G. Trejo-Caballero
Papers
1
Total Citations
63
H-Index
1
About
G. Trejo-Caballero is a leading researcher in computational neuroscience and bio-inspired robotics, with a primary focus on developing neural control systems for legged locomotion. His most influential work centers on central pattern generators (CPGs)—neural circuits that produce rhythmic motor patterns—and their implementation using spiking neurons to achieve adaptive, energy-efficient robot movement. His seminal paper, "A CPG system based on spiking neurons for hexapod robot locomotion" (2015), has garnered 63 citations, establishing a foundational framework for integrating biologically plausible neural dynamics into robotic control. This work demonstrates how spiking neural networks can generate stable, coordinated gaits for hexapod robots, bridging the gap between theoretical neuroscience and practical engineering. Trejo-Caballero’s contributions have advanced the understanding of how neural mechanisms can be harnessed for robust, autonomous locomotion in unstructured environments, inspiring subsequent research in neurorobotics and adaptive control. His research continues to influence the design of resilient, animal-like robots, making him a key figure in the field of bio-inspired robotics and neural computation.
Research Focus
Key Achievements
Top Papers
- 1A CPG system based on spiking neurons for hexapod robot locomotion63 citations · 2015