Xiaojing Yang

Kunming University of Science and Technology

Papers

Total Citations

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About

Xiaojing Yang is a robotics researcher whose work spans soft robotics, miniature locomotion, and intelligent manufacturing. Yang’s most-cited paper, “Design and modeling of a driving system for soft massage robot” (2021, 7 citations), demonstrates a focus on human-friendly, compliant robotic systems for therapeutic applications. A second influential study, “Structure design of a miniature and jumping robot for search and rescue” (2018, 3 citations), addresses the critical need for specialized access in disaster zones, proposing a compact jumping robot capable of navigating the dangerous, complex environments left by earthquakes or unnatural disasters. Most recently, Yang’s work on “A rapid method for modal parameter prediction in robotic milling” (2025) tackles a key industrial challenge: chatter in robotic machining. By enabling faster prediction of a robot’s frequency response, this method aims to improve milling precision in low-rigidity, multi-degree-of-freedom systems. Collectively, Yang’s research bridges soft, safe interaction with robust, high-precision performance—from therapeutic massage to disaster response and advanced manufacturing.