Robotics, Volume 14, Issue 11
2025 November - 24 articles
Cover Story: This paper presents sign gradient descent (SGD) algorithms that accelerate kinetostatic protein folding, a computational tool for designing protein-based nanorobotic mechanisms. By leveraging gradient-sign information rather than full-torque magnitudes, the method reduces costly force-field evaluations and accelerates convergence within the KCM framework. Simulations on α-helices and β-sheets show substantial performance gains, enabling more efficient modeling and development of protein-based nanorobotic components. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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