Papers
2
Total Citations
111
H-Index
2
About
Yuze Jiang is a leading researcher in robotic assembly and intelligent manufacturing, with a focus on bridging the gap between perception, planning, and execution in automated systems. His work centers on developing comprehensive strategies that integrate geometry perception, motion planning, and real-time evaluation to enable robots to perform complex assembly tasks with greater autonomy and precision. Jiang's most influential contribution is his landmark review, "A review of robotic assembly strategies for the full operation procedure: planning, execution and evaluation," which has garnered 97 citations and serves as a foundational reference for researchers and engineers in the field. This work systematically maps the entire assembly workflow, from task planning to performance assessment, offering a unified framework that has shaped subsequent research. In his more recent study, "Geometry perception and motion planning in robotic assembly based on semantic segmentation and point clouds reconstruction" (14 citations), Jiang advances the use of deep learning and 3D reconstruction to enhance robots' ability to perceive and adapt to unstructured environments. His research is notable for its practical impact on industrial automation, and he is recognized for his contributions to making robotic assembly more efficient, flexible, and intelligent.
Research Focus
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