Kaiyuan Zheng

Papers

Total Citations

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About

Kaiyuan Zheng is a robotics and autonomous systems researcher whose work centers on motion planning, path optimization, and intelligent navigation for service robots. Zheng's most recognized contribution comes from a 2020 study proposing an improved RRT* path planning algorithm, which addressed critical limitations of the traditional Rapidly-exploring Random Tree Star method — namely its high memory consumption, slow convergence speed, and computational inefficiency in complex spatial environments. By refining this foundational algorithm, Zheng advanced the field's ability to achieve faster, more reliable global path planning while preserving the probabilistic completeness and asymptotic optimality that make RRT*-based approaches valuable for real-world robotic deployment. This work has accumulated 18 citations, reflecting its meaningful uptake within the robotics research community and its relevance to practitioners developing autonomous service robots for dynamic, obstacle-rich environments. Zheng's research speaks to a broader challenge in modern robotics: bridging theoretical planning algorithms with practical performance requirements. For students and researchers working on autonomous navigation, human-robot interaction spaces, or algorithm optimization, Zheng's contributions offer a focused and technically grounded entry point into next-generation mobile robot path planning strategies.