Max Robotics — Global Service Robot Directory + US Certification

About

Dr. Lixiong Cao is a leading researcher in the field of reliability engineering, with a specific focus on uncertainty quantification and surrogate modeling. His work addresses the critical challenge of epistemic uncertainty—the kind that arises from a lack of knowledge—in complex mechanical systems. Dr. Cao’s major contributions lie in the application of evidence theory to reliability analysis, particularly through the development of efficient Kriging surrogate models. This approach, detailed in his highly cited 2021 paper (32 citations), overcomes the computational barriers that previously hindered the practical use of evidence theory in engineering. He has further advanced the field by applying these methods to industrial robotics, developing novel frameworks to analyze and improve positioning accuracy. His 2022 works (29 and 25 citations, respectively) provide robust methods for both reliability analysis and uncertainty inverse analysis, enabling the identification of error sources in robotic manipulators. By accounting for parameter correlations and small, unmeasurable uncertainties, Dr. Cao’s research directly enhances the precision and reliability of industrial robots, making a tangible impact on modern manufacturing and automation.