Model-free control for soft manipulators based on reinforcement learning
IROS, pp. 2909-2915, 2017.
Most control methods of soft manipulators are developed based on physical models derived from mathematical analysis or learning methods. However, due to internal nonlinearity and external uncertain disturbances, it is difficult to build an accurate model, further, these methods lack robustness and portability among different prototypes. I...More
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