Shuangsi Xue

Papers

Total Citations

H-Index

About

Shuangsi Xue is a leading researcher at the intersection of robotics, multi-agent systems, and intelligent control, with a focus on enhancing autonomy in complex, safety-critical environments. Their major contributions include pioneering graph-based knowledge acquisition using convolutional networks for distribution network patrol robots, a method that significantly enriches robotic situational awareness in smart grids. This work, their most cited with 18 citations, provides a foundational framework for integrating structural knowledge into robotic perception and decision-making. Xue has also advanced fixed-time formation control for multi-agent systems through neural observer-based designs, ensuring robust and rapid coordination. More recently, they have broken new ground in adaptive hierarchical control of quadcopters by combining safe reinforcement learning with human demonstration, a notable achievement that bridges the gap between human expertise and autonomous learning while guaranteeing operational safety. With a growing body of work that consistently pushes the boundaries of learning-based control and robotic intelligence, Shuangsi Xue is establishing a reputation for developing practical, theoretically sound solutions that address real-world challenges in automation and smart infrastructure.