Decoupling stochastic optimal control problems for efficient solution: insights from experiments across a wide range of noise regimes [article]

Mohamed Naveed Gul Mohamed, Suman Chakravorty, Dylan A. Shell
2019 arXiv   pre-print
We consider the problem of robotic planning under uncertainty in this paper. This problem may be posed as a stochastic optimal control problem, a solution to which is fundamentally intractable owing to the infamous "curse of dimensionality". Hence, we consider the extension of a "decoupling principle" that was recently proposed by some of the authors, wherein a nominal open-loop problem is solved followed by a linear feedback design around the open-loop, and which was shown to be near-optimal
more » ... second order in terms of a "small noise" parameter, to a much wider range of noise levels. Our empirical evidence suggests that this allows for tractable planning over a wide range of uncertainty conditions without unduly sacrificing performance.
arXiv:1909.08585v1 fatcat:3teb2wgtyzhmbkzapzsnvrlnoi