Fengen Dai

Learning Time-Varying Joint-Motor Mapping for Precise Control of Cable-Driven Humanoid Robots Under Transmission Uncertainties

Cable-driven robots face significant challenges in achieving precise motion control due to the inherent nonlinearity, strong coupling, and time-varying transmission dynamics. Traditional model-based methods require precise parameter identification and offline calibration, while existing data-driven