Path Integral Control on Lie Groups

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Abstract
Path Integral control theory yields a sampling-based methodology for solving stochastic optimal control problems. Motivated by its computational efficiency, we extend this framework to account for systems evolving on Lie groups. Our derivation relies on recursive mappings between system poses and corresponding Lie algebra elements. This allows us to apply standard facts from stochastic calculus, and obtain expressions analogous to those of Euclidean problems. The results imply that stochastic optimal control can be applied in a parameterization-free manner, even when nonlinear configuration spaces are considered. The method is tested in simulation on a simple model of a rigid satellite.

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