Papers
12
Total Citations
619
H-Index
10
About
Erkan Kayacan is a robotics and control systems researcher whose work spans intelligent control theory, autonomous mobile robotics, and agricultural automation. He is best known for his foundational contributions to spherical rolling robot dynamics and control, with his 2011 and 2012 papers on decoupled modeling and adaptive neuro-fuzzy control accumulating over 260 citations combined — establishing him as a leading authority in this niche yet mathematically rich domain. His research skillfully bridges advanced control methodologies, including sliding-mode control, feedback linearization, and nonlinear model predictive control, with real-world robotic applications. A distinctive thread in Kayacan's later work is the deployment of learning-based control strategies across diverse robotic platforms — from 3D-printed field robots and aerial drones to reconfigurable autonomous vessels (Roboats). His contributions to agricultural robotics are particularly impactful, with highly cited work on high-throughput phenotyping robots for energy sorghum and corn stand counting systems, addressing critical challenges in precision agriculture and food security. His development of online learning algorithms that function without persistent excitation further demonstrates his commitment to practical, robust solutions. Across platforms and environments, Kayacan's research consistently pursues autonomous systems that are both theoretically rigorous and deployable in uncertain, real-world conditions.
Research Focus
Key Achievements
Top Papers
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- 3Modeling and control of a spherical rolling robot: a decoupled dynamics approach108 citations · 2011
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