Eliot Xing
Papers
2
Total Citations
18
H-Index
2
About
Eliot Xing is a robotics researcher whose work lies at the intersection of physical human-robot interaction and autonomous material perception. His research focuses on enabling robots to sense and respond to their environment with greater precision and intelligence, particularly in unstructured, human-centric settings. Xing’s most cited work, “Characterizing Multidimensional Capacitive Servoing for Physical Human–Robot Interaction” (2022, 14 citations), introduces a novel capacitive servoing control scheme that allows robots to accurately sense the human body, follow trajectories around it, and track motion—a critical step toward safe and robust physical collaboration between humans and robots. In earlier work, “Multimodal Material Classification for Robots using Spectroscopy and High Resolution Texture Imaging” (2020, 4 citations), he developed a multimodal sensing technique that combines near-infrared spectroscopy with high-resolution texture imaging, enabling robots to estimate material properties for more informed manipulation of real-world objects. Together, these contributions demonstrate Xing’s commitment to advancing robot perception and control, bridging the gap between sensing and action in complex, real-world environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2