Papers
3
Total Citations
69
H-Index
3
About
Liansen Sha is a researcher whose work sits at the intersection of robotics, structural optimization, and mechanical design, with a particular focus on lightweight design for collaborative robots and exoskeletons. His primary research area is topology optimization—a computational method for determining the most efficient material layout within a given design space—applied to robotic systems. Sha’s major contributions include developing novel topology optimization methods that account for assembly-level finite element models and multi-working conditions, moving beyond traditional single-pose analyses. His 2020 paper, "A topology optimization method of robot lightweight design based on the finite element model of assembly and its applications," has garnered 38 citations, establishing a foundation for more realistic and practical robot design. A subsequent 2022 paper, with 22 citations, introduced orthogonal experiment techniques to better determine extreme loading conditions, addressing a key limitation in existing approaches. Sha has also extended his methods to upper-limb powered exoskeletons, demonstrating the versatility of his work. By enabling lighter, stronger, and more efficient robotic structures, his research has significant implications for the development of safer, more agile collaborative robots and assistive devices.
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