Abstract: Protective hardware is essential for mitigating damage caused by unavoidable falls in humanoid robots. Despite notableprogress in fall protection hardware, the theoretical foundation for modeling and the feasibility of conducting full-scalefall experiments on robots or their surrogates remain somewhat limited. This paper proposes a method for optimizing thethickness of Expandable Polyethylene (EPE), which is used as back protection for the Chubao humanoid robot, based onsmall-scale impact test data to predict full-scale behavior. The optimal thickness is defined as a balance between compactdesign and protective effectiveness. An equivalent impact model characterized by four parameters: contact area S, massm, fall height h, and cushioning material thickness d is introduced to describe impact conditions. The relationship betweenthe peak impact acceleration ap and material thickness d, which forms the core of the method and gives rise to the nameAP-D, is analyzed through their plotted curves. After introducing three characteristic parameters and two correction factors, the relationship among the aforementioned variables is derived. Subsequently, both the optimal thickness do and itscorresponding peak impact acceleration ao p are predicted via nonlinear and linear regression models. Finally, the accuracyand effectiveness of the theoretically derived optimal thickness are validated on both a dummy and the actual robot. Withthe cushioning material applied, the peak chest acceleration is reduced to 41.57g for the dummy and 32.08g for the robot.

Key words: Humanoid robot, Fall protection, Cushioning material, Impact test, Regression model')">Humanoid robot, Fall protection, Cushioning material, Impact test, Regression model