5 citations · 5 across the 5 of their papers we have counts for
5 papers
VLMs Can Describe, But Not Measure: Object-Centric Scene Understanding for Robotic Manipulation
Enrico Saccon, Tommaso Faraci, Iñigo De La Ossa Zarzuelo +3
Robotic operation in previously unseen environments requires both semantic understanding and reliable metric information. While vision--language models (VLMs) provide strong semant…
Automated Generation of MDPs Using Logic Programming and LLMs for Robotic Applications
Enrico Saccon, Davide De Martini, Matteo Saveriano +3
We present a novel framework that integrates Large Language Models (LLMs) with automated planning and formal verification to streamline the creation and use of Markov Decision Proc…
Combining Large Language Models and Symbolic Reasoning for Multi-Robot Temporal Planning through Explainable Knowledge Bases
Enrico Saccon, Matteo Saveriano, Edoardo Lamon +2
We present PLANTOR, a framework for generating and executing multi-robot task plans from natural-language task descriptions through LLM-assisted knowledge-base construction. The ap…
Fast Shortest Path Polyline Smoothing With Continuity and Bounded Curvature
Patrick Pastorelli, Simone Dagnino, Enrico Saccon +2
In this work, we propose a novel and efficient method for smoothing polylines in motion planning tasks. The algorithm applies to motion planning of vehicles with bounded curvature.…
When Prolog meets generative models: a new approach for managing knowledge and planning in robotic applications
Enrico Saccon, Ahmet Tikna, Davide De Martini +3
In this paper, we propose a robot oriented knowledge management system based on the use of the Prolog language. Our framework hinges on a special organisation of knowledge base tha…