A reinforcement learning control approach for underwater manipulation under position and torque constraints
A reinforcement learning control approach for underwater manipulation under position and torque constraints
In marine operations underwater manipulators play a primordial role. However, due to uncertainties in the dynamic model and disturbances caused by the environment, low-level control methods require great capabilities to adapt to change. Furthermore, under position and torque constraints the requirements for the control system are greatly increased. Reinforcement learning …