Papers
14
Total Citations
421
H-Index
11
About
Zhaokun Zhang is a leading researcher in cable-driven parallel robots (CDPRs), with a focus on high-speed, translational, and application-specific designs. His major contributions span the full lifecycle of CDPR development—from optimal design and kinematic calibration to real-world deployment. Notably, his 2022 state-of-the-art review on CDPR theories and applications has garnered over 100 citations, establishing a foundational reference for the field. Zhang’s work on high-speed pick-and-place CDPRs, including the TBot and a 3-DOF translational robot, has achieved significant impact, with his 2019 optimization paper cited 79 times. He has advanced practical solutions such as a cable-driven robot for cleaning building exterior walls (30 citations) and introduced passive springs to simplify CDPR architecture while maintaining tension. His kinematic calibration method, which accounts for pulley kinematics (57 citations), addresses a critical accuracy challenge. More recently, Zhang has explored machine learning applications in parallel robots, signaling a forward-looking integration of AI. His research is distinguished by its blend of rigorous theoretical analysis, innovative mechanical design, and tangible engineering applications, making him a key contributor to the advancement of high-performance, lightweight robotic systems.
Research Focus
Key Achievements
Top Papers
- 1State-of-the-art on theories and applications of cable-driven parallel robots104 citations · 2022
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- 4Optimal Design of a High-Speed Pick-and-Place Cable-Driven Parallel Robot34 citations · 2017
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- 9Kinematic analysis of the X4 translational–rotational parallel robot14 citations · 2018
- 10Machine Learning Applications in Parallel Robots: A Brief Review12 citations · 2025