Rikky R. P. R. Duivenvoorden
Papers
4
Total Citations
48
H-Index
3
About
Rikky R. P. R. Duivenvoorden is a robotics and control systems researcher whose work sits at the intersection of adaptive control, machine learning, and autonomous aerial vehicles. His research is primarily focused on developing robust control strategies that enable robots and automated systems to perform reliably in unknown, dynamic environments — a challenge central to the future of real-world robotics deployment. Duivenvoorden's most significant contributions lie in combining L₁ adaptive feedback with iterative learning control (ILC) to achieve high-precision trajectory tracking under disturbances, unmodeled dynamics, and parametric uncertainties. His 2018 paper on transfer learning for trajectory tracking, which introduced adaptive feedback mechanisms capable of generalizing across changing environments, has garnered 19 citations and represents a meaningful advance in intelligent motion control. His earlier 2017 theoretical work establishing formal proofs for this combined framework further cemented the approach's credibility, accumulating 15 citations. Beyond control theory, Duivenvoorden has made tangible contributions to the aerial robotics community through the Phoenix Drone project — a fully open-source, dual-rotor tail-sitter micro aerial vehicle designed for accessibility in research and education. With 12 citations, this platform reflects his commitment to democratizing robotics research tools and fostering collaborative innovation across the broader community.
Research Focus
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Top Papers
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