Dexu Bu

Papers

Total Citations

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About

Dexu Bu is a robotics researcher whose work focuses on adaptive control systems for specialized robotic platforms, particularly duct cleaning robots. His major contributions lie in developing intelligent control strategies that enable robots to operate reliably in constrained, uncertain environments. Bu’s most cited paper, “Adaptive robust control based on RBF neural networks for duct cleaning robot” (2015, 22 citations), introduced a neural-network-based approach to handle system uncertainties and external disturbances, significantly improving robot stability and precision. He further advanced this field with a task-space tracking control method using fuzzy wavelet neural networks (2019, 7 citations), which addressed the challenges of mobile manipulators navigating narrow ducts. Bu also explored visual servo systems, proposing a fuzzy cerebellar model articulation controller for robot vision (2012, 3 citations). His work bridges theoretical control engineering and practical robotics, offering solutions for maintenance automation in hazardous or inaccessible environments. With a cumulative citation count reflecting growing interest in autonomous service robots, Bu’s research is particularly relevant for students and engineers working on adaptive control, neural networks, and field robotics.