Papers
8
Total Citations
47
H-Index
4
About
Yilin Yu is a robotics researcher whose work focuses on motion planning, control, and human-robot interaction for redundant and dual-arm robotic systems. Their major contributions include developing advanced algorithms for robot control and coordination, such as an improved particle swarm optimization (PSO) for pipeline robot adsorption control (22 citations) and a discrete-time zeroing neural network for solving time-dependent constrained nonlinear equations in dual-arm systems (6 citations). Yu has also proposed adaptive noise rejection strategies for cooperative motion control (5 citations) and acceleration-level repetitive motion planning schemes for redundant manipulators (4 citations). Their recent work on robust myoelectric gesture recognition (2025, 4 citations) enhances human-robot interaction reliability. Additional notable achievements include integration-enhanced repetitive path planning for omnidirectional mobile manipulators (3 citations) and synchronous motion planning with joint constraints for dual-arm robots (2 citations). With a portfolio spanning from 2020 to 2025, Yu’s research demonstrates a sustained focus on practical, real-time solutions for complex robotic systems, making significant strides in improving robot autonomy, coordination, and user-friendly interaction.
Research Focus
Key Achievements
Top Papers
- 1Adsorption control of a pipeline robot based on improved PSO algorithm22 citations · 2020
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