Xiafu Lv

Chongqing University of Posts and Telecommunications

Papers

Total Citations

H-Index

About

Xiafu Lv is a leading researcher in intelligent robotics, specializing in path planning and autonomous navigation for both mobile robots and robotic arms. His work addresses critical inefficiencies in traditional algorithms by developing novel hybrid approaches that dramatically improve convergence speed and path optimality. Lv’s most influential contribution is the "Improved A-star Ant Colony Algorithm" for global path planning, which fuses A-star’s heuristic efficiency with ant colony optimization’s adaptability—a breakthrough that has garnered 34 citations for solving slow convergence and excessive iteration issues. He has also advanced manipulator path planning through an improved Rapidly-exploring Random Tree (RRT) algorithm, enhanced by artificial potential fields to reduce randomness and space complexity, earning 10 citations. These innovations are pivotal for real-time robotics applications, from warehouse automation to surgical assistance. Lv’s work is distinguished by its practical focus on overcoming computational bottlenecks, making complex path planning more accessible for real-world deployment. His research continues to shape the next generation of autonomous systems, offering elegant solutions to foundational challenges in robotics.