Senjian Lu

Zhejiang University of Science and Technology

Papers

Total Citations

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About

Senjian Lu is a researcher at the forefront of robotic perception and manipulation, with a particular focus on applying computer vision to complex, real-world industrial and medical challenges. His work bridges the gap between advanced algorithms and practical automation, addressing critical needs in both healthcare and power infrastructure. Lu’s major contributions include developing a pixel-level collision-free grasp prediction network, a breakthrough that enables robots to reliably sort medical test tubes from cluttered, unstructured trays—a task previously fraught with difficulty for vision-based systems. This work, published in 2023 and already garnering 6 citations, demonstrates immediate applicability in medical logistics. Additionally, Lu has pioneered an automated method for registering 3D point clouds of electrical arresters using the SHOT descriptor and ICP algorithm, solving the long-standing problem of accurately inspecting power system components with uniform, repetitive geometries. This 2024 paper, with 3 citations, highlights his ability to tackle niche but critical industrial inspection tasks. Through these contributions, Senjian Lu is establishing himself as a key innovator in vision-guided robotics, creating systems that are not only intelligent but also directly deployable in high-stakes environments.