Stein Variational Guided Model Predictive Path Integral Control: Proposal and Experiments with Fast Maneuvering Vehicles

This paper presents a novel Stochastic Optimal Control (SOC) method based on Model Predictive Path Integral control (MPPI), named Stein Variational Guided MPPI (SVG-MPPI), designed to handle rapidly shifting multimodal optimal action distributions. While MPPI can find a Gaussian-approximated optimal action distribution in closed form, i.e., without iterative solution updates, it struggles with multimodality of the optimal distributions, such as those involving non-convex constraints for obstacle avoidance. This is due to the less representative nature of the Gaussian. To overcome this limitation, our method aims to identify a target mode of the optimal distribution and guide the solution to converge to fit it. In the proposed method, the target mode is roughly estimated using a modified Stein Variational Gradient Descent (SVGD) method and embedded into the MPPI algorithm to find a closed-form "mode-seeking" solution that covers only the target mode, thus preserving the fast convergence property of MPPI. Our simulation and real-world experimental results demonstrate that SVG-MPPI outperforms both the original MPPI and other state-of-the-art sampling-based SOC algorithms in terms of path-tracking and obstacle-avoidance capabilities. Source code: https://github.com/kohonda/proj-svg_mppiComment: 7 pages, 5 figure

Large amplitude behavior of the Grinfeld instability: a variational approach

In previous work, we have performed amplitude expansions of the continuum equations for the Grinfeld instability and carried them to high orders. Nevertheless, the approach turned out to be restricted to relatively small amplitudes. In this article, we use a variational approach in terms of multi-cycloid curves instead. Besides its higher precision at given order, the method has the advantages of giving a transparent physical meaning to the appearance of cusp singularities and of not being restricted to interfaces representable as single-valued functions. Using a single cycloid as ansatz function, the entire calculation can be performed analytically, which gives a good qualitative overview of the system. Taking into account several but few cycloid modes, we obtain remarkably good quantitative agreement with previous numerical calculations. With a few more modes taken into consideration, we improve on the accuracy of those calculations. Our approach extends them to situations involving gravity effects. Results on the shape of steady-state solutions are presented at both large stresses and amplitudes. In addition, their stability is investigated.Comment: subm. to EPJ