Papers
13
Total Citations
218
H-Index
8
About
Jorge Hermosillo is a versatile robotics and artificial intelligence researcher whose work spans autonomous navigation, nonholonomic control systems, cognitive robotics, and precision agriculture. He is perhaps best known for his foundational contributions to the CyCab platform — a bi-steerable, differentially flat robotic vehicle designed for safe autonomous navigation in pedestrian environments. His series of papers on the CyCab, including trajectory tracking via flatness-based feedback control and motion planning for bi-steerable cars, established important theoretical and practical frameworks for this class of nonholonomic systems, collectively earning well over 100 citations. Beyond vehicle robotics, Hermosillo has made meaningful contributions to cognitive robotics, exploring how artificial agents can develop internal models, sensory-motor schemes, and mental imagery for anticipatory behavior — work that bridges neuroscience-inspired theory and embodied AI. His 2016 paper on self-organized internal model architectures reflects a sustained interest in grounded cognition and biologically plausible computation. More recently, his research has extended into precision agriculture, with a highly cited 2019 study applying deep convolutional encoder-decoder networks to aerial fig plant segmentation, demonstrating his capacity to translate robotics expertise into impactful applied domains. With a citation portfolio exceeding 200, Hermosillo represents a productive bridge between theoretical robotics and emerging real-world applications.
Research Focus
Key Achievements
Top Papers
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- 4The Cycab robot: a differentially flat system22 citations · 2002
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- 7An autonomous car-like robot navigating safely among pedestrians10 citations · 2004
- 8Self Body Mapping in Mobile Robots Using Vision and Forward Models8 citations · 2012
- 9Motion planning for a Bi-steerable Car.7 citations · 2001
- 10Cycab bi-steerable cars: a new family of differentially flat systems6 citations · 2002