Noé Pérez-Higueras — accepted AI-conference papers

2024

Adaptive Social Force Window Planner with Reinforcement Learning

Mauro Martini, Noé Pérez-Higueras, Andrea Ostuni, Marcello Chiaberge, Fernando Caballero, Luis Merino

IROS 2024poster

Human-aware navigation is a complex task for mobile robots, requiring an autonomous navigation system capable of achieving efficient path planning together with socially compliant behaviors. Social planners usually add costs or constraints to the objective function, leading to intricate tuning proce…

Cited by 3 Source ↗Scholar ↗

2023

HuNavSim: A ROS 2 Human Navigation Simulator for Benchmarking Human-Aware Robot Navigation

Noé Pérez-Higueras, Roberto Otero, Fernando Caballero, Luis Merino

RA-L 2023

This work presents the Human Navigation Simulator ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">HuNavSim</i> ), a novel open-source tool for the simulation of different human-agent navigation behaviors in scenarios with mobile robots. The tool, t

Cited by 39 Source ↗code ↗Scholar ↗

2018

Learning Human-Aware Path Planning with Fully Convolutional Networks

Noé Pérez-Higueras, Fernando Caballero, Luis Merino

ICRA 2018poster

This work presents an approach to learn path planning for robot social navigation by demonstration. We make use of Fully Convolutional Neural Networks (FCNs) to learn from expert's path demonstrations a map that marks a feasible path to the goal as a classification problem. The use of FCNs allows us…

Cited by 74 Source ↗Scholar ↗