Tianliang Hu
Papers
17
Total Citations
401
H-Index
12
About
Tianliang Hu is a prominent researcher in the field of robotics and intelligent manufacturing, whose work spans robotic process planning, motion control, and advanced manufacturing automation. His research addresses some of the most pressing challenges in industrial robotics, including trajectory planning, dynamic parameter identification, and robotic machining optimization. Hu's most influential contributions include developing a welding task data model for intelligent robotic process planning (72 citations) and a comprehensive posture optimization framework for robotic machining that accounts for both spindle weight and cutting forces (71 citations). These works reflect his sustained focus on improving the precision and intelligence of robotic manufacturing systems. His research on finite-time trajectory tracking control and model-assisted extended state observer-based computed torque control demonstrates deep expertise in robust robot motion control under real-world uncertainties and disturbances. Hu has also made meaningful contributions to emerging applications, including freeform surface laser treatment using NURBS interpolation, online chatter detection in robotic machining, and adaptive remanufacturing with laser cladding. His work on grasp detection in disordered manufacturing scenarios further highlights his engagement with AI-driven robotics. With over 335 cumulative citations across a decade of research, Hu stands as a significant voice shaping the future of intelligent robotic manufacturing.
Research Focus
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