Saul Enrique Benitez-Garcia

Instituto Politécnico Nacional

Papers

5

Total Citations

34

H-Index

3

About

Saul Enrique Benitez-Garcia is a leading researcher in the optimization and control of robotic systems, with a primary focus on bipedal locomotion, manipulator stabilization, and robot–environment interaction. His most influential work introduces a Pareto optimal synthesis approach for eight-bar mechanisms using meta-heuristic multi-objective search, enabling efficient bipedal gait generation with reduced actuator complexity—a contribution that has garnered 12 citations and advanced the field of energy-efficient humanoid robotics. Benitez-Garcia has also made significant strides in event-triggered control (ETC), developing both event-triggered and periodic event-triggered control (PETC) strategies for robotic manipulators. These designs reduce computational and communication overhead by updating control signals only when necessary, achieving stabilization without continuous state monitoring. His PETC work, with 9 citations, and related studies on three-degree-of-freedom manipulators underscore his impact on real-time control efficiency. More recently, Benitez-Garcia has explored optimal tuning of robot–environment interaction controllers using bio-inspired differential evolution, demonstrating a commitment to safe, adaptive, and high-performance robotics. His cumulative work bridges theoretical control advances with practical robotic applications, making him a notable figure in modern robotics and automation research.

Research Focus

Key Achievements

3
H-Index
5
Papers
34
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Pareto optimal synthesis of eight-bar mechanism using meta-heuristic multi-objective search approaches: application to bipedal gait generation
12 citations · 2020
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Instituto Politécnico Nacional

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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