collaborators

5 papers

cs.RO2026

Language-Driven Cost Optimization for Autonomous Driving

Diego Martinez-Baselga, Khaled Mustafa, Javier Alonso-Mora

The driving behavior of autonomous vehicles is typically governed by the cost function of their motion planner, which encodes objectives such as speed tracking, smoothness, lane ke…

cs.RO2025

SHINE: Social Homology Identification for Navigation in Crowded Environments

Diego Martinez-Baselga, Oscar de Groot, Luzia Knoedler +3

Navigating mobile robots in social environments remains a challenging task due to the intricacies of human-robot interactions. Most of the motion planners designed for crowded and…

cs.RO2025

RUMOR: Reinforcement learning for Understanding a Model of the Real World for Navigation in Dynamic Environments

Diego Martinez-Baselga, Luis Riazuelo, Luis Montano

Autonomous navigation in dynamic environments is a complex but essential task for autonomous robots, with recent deep reinforcement learning approaches showing promising results. H…

cs.RO2025

AVOCADO: Adaptive Optimal Collision Avoidance driven by Opinion

Diego Martinez-Baselga, Eduardo Sebastián, Eduardo Montijano +3

We present AVOCADO (AdaptiVe Optimal Collision Avoidance Driven by Opinion), a novel navigation approach to address holonomic robot collision avoidance when the robot does not know…

cs.RO2025

Improving robot navigation in crowded environments using intrinsic rewards

Diego Martinez-Baselga, Luis Riazuelo, Luis Montano

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 re…