeronáutica en Querétaro
Papers
2
Total Citations
23
H-Index
2
About
Geovanni Flores-Caballero is a researcher whose work centers on autonomous mobile robotics, with a particular focus on intelligent path-planning algorithms and optimization techniques. His research addresses one of the most fundamental challenges in robotics: enabling mobile robots to navigate complex environments safely, efficiently, and with minimal human intervention — capabilities critical for applications ranging from industrial automation to hazardous exploration. Flores-Caballero's most recognized contribution lies in developing and applying metaheuristic optimization strategies to the path-planning problem. His 2021 paper introduced a novel variable-length variant of Differential Evolution for mobile robot path planning, earning 13 citations and demonstrating how evolutionary algorithms can be tailored to solve the nuanced geometric and computational demands of navigation tasks. Building on this, his 2022 work extended these ideas into dynamic environments, proposing online metaheuristic optimization methods that allow robots to adapt their planned paths in real time as obstacles change — a significant step beyond traditional static scenario solutions, accumulating 10 citations. Together, these contributions reflect Flores-Caballero's commitment to bridging theoretical optimization with practical robotics applications, offering solutions that advance robot autonomy in real-world, unpredictable settings — making his work highly relevant to students and researchers in robotics, AI, and control systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2