Papers
1
Total Citations
11
H-Index
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About
Yilin Lv is a researcher in robotics and intelligent control systems, with a primary focus on locomotion planning and optimization for specialized robotic platforms. Their most-cited work, "Research on Gait Trajectory Planning of Wall-Climbing Robot Based on Improved PSO Algorithm" (2024, 11 citations), introduces a novel approach to enhancing the efficiency and stability of wall-climbing robots. By integrating an improved Particle Swarm Optimization (PSO) algorithm into gait trajectory planning, Lv addresses critical challenges in robot mobility on vertical surfaces—such as energy consumption, trajectory smoothness, and adaptability to complex environments. This contribution is significant for advancing autonomous inspection and maintenance robots used in high-altitude or hazardous settings. Though early in their career, Lv’s work has already attracted attention for its practical implications in robotics and automation. Their research bridges algorithmic innovation with real-world robotic applications, offering a foundation for future studies in bio-inspired locomotion and swarm intelligence. As the field of climbing robotics grows, Lv’s contributions stand out for their potential to improve safety and efficiency in industrial and rescue operations.
Research Focus
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Top Papers
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