NCM: How can robotic explorers under uncertainty take optimal and provably-stable actions in real-time?

Neural Contraction Metrics (NCMs) for Robust Estimation and Control We have developed new deep learning-based framework for robust nonlinear estimation and control using the concept of an NCM. NCM-based State Estimation and Control It globally models optimal contraction metrics sampled offline using an LSTM-RNN as depicted in (2) of the …

CV-STEM: Optimal and Provably-Stable Feedback Control of Stochastic Nonlinear Systems

ConVex optimization-based Stochastic steady-state Tracking Error Minimization (CV-STEM) CV-STEM is a new optimal state feedback control framework for a class of Itô stochastic nonlinear systems and Lagrangian systems. CV-STEM Control Computes its control input by an optimal contraction metric M(x,t), which greedily minimizes an upper bound of the steady-state mean squared …