Ximing Liang

Beijing University of Civil Engineering and Architecture, Central South University

Papers

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About

Ximing Liang is a leading researcher in swarm intelligence and multi-robot systems, with a focus on bio-inspired optimization algorithms and decentralized formation control. His most impactful work includes the development of an improved Chicken Swarm Optimization (CSO) algorithm, which enhances the performance of this nature-inspired metaheuristic for solving complex global optimization problems. This paper has garnered 53 citations, reflecting its significance in advancing optimization techniques for applications such as robot path planning. Liang has also made notable contributions to swarm robotics, proposing the Triangular Formation Algorithm (TFA) for decentralized flocking and a regular tetrahedron formation strategy for three-dimensional environments. These works, cited 10 and 7 times respectively, address critical challenges in scalable swarm coordination and obstacle avoidance. His research bridges theoretical algorithm design with practical robotic applications, offering efficient solutions for autonomous navigation and formation control in both 2D and 3D spaces. Liang’s work is essential reading for researchers interested in swarm intelligence, optimization algorithms, and the deployment of robot swarms in complex, real-world environments.