Jieyu Lei
Papers
2
Total Citations
24
H-Index
1
About
Jieyu Lei is a robotics researcher whose work centers on intelligent path planning and cooperative manipulation, with a particular emphasis on multi-robot systems and optimization-driven algorithms. In their most impactful contribution, Lei developed a dual-robot cooperative arc welding path planning algorithm that leverages multi-objective cross-entropy optimization, a method that has already garnered 23 citations since its 2024 publication. This work addresses the critical challenge of coordinating two robotic arms in complex manufacturing tasks, balancing competing objectives such as time, energy, and collision avoidance. Building on this foundation, Lei’s 2025 paper introduces an adaptive rapidly-exploring random trees algorithm enhanced by cross-entropy optimization (CE-RRT), which provides a low-cost, fast, and effective solution for path planning in diverse and cluttered environments. By integrating an adaptive sampling strategy, this approach significantly improves upon traditional RRT methods in both efficiency and robustness. Lei’s research is notable for its practical impact on industrial automation, offering scalable solutions for real-world robotic applications. Their work exemplifies how cross-entropy methods can be harnessed to solve complex, multi-objective problems in robotics, making them a rising voice in the field of autonomous systems and cooperative robotics.
Research Focus
Key Achievements
Top Papers
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- 2