Shaofei Zang

Henan University of Science and Technology

Papers

Total Citations

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About

Shaofei Zang is a leading researcher in mobile robotics and intelligent path planning, whose work has significantly advanced autonomous navigation systems. His primary research areas focus on developing hybrid optimization algorithms that combine evolutionary computation with geometric modeling to solve complex robotic motion challenges. Zang’s most impactful contribution is his 2020 paper on "Robot Path Planning Based on Genetic Algorithm Fused with Continuous Bezier Optimization," which has garnered 64 citations. This study introduced a novel approach that integrates genetic algorithms with Bezier curves to eliminate redundant nodes and sharp inflection points, producing smoother, more efficient robot trajectories. His 2019 work on "Dynamic Path Planning of Mobile Robot Based on Improved Ant Colony Optimization Algorithm" (16 citations) further demonstrates his expertise, where he enhanced traditional ant colony optimization by incorporating genetic operators to improve solution quality in dynamic environments. Zang’s research is characterized by its practical applicability, offering robust solutions for real-world robotic navigation challenges. His innovative fusion of genetic algorithms with geometric optimization techniques has established him as a key contributor to the field, inspiring further developments in autonomous systems and intelligent path planning.