Papers
20
Total Citations
303
H-Index
10
About
Zhifeng Liu is a robotics and mechanical engineering researcher whose work spans intelligent robotic assembly, robot kinematics, and precision transmission systems. His research primarily addresses the challenge of automating complex assembly operations in industrial environments, with particular emphasis on peg-in-hole assembly, bolt fastening, and screw disassembly tasks. Liu's contributions to robot-guided assembly are notable: his noncontact control strategy for circular peg-in-hole assembly (2022, 42 citations) introduced a hybrid vision-guided approach that overcomes the efficiency and adaptability limitations of conventional methods, while his comprehensive review of intelligent bolt assembly under complex conditions (2019, 26 citations) has become a valuable reference for researchers in the field. Beyond assembly automation, Liu has made significant contributions to robot motion planning and collision detection, developing a pseudo-distance algorithm for manipulator safety (2020, 40 citations) and advancing trajectory planning through screw theory (2018, 27 citations). His work on harmonic drives and strain wave gearing — including dynamic transmission error analysis and flexspline load modeling — reflects deep expertise in precision robotic transmission components. With over 240 cumulative citations across his most-cited works alone, Liu has established himself as an influential voice at the intersection of intelligent robotics, mechanical design, and industrial automation.
Research Focus
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