Chenxu Duan

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About

Chenxu Duan is a researcher focused on advancing intelligent path planning for robotic systems, particularly in industrial welding and mobile robot navigation. His work addresses critical efficiency challenges in automated manufacturing, where the length of a welding robot’s path directly impacts production line throughput. Duan’s most cited paper, “Path Planning for Welding Robot based on Ant Colony Optimization Algorithm” (2021, 4 citations), introduces a bio-inspired approach to optimize traversal of numerous welding points, overcoming the limitations of traditional methods. He further refines mobile robot navigation in “Research on Mobile Robot Path Planning Based on Fuzzy Artificial Potential Field Algorithm” (2023, 3 citations), tackling the common pitfalls of the classical APF method, such as target unreachability and wandering behavior. In “Research on Welding Robot Path Planning Based on Genetic Algorithm” (2023, 2 citations), Duan proposes an automated alternative to technician-dependent solder joint planning, enabling complex environments to be handled more adaptively. Collectively, his contributions demonstrate a systematic effort to replace heuristic or manual approaches with robust, optimization-driven algorithms, laying groundwork for more autonomous and efficient robotic operations in manufacturing.