Liu Jin-gang

Shenyang University of Chemical Technology

Papers

Total Citations

H-Index

About

Liu Jin-gang is a researcher specializing in mobile robotics and computational intelligence, with a particular focus on path planning algorithms and bio-inspired optimization techniques. His most notable contributions center on advancing ant colony optimization (ACO) algorithms to solve complex navigation challenges faced by autonomous mobile robots. In his highly cited 2010 work, Liu introduced an innovative approach combining fuzzy logic controllers with ACO to dynamically optimize key algorithm parameters, while incorporating chaos theory into the construction of near-neighbour city tables and establishing dynamic searching windows for improved exploration efficiency. Building on this foundation, his 2011 research introduced the Differential Evolution Chaos Ant Colony Optimization (DEACO) algorithm, which leverages differential evolution strategies for pheromone updating to generate optimal collision-free paths in complex static environments. Together, these works have accumulated 20 citations, reflecting meaningful influence within the robotics and swarm intelligence communities. Liu's research addresses a critical challenge in autonomous robotics — efficient and reliable path planning — by creatively hybridizing multiple optimization paradigms. His work offers practical value for researchers developing smarter navigation systems and contributes foundational insights to the broader field of evolutionary computation applied to real-world robotics problems.