Differentiable optimization is a powerful new paradigm capable of reconciling model-based
and learning-based approaches in robotics. However, the majority of robotics optimization …

We consider the problem of learning error covariance matrices for robotic state estimation.
The convergence of a state estimator to the correct belief over the robot state is dependent …