Ewerton R. Vieira — accepted AI-conference papers

2024

MORALS: Analysis of High-Dimensional Robot Controllers via Topological Tools in a Latent Space

Ewerton R. Vieira, Aravind Sivaramakrishnan, Sumanth Tangirala, Edgar Granados, Konstantin Mischaikow, Kostas E. Bekris

ICRA 2024poster

Estimating the region of attraction (RoA) for a robot controller is essential for safe application and controller composition. Many existing methods require a closed-form expression that limit applicability to data-driven controllers. Methods that operate only over trajectory rollouts tend to be dat…

Cited by 3 Source ↗Scholar ↗

2023

Data-Efficient Characterization of the Global Dynamics of Robot Controllers with Confidence Guarantees

Ewerton R. Vieira, Aravind Sivaramakrishnan, Yao Song, Edgar Granados, Marcio Gameiro, Konstantin Mischaikow +2

ICRA 2023poster

This paper proposes an integration of surrogate modeling and topology to significantly reduce the amount of data required to describe the underlying global dynamics of robot controllers, including closed-box ones. A Gaussian Process (GP), trained with randomized short trajectories over the state-spa…

Cited by 4 Source ↗Scholar ↗

2022

Persistent Homology for Effective Non-Prehensile Manipulation

Ewerton R. Vieira, Daniel Nakhimovich, Kai Gao, Rui Wang, Jingjin Yu, Kostas E. Bekris

ICRA 2022poster

This work explores the use of topological tools for achieving effective non-prehensile manipulation in cluttered, constrained workspaces. In particular, it proposes the use of persistent homology as a guiding principle in identifying the appropriate non-prehensile actions, such as pushing, to clean…

Cited by 27 Source ↗Scholar ↗