Jianwei Cheng

China University of Mining and Technology

Papers

Total Citations

H-Index

About

Jianwei Cheng’s research focuses on advancing autonomous navigation for mobile robots, particularly in complex, hybrid-terrain environments where traditional path planning methods fall short. His major contributions lie in integrating evolutionary computation with domain-specific knowledge to solve NP-complete path planning problems. In his most cited work, “Path planning method for robots in complex ground environment based on cultural algorithm” (2009, 4 citations), Cheng pioneered a dual-evolution framework that leverages both common-sense heuristics and cultural algorithm principles to guide robots through varied road conditions. He extended this approach in “Knowledge-inducing Global Path Planning for Robots in Environment with Hybrid Terrain” (2010, 2 citations), developing a novel method that embeds terrain-specific knowledge into the evolutionary search process, significantly improving global path efficiency and robustness. While his citation counts are modest, Cheng’s work represents an early and creative synthesis of cultural algorithms and robotics—a niche but impactful contribution that has informed subsequent research in intelligent path planning. His achievements highlight the value of hybrid intelligence in solving real-world robotic navigation challenges, making his research a thoughtful resource for students and engineers exploring evolutionary robotics and autonomous systems.