Xiaopeng Bai

China Academy of Space Technology, Beijing Forestry University

Papers

Total Citations

H-Index

About

Xiaopeng Bai is a researcher whose work bridges robotics, manufacturing, and biomechanics. His primary research areas include robotic belt grinding, inverse modeling, and the biomechanical analysis of plant structures. Bai’s major contribution lies in developing an inverse input prediction model for robotic belt grinding, a novel approach that enhances precision and efficiency in automated surface finishing processes. This work, published in 2021 and garnering 5 citations, addresses critical challenges in adaptive control for industrial robotics, offering a framework for predicting optimal grinding parameters without direct sensor feedback. Additionally, Bai has explored the finite element modeling of Populus tomentosa branches, investigating pruning mechanisms with a 2025 study that provides insights into the biomechanical properties of woody plants. This interdisciplinary work, while early in its citation impact, demonstrates Bai’s versatility in applying computational modeling to both engineering and biological systems. His achievements reflect a commitment to advancing robotic automation and understanding natural structures, making his research relevant for students and researchers interested in manufacturing technology, biomechanics, and the intersection of robotics with material science.