A Differentiable Physics Engine for Deep Learning in Robotics
A Differentiable Physics Engine for Deep Learning in Robotics
An important field in robotics is the optimization of controllers. Currently, robots are often treated as a black box in this optimization process, which is the reason why derivative-free optimization methods such as evolutionary algorithms or reinforcement learning are omnipresent. When gradient-based methods are used, models are kept small or …