Xiangyu Dong

Papers

Total Citations

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About

Xiangyu Dong is a roboticist whose work sits at the intersection of perception, manipulation, and autonomous navigation. His primary research focuses on enabling robots to operate reliably in dynamic, unstructured environments—a critical challenge for real-world deployment. Dong’s major contributions include developing a vision-guided framework for dynamic object grasping, which integrates real-time tracking with manipulator control to allow robots to successfully grasp moving targets. This work, published in 2020, has garnered 5 citations and addresses a fundamental bottleneck in industrial and service robotics. He has also advanced the field of mobile robot localization with his work on Semantic Lidar Odometry and Mapping (SLAM). By integrating RangeNet++ semantic segmentation into the SLAM pipeline, his 2022 paper tackles the problem of dynamic points corrupting point cloud registration—a key limitation of traditional systems. This contribution, with 4 citations, is particularly impactful for autonomous navigation in crowded or changing spaces. Dong’s research elegantly bridges the gap between perception and action, offering practical solutions for robots that must see, understand, and interact with a moving world.