Zhengyang Zou

Shanghai Jiao Tong University, China University of Mining and Technology

Papers

Total Citations

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About

Zhengyang Zou is a researcher whose work bridges multi-robot systems and computer vision, with a focus on intelligent control and image enhancement. His key contributions lie in two distinct but impactful areas: distributed multi-robot formation control and low-light image enhancement. In his 2020 paper on multi-robot formation control under dynamic obstacle interference—cited 11 times—Zou introduced bio-inspired strategies, drawing from fish shoaling behavior, to enable robot swarms to maintain formation and avoid collisions when obstacles disrupt inter-robot visibility and topology. This work addresses critical challenges in real-world autonomous coordination. More recently, in 2024, Zou advanced low-light image enhancement with a conditional generative model featuring a skip-connection structure, garnering 9 citations. This approach improves image quality in poorly lit conditions, with applications in surveillance and autonomous navigation. Together, these contributions demonstrate Zou’s versatility in tackling both physical and perceptual challenges in robotics, earning recognition for innovative solutions that enhance system robustness and visual clarity.