Xiaojian Wang

State Key Laboratory of Tribology, Tsinghua University

Papers

Total Citations

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About

Xiaojian Wang is a leading researcher in robotics, specializing in the optimal design and dynamic analysis of hybrid and parallel robotic mechanisms. His work focuses on advancing industrial automation, particularly through the development of high-performance spray-painting robots and multi-degree-of-freedom (DOF) manipulators. Wang’s major contributions include the multi-objective optimal design of a novel 6-DOF hybrid spray-painting robot, where he integrated kinematic modeling with the virtual work principle to enhance precision and efficiency. His 2021 paper on this topic has garnered 25 citations, reflecting its impact on robotic design methodologies. Additionally, his 2020 study on the dynamics evaluation of a 2UPU/SP parallel mechanism for a 5-DOF hybrid robot, which considered gravitational effects, has received 23 citations. This work is notable for its rigorous approach to performance evaluation, offering insights into the stability and control of complex robotic systems. Wang’s research is instrumental in bridging theoretical mechanics with practical engineering, making him a key figure in the evolution of next-generation industrial robots.