Xin Meng

National University of Singapore, East China Jiaotong University

Papers

Total Citations

H-Index

About

Xin Meng is a robotics researcher whose work bridges the gap between intelligent manipulation and precision engineering. Her primary research areas include robotic rearrangement tasks, motion reliability analysis, and non-probabilistic uncertainty quantification for industrial robots. In her highly cited 2022 paper, "Transporters with Visual Foresight for Solving Unseen Rearrangement Tasks," Meng proposed a novel visual foresight model that enables robots to efficiently learn pick-and-place manipulation for constructing unseen structures—a critical challenge in intelligent robotic manipulation. Her second most-cited work, "Non-Probabilistic Reliability Analysis of Robot Accuracy under Uncertain Joint Clearance," addresses the motion reliability constraints limiting industrial robots in high-precision fields by establishing kinematic models that account for joint clearance. Most recently, her 2025 research on non-probabilistic reliability partitioning methods tackles the uneven error distribution in large workspace robots, moving beyond conventional probabilistic approaches. With over 26 citations across her top papers, Meng is making significant contributions to both the cognitive and mechanical aspects of robotics, advancing the field toward more reliable and adaptable automation for high-stakes industrial applications.