Dongliang Wang

South China University of Technology, Shantou University

Papers

Total Citations

105

H-Index

About

Dongliang Wang is a robotics and autonomous systems researcher whose work spans mobile robot control, swarm intelligence, and bio-inspired algorithms. His most recognized contribution is a robust Model Predictive Control (MPC) strategy for trajectory tracking in omni-directional mobile robots, published in 2019 and garnering 86 citations — a testament to its practical relevance in the robotics community. This work addressed key challenges in achieving precise, real-time path following under uncertainty, making it a valuable reference for engineers and researchers working on wheeled robot platforms. More recently, Wang has turned his attention to swarm robotics, exploring how collective behavior inspired by nature can solve complex autonomous navigation problems. His 2022 paper on Lévy flight and artificial potential field methods introduces a biologically inspired exploration algorithm that scales individual agent behavior to the swarm level, while a complementary study proposes a swarm control model combining virtual leader strategies with obstacle avoidance in unknown environments. Together, these works reflect Wang's growing interest in decentralized, nature-inspired approaches to multi-robot coordination. His research bridges theoretical modeling and practical implementation, offering meaningful contributions to the evolving field of intelligent robotic systems.