Yucong Tong

Wuhan University of Science and Technology

Papers

Total Citations

H-Index

About

Yucong Tong is a researcher specializing in mobile robotics and path planning algorithms, with a particular focus on improving the efficiency of autonomous navigation systems. His most cited work, "Fast Jump Point Search Based Path Planning for Mobile Robots" (2021), introduces a novel approach to accelerate pathfinding on static grid maps by enhancing the Jump Point Search (JPS) algorithm. Tong’s key contributions include a fast neighbor pruning method that leverages bit operations to identify jump points in a single step, significantly reducing computational overhead, and a symmetry-breaking heuristic function that eliminates redundant search paths. This work has garnered 3 citations and represents a meaningful step forward in real-time path planning for mobile robots, addressing critical challenges in computational speed and memory usage. Tong’s research is particularly relevant for applications in autonomous vehicles, warehouse robots, and drone navigation, where efficient pathfinding is essential. His innovative use of bit-level operations demonstrates a deep understanding of algorithmic optimization, making his work a valuable resource for students and researchers exploring advanced path planning techniques in robotics.