Shuibiao Chen

Guilin University of Electronic Technology, Guangdong University of Technology

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About

Shuibiao Chen is a researcher at the forefront of intelligent manufacturing and robotics, with a focus on advancing automation through sensor integration and machine learning. His work centers on three key areas: precision welding automation, robotic calibration, and bio-inspired robotics. Chen’s most impactful contribution is his 2022 study on narrow weld joint recognition using laser profile sensors, which has garnered 17 citations and addresses a critical bottleneck in intelligent robot welding systems. By enabling accurate detection of deformations in tight spaces, this work directly enhances the reliability of automated manufacturing. In 2024, he advanced the field further by proposing a unified framework for hand-eye parameter estimation and line-structured light scanning calibration, simplifying complex multi-step processes into a single, efficient solution. Earlier, Chen explored robotic fish control, developing an action control model based on an improved extreme learning machine optimized by particle swarm algorithms. This model, cited 4 times, allows for rapid, precise state prediction and adjustment, demonstrating his versatility in applying machine learning to both industrial and bio-inspired systems. Chen’s research consistently bridges theoretical innovation with practical application, making him a notable contributor to the evolution of smart robotics.