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arXiv · 2512.15533

Ising Machines for Model Predictive Path Integral-Based Optimal Control

Lorin Werthen-Brabants·Pieter Simoens
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Abstract

We present a sampling-based Model Predictive Control (MPC) method that implements Model Predictive Path Integral (MPPI) as an \emph{Ising machine}, suitable for novel forms of probabilistic computing. By expressing the control problem as a Quadratic Unconstrained Binary Optimization (QUBO) problem, we map MPC onto an energy landscape suitable for Gibbs sampling from an Ising model. This formulation enables efficient exploration of (near-)optimal control trajectories. We demonstrate that the approach achieves accurate trajectory tracking compared to a reference MPPI implementation, highlighting the potential of Ising-based MPPI for real-time control in robotics and autonomous systems.

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Lorin Werthen-Brabants, Pieter Simoens. 2025-12-17. Ising Machines for Model Predictive Path Integral-Based Optimal Control. https://arxiv.org/abs/2512.15533

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