# REAP-T: A MATLAB Toolbox for Implementing Robust-to-Early Termination Model Predictive Control

arXiv: https://arxiv.org/abs/2507.00863 · HTML: https://mlsanity.com/paper/2507.00863/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Jul 2025.

## Built on by (most cited first, 1 of 1)

- [PriPG-RL: Privileged Planner-Guided Reinforcement Learning for Partially Observable Systems with Anytime-Feasible MPC](https://mlsanity.com/paper/2604.08036/) (2026)

## Abstract (arXiv)

This paper presents a MATLAB toolbox for implementing robust-to-early termination model predictive control, abbreviated as REAP, which is designed to ensure a sub-optimal yet feasible solution when MPC computations are prematurely terminated due to limited computational resources. Named REAP-T, this toolbox is a comprehensive, user-friendly, and modular platform that enables users to explore, analyze, and customize various components of REAP for their specific applications. Notable attributes of REAP-T are: (i) utilization of built-in MATLAB functions for defining the MPC problem; (ii) an interactive and intuitive graphical user interface for parameter tuning and visualization; (iii) real-time simulation capabilities, allowing users to observe and understand the real-time behavior of their systems; and (iv) inclusion of real-world examples designed to guide users through its effective use.