Daxin Xin
Papers
3
Total Citations
9
H-Index
2
About
Daxin Xin is a robotics researcher whose work focuses on bionic locomotion, robotic manipulation, and precision automation. His research spans the design and simulation of legged robots, path planning for dual-arm systems, and high-accuracy visual servoing for industrial applications. In his most cited work, "Motion Simulation of Bionic Hexapod Robot Based on Virtual Prototyping Technology" (2017, 4 citations), Xin developed a 3D virtual prototype using MSC. ADAMS to model hexapod locomotion and foot-ground contact dynamics, advancing the understanding of bionic robot motion on horizontal terrain. He further addressed a critical limitation in robotic path planning by proposing a hybrid algorithm that combines an improved Artificial Potential Field method with Rapidly-exploring Random Trees (RRT) to overcome local minima issues in dual-arm coordination, as detailed in his 2023 paper (3 citations). Most recently, in 2024 (2 citations), Xin introduced a convex relaxation optimization approach for hand-eye calibration, enabling high-precision localization for remote switching operations in high-voltage environments—a significant step toward safer, automated electrical maintenance. With contributions that bridge simulation, algorithm design, and real-world safety, Xin is establishing himself as a thoughtful innovator in intelligent robotics and automation.
Research Focus
Key Achievements
Top Papers
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