  Soft robots have gained increased popularity in recent years due to their
adaptability and compliance. In this paper, we use a digital twin model of
cable-driven soft robots to learn control parameters in simulation. In doing
so, we take advantage of differentiable rendering as a way to instruct robots
to complete tasks such as point reach, gripping an object, and obstacle
avoidance. This approach simplifies the mathematical description of such
complicated tasks and removes the need for landmark points and their tracking.
Our experiments demonstrate the applicability of our method.
