Wenxiong Mo
Papers
4
Total Citations
8
H-Index
2
About
Wenxiong Mo is a researcher specializing in industrial robotics, with a focus on intelligent automation, robot control, and machine vision. His work addresses critical challenges in manufacturing, including compliance inspection, human-robot interaction, and autonomous path planning. Mo proposed a real-time wavelet transform inspection algorithm for switchgear circuit breaker trolley compliance, integrating Kalman filtering and wavelet decomposition to enhance robotic inspection accuracy. He also developed a phased optimization method for drag teaching without torque sensors, using disturbance observers to improve robot flexibility and ease of programming. In the domain of vision-guided robotics, Mo contributed methods for position and posture estimation of randomly placed workpieces, enabling more reliable grasping and assembly. Additionally, he advanced motion planning with an extended RRT-Connect algorithm that accelerates path generation and reduces cost for sorting robots. Each of his most-cited papers has garnered 2 citations, reflecting early but meaningful impact in applied robotics. Mo’s research bridges practical industrial needs with algorithmic innovation, offering solutions that improve efficiency, autonomy, and adaptability in automated manufacturing environments.
Research Focus
Key Achievements
Top Papers
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