Luis Montano — accepted AI-conference papers

2025

Hey Robot! Personalizing Robot Navigation Through Model Predictive Control with a Large Language Model

Diego Martinez-Baselga, Oscar de Groot, Luzia Knödler, Javier Alonso-Mora, Luis Riazuelo, Luis Montano

ICRA 2025

Robot navigation methods allow mobile robots to operate in applications such as warehouses or hospitals. While the environment in which the robot operates imposes requirements on its navigation behavior, most existing methods do not allow the end-user to configure the robot's behavior and priorities

Cited by 3 Source ↗Scholar ↗

2024

G-Loc: Tightly-Coupled Graph Localization With Prior Topo-Metric Information

Lorenzo Montano-Oliván, Julio A. Placed, Luis Montano, María Teresa Lázaro

RA-L 2024

Localization in already mapped environments is a critical component in many robotics and automotive applications, where previously acquired information can be exploited along with sensor fusion to provide robust and accurate localization estimates. In this letter, we offer a new perspective on map-b

Cited by 8 Source ↗Scholar ↗

2023

Improving robot navigation in crowded environments using intrinsic rewards

Diego Martinez-Baselga, Luis Riazuelo, Luis Montano

ICRA 2023poster

Autonomous navigation in crowded environments is an open problem with many applications, essential for the coexistence of robots and humans in the smart cities of the future. In recent years, deep reinforcement learning approaches have proven to outperform model-based algorithms. Nevertheless, even…

Cited by 20 Source ↗code ↗Scholar ↗

2015

Layout aware visual tracking and mapping

Marta Salas, Wajahat Hussain, Alejo Concha, Luis Montano, Javier Civera, J. M. M. Montiel

IROS 2015poster

Nowadays real time visual Simultaneous Localization And Mapping (SLAM) algorithms exist and rely on consistent measurements across multiple views. In indoor environments, where majority of robot's activity takes place, severe occlusions can occur, e.g., when turning around a corner or moving from on…

Cited by 25 Source ↗Scholar ↗