NeuralSim: Augmenting Differentiable Simulators with Neural Networks
Eric Heiden David Millard Erwin Coumans Yizhou Sheng Gaurav S. Sukhatme Eric Heiden David Millard Erwin Coumans Yizhou Sheng Gaurav S. Sukhatme
Differentiable simulators provide an avenue for closing the sim-to-real gap by enabling the use of efficient, gradient-based optimization algorithms to find the simulation parameters that best fit the observed sensor readings. Nonetheless, these analytical models can only predict the dynamical behavior of systems for which they have been designed. In this work, we study the augmentation of a novel...