This article reviews the state-of-the-art of nonlinear solvers as well as frameworks for numerical optimiza-tion, which is more and more utilized for robotics appli-cations. We will discuss the features and project status for each solver and detail how one can use a numeri-cal optimization framework to avoid being limited to a particular solver. The comparison allows to choose the appropriate strategy in robotics where trajectory gener-ation, posture generation, control can be implemented as different types of optimization problems.
CITATION STYLE
Moulard, T., Chr^|^eacute;tien, B., & Yoshida, E. (2014). Software Tools for Nonlinear Optimization. Journal of the Robotics Society of Japan, 32(6), 536–541. https://doi.org/10.7210/jrsj.32.536
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