Papers

7

Total Citations

75

H-Index

5

About

Juan Antonio Rojas-Quintero is a roboticist whose work bridges the mathematical elegance of differential geometry with the practical demands of humanoid robotics. His research centers on two interconnected domains: the optimal control of robotic manipulators and the development of sensor-rich heads for humanoid robots. In the realm of control theory, Rojas-Quintero has pioneered the application of Riemannian geometry to formulate covariant control equations, offering a mathematically rigorous framework for optimal robot motion. By reinterpreting Pontryagin’s Maximum Principle through a geometric lens, he has developed controllers that respect the intrinsic structure of robotic systems, with his most-cited work on this topic garnering 9 citations. Complementing this theoretical work, his comprehensive literature review on sensor heads for humanoid robots—his most impactful publication with 43 citations—established a foundational taxonomy of perception systems, highlighting vision as the dominant modality. Rojas-Quintero has also contributed to practical implementations, including the design of a real-time stereoscopic foveated vision system for humanoid platforms. His work uniquely positions him at the intersection of advanced control theory and embodied AI, making significant strides toward more perceptive and gracefully moving humanoid robots.

Research Focus

Key Achievements

5
H-Index
7
Papers
75
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
A literature review of sensor heads for humanoid robots
43 citations · 2021
📈 Most Prolific Year: 2021 (4 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: Ensenada Institute of Technology, Consejo Nacional de Humanidades, Ciencias y Tecnologías

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago