[2602.23524] V-MORALS: Visual Morse Graph-Aided Estimation of Regions of Attraction in a Learned Latent Space

Computer Science > Robotics arXiv:2602.23524 (cs) [Submitted on 26 Feb 2026] Title:V-MORALS: Visual Morse Graph-Aided Estimation of Regions of Attraction in a Learned Latent Space Authors:Faiz Aladin, Ashwin Balasubramanian, Lars Lindemann, Daniel Seita View a PDF of the paper titled V-MORALS: Visual Morse Graph-Aided Estimation of Regions of Attraction in a Learned Latent Space, by Faiz Aladin and 3 other authors View PDF HTML (experimental) Abstract:Reachability analysis has become increasingly important in robotics to distinguish safe from unsafe states. Unfortunately, existing reachability and safety analysis methods often fall short, as they typically require known system dynamics or large datasets to estimate accurate system models, are computationally expensive, and assume full state information. A recent method, called MORALS, aims to address these shortcomings by using topological tools to estimate3DR-eEgnciodnesr of Attraction (ROA) in a low-dimensional latent space. However, MORALS still relies on full state knowledge and has not been studied when only sensor measurements are available. This paper presents Visual Morse Graph-Aided Estimation of Regions of Attraction in a Learned Latent Space (V- MORALS). V-MORALS takes in a dataset of image-based trajectories of a system under a given controller, and learns a latent space for reachability analysis. Using this learned latent space, our method is able to generate well-defined Morse Graphs, from which we can comput...