Zixuan Liao
Papers
2
Total Citations
16
H-Index
2
About
Zixuan Liao is a rising researcher in robotics, whose work focuses on advancing the safety and efficiency of multi-robot systems. His key research areas include multi-manipulator coordination, collision detection, and sensorless control. Liao's most notable contribution is an integral design for high-performance, sensor-less collision detection in serial robots, which uses a generalized momentum-based observer to estimate external disturbance torques—a method that enhances robot safety without requiring expensive force sensors. This work, published in 2022, has already garnered 6 citations for its practical impact. In 2024, Liao further advanced the field with a study on online task allocation and scheduling in multi-manipulator systems, addressing collision constraints and unknown tasks—a critical challenge for real-world automation. This paper has earned 10 citations, reflecting its relevance to scalable robotic systems. Through these contributions, Liao is helping to make robotic systems more autonomous, safer, and better suited for dynamic environments.
Research Focus
Key Achievements
Top Papers
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