Papers
2
Total Citations
123
H-Index
2
About
J. M. Vazquez-Nicolas is a leading researcher in robotics and intelligent control systems, with a focus on enhancing the autonomy and reliability of robotic platforms. His major contributions lie at the intersection of advanced control theory and computer vision, particularly in the development of neural network-based compensation for industrial manipulators and autonomous inspection systems. His most cited work, "PD Control Compensation Based on a Cascade Neural Network Applied to a Robot Manipulator" (2020, 98 citations), addresses a critical limitation of traditional PID controllers—integral gain degradation over time—by introducing a cascade neural network that improves stability and bandwidth. This innovation has significant implications for long-duration industrial tasks. Additionally, his paper "Towards automatic inspection: crack recognition based on Quadrotor UAV-taken images" (2018, 25 citations) pioneers the use of quadrotor drones for building defect detection, reducing human risk and inspection costs. Vazquez-Nicolas’s work is notable for bridging theoretical control advances with practical robotic applications, making him a key figure in the push toward fully autonomous maintenance and manufacturing systems.
Research Focus
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Top Papers
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