Papers
5
Total Citations
34
H-Index
3
About
Yanze Zhang is a rising robotics researcher whose work sits at the intersection of vision-based control, multi-agent coordination, and high-precision manufacturing. His primary research areas include image-based visual servoing (IBVS), decentralized multi-robot systems, and hand–eye collaborative measurement. Zhang’s major contributions address fundamental challenges in real-world robotic deployment: occlusion resilience, positioning accuracy, and safety under uncertainty. His 2023 paper on occlusion-free IBVS using probabilistic control barrier certificates (15 citations) offers a rigorous solution to a long-standing problem where obstructed visual features cause servoing failure. In the same year, he developed an eye-in-hand active correction method for high-accuracy spindle positioning (9 citations), directly applicable to industrial automation. His 2024 work on decentralized multi-robot line-of-sight connectivity maintenance (5 citations) tackles the critical issue of maintaining communication links under localization uncertainty, while his 2025 paper on adaptive deadlock avoidance introduces a CBF-inspired risk metric to prevent equilibrium states in decentralized systems. Zhang’s research is notable for its theoretical grounding in control barrier functions and its clear pathway to practical applications in manufacturing and multi-robot coordination.
Research Focus
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