Approximate Robust Control of Uncertain Dynamical Systems

Edouard Leurent, Yann Blanco, Denis Efimov, Odalric-Ambrym Maillard

Oct 12, 2018 (modified: Oct 12, 2018) NIPS 2018 Workshop MLITS Submission readers: everyone
  • Abstract: This work studies the design of safe control policies for large-scale non-linear systems operating in uncertain environments. In such a case, the robust control framework is a principled approach to safety that aims to maximize the worst-case performance of a system. However, the resulting optimization problem is generally intractable for non-linear systems with continuous states. To overcome this issue, we introduce two tractable methods that are based either on sampling or on a conservative approximation of the robust objective. The proposed approaches are applied to the problem of autonomous driving.
  • TL;DR: We propose two methods to approximately solve the robust control of uncertain dynamical systems, and apply them to a decision-making problem for autonomous driving.
  • Keywords: robust, control, planning, safety, uncertainty, behaviour, negotiation
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