Papers
3
Total Citations
27
H-Index
2
About
Rafael Carbonell is a leading researcher in mobile robotics and networked control systems, with a focus on advancing autonomous vehicle navigation under real-world constraints. His work centers on path-following control for holonomic and nonholonomic mobile robots, particularly those equipped with Mecanum wheels, addressing critical challenges in sensor fusion, communication efficiency, and system robustness. Carbonell’s most cited paper (2022, 19 citations) introduces a nonuniform dual-rate extended Kalman-filter-based sensor fusion method for holonomic robots, enabling precise path-following despite varying sensor output rates. He further extends this work with a resource-efficient networked control system (2024, 6 citations) that integrates Kalman filtering, dual-rate sampling, and event-triggered communication to reduce bandwidth usage while maintaining control performance. His recent contributions (2024, 2 citations) tackle time-varying delays and input saturation in nonholonomic robots, offering a simpler, smooth static nonlinear control synthesis validated experimentally. Carbonell’s research is notable for its practical experimental validation and its systematic approach to bridging theoretical control design with real-world implementation, making significant strides toward reliable, efficient autonomous systems in constrained environments.
Research Focus
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Top Papers
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