A hysteresis-aware neural network with pressure-direction inputs, combined with PPO control trained in a neural-network simulator, tracks trajectories on a soft surgical robot with 0.126 to 0.250 mm error.
Modeling of fluidic pre- stressed composite actuators with application to soft robotic grippers,
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Hysteresis-Aware Neural Network Modeling and Whole-Body Reinforcement Learning Control of Soft Robots
A hysteresis-aware neural network with pressure-direction inputs, combined with PPO control trained in a neural-network simulator, tracks trajectories on a soft surgical robot with 0.126 to 0.250 mm error.