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cs.RO2026

From Language to Navigation Goals: A Vision-Language Approach for Semantic Navigation of Mobile Robots Using RGB-D Perception

Jose Martínez-Fajardo, Pablo Pueyo, Fernando Caballero +1

Natural language interaction provides an intuitive way for non-expert users to communicate with robotic platforms. However, transforming user requests into executable navigation ac…

cs.RO2026

Navigating the Crowd: Non-linear MPC with Social Forces Dynamics for Human-Aware Robot Navigation

Stefano Trepella, Andrea Ostuni, Mauro Martini +5

Safe and socially compliant navigation remains a fundamental challenge for autonomous robots operating in human-populated environments. Beyond collision avoidance, robots must anti…

cs.RO2025

CineWild: Balancing Art and Robotics for Ethical Wildlife Documentary Filmmaking

Pablo Pueyo, Fernando Caballero, Ana Cristina Murillo +1

Drones, or unmanned aerial vehicles (UAVs), have become powerful tools across domains-from industry to the arts. In documentary filmmaking, they offer dynamic, otherwise unreachabl…

cs.RO2024

Gen-Swarms: Adapting Deep Generative Models to Swarms of Drones

Carlos Plou, Pablo Pueyo, Ruben Martinez-Cantin +3

Gen-Swarms is an innovative method that leverages and combines the capabilities of deep generative models with reactive navigation algorithms to automate the creation of drone show…

cs.RO20242 cited

CLIPSwarm: Generating Drone Shows from Text Prompts with Vision-Language Models

Pablo Pueyo, Eduardo Montijano, Ana C. Murillo +1

This paper introduces CLIPSwarm, a new algorithm designed to automate the modeling of swarm drone formations based on natural language. The algorithm begins by enriching a provided…