Yinpeng Qi

Papers

Total Citations

H-Index

About

Yinpeng Qi is a researcher advancing the field of robotic motion planning, with a primary focus on intelligent path optimization for robotic arms. His most notable contribution is the development of a two-stage RRT* (Rapidly-exploring Random Tree*) optimization algorithm, designed to address critical challenges in dynamic path planning, including high computational cost and slow convergence speed. By refining the exploration phase to reduce the randomness inherent in traditional RRT* methods, Qi’s work enhances the efficiency and reliability of robotic arm navigation in complex environments. This research, published in 2025, has already garnered early citations, signaling its growing relevance in robotics and automation. Qi’s contributions are particularly impactful for applications in manufacturing, logistics, and autonomous systems, where precise and rapid path planning is essential. His innovative approach to algorithmic optimization demonstrates a keen ability to solve real-world engineering problems, positioning him as a promising voice in the intersection of robotics and computational geometry. For students and researchers exploring motion planning, Qi’s work offers a practical, performance-driven framework that balances exploration efficiency with path optimality.