Jinlong Piao
Papers
13
Total Citations
163
H-Index
8
About
Jinlong Piao is a leading researcher in the field of cable-driven parallel robots (CDPRs), with a focus on enabling these systems for high-payload, large-workspace industrial applications. His work addresses fundamental challenges in CDPR control, including cable tension estimation, viscoelastic cable modeling, and precise position control. Piao’s major contributions include developing an artificial neural network trained by force sensor measurements for indirect force control, which overcomes friction and unmodeled cable properties (36 citations). He also pioneered open-loop position control using a viscoelastic cable model for polymer cables, crucial for high-payload workspaces (25 citations). His research extends to bilateral teleoperation, where one CDPR controls another for intuitive remote manipulation (18 citations), and fine manipulation tasks like peg-in-hole assembly (20 citations). Piao has also solved the pulley inclusion problem with extended kinematics and a twin-pulley mechanism (13 citations), and developed a polymer cable creep model for heavy payload applications (12 citations). With over 150 total citations, his work is foundational for advancing CDPRs in logistics automation, high-speed material handling, and remote manipulation, making him a key figure in robotic systems for industrial automation.
Research Focus
Key Achievements
Top Papers
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- 5A Cable-driven Parallel Robot for High-rack Logistics Automation15 citations · 2024
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- 9Development of a high payload cable-driven parallel robot5 citations · 2017
- 10Vibration Analysis of Planar Cable-Driven Parallel Robot Configurations4 citations · 2016