Kemeng Ran

Papers

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About

Kemeng Ran is a rising researcher in mobile robotics, specializing in motion planning under kinematic constraints. Their work focuses on advancing the Rapidly-exploring Random Trees (RRT*) algorithm to generate smoother, more efficient paths for mobile robots. In their highly cited 2024 paper, Ran introduced an improved RRT* algorithm that integrates the Clothoid curve, enabling robots to produce continuous-curvature paths that respect real-world turning limitations. This work, with 14 citations, directly addresses the critical gap between theoretical path planning and practical robot execution. Building on this, their 2025 paper, "FHQ-RRT*," tackles the persistent challenges of slow convergence and high path cost in RRT* variants. By proposing a method to acquire high-quality paths faster, this work has already garnered 10 citations, reflecting its immediate relevance to the field. Ran’s contributions are particularly notable for their focus on real-time applicability, ensuring that generated paths are not only mathematically optimal but also physically feasible for wheeled robots. Their research is essential reading for engineers and researchers working on autonomous navigation, offering practical solutions that bridge algorithm design and real-world deployment.