Chengkan Huang

Papers

Total Citations

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About

Chengkan Huang is a researcher focused on advancing autonomous navigation and robotics, with particular expertise in localization and path planning for automated guided vehicles (AGVs). His most cited work, "Vision-based initial localization of AGV and path planning with PO-JPS algorithm" (2024), tackles critical challenges in robot mobility by addressing the limitations of traditional adaptive Monte Carlo localization (AMCL), which struggles with global localization and computational inefficiency. Huang’s proposed PO-JPS algorithm enhances path planning by reducing unnecessary node calculations, leading to more complete and time-efficient routes. This contribution is especially relevant for industrial automation and logistics, where AGVs require reliable, real-time navigation. With 4 citations to date, his research is gaining traction among peers seeking to optimize robotic systems. Huang’s work stands out for its practical focus on overcoming real-world deployment hurdles, making it a valuable reference for students and researchers in robotics, computer vision, and autonomous systems. His innovative approach to integrating vision-based localization with efficient path planning underscores his commitment to advancing the field of intelligent robotics.