[CoRL 2020 Best Paper Nominee] Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs

CoRL 2020

[CoRL 2020 Best Paper Nominee] Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs

Dec 16, 2020
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"**Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs** Marcus Pereira (Georgia Institute Technology)*; Ziyi Wang (Georgia Institute of Technology); Ioannis Exarchos (Stanford University); Evangelos Theodorou (Georgia Institute of Technology) Publication: http://corlconf.github.io/paper_408/ **Abstract** This paper introduces a new formulation for stochastic optimal control and stochastic dynamic optimization that ensures safety with respect to state and control constraints. The proposed methodology brings together concepts such as Forward-Backward Stochastic Differential Equations, Stochastic Barrier Functions, Differentiable Convex Optimization and Deep Learning. Using the aforementioned concepts, a Neural Network architecture is designed for safe trajectory optimization in which learning can be performed in an end-to-end fashion. Simulations are performed on three systems to show the efficacy of the proposed methodology. "

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