Mingming Shen

Papers

Total Citations

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About

Mingming Shen is a researcher whose work sits at the intersection of robotics, computer vision, and intelligent grasping systems. His primary focus is on developing algorithms that enable robots to perceive and manipulate objects with human-like dexterity and precision. Shen’s most notable contribution is his 2021 paper, “Robot Three-Finger Grasping Strategy Based on DeeplabV3+,” which addresses a fundamental challenge in robotics: achieving stable and accurate grasping. By integrating an improved DeeplabV3+ semantic segmentation model, he proposed a strategy that allows robots to better understand object geometry and plan effective grasps. This work has garnered attention from the global robotics community, accumulating 2 citations and laying groundwork for more adaptive manipulation systems. Shen’s research is particularly significant as it bridges deep learning and robotic control, offering a pathway toward more autonomous and versatile robots capable of operating in unstructured environments. His contributions are especially relevant for applications in industrial automation, assistive robotics, and human-robot collaboration, where reliable grasping is essential.