4 citations · 5 across the 5 of their papers we have counts for
5 papers
Learning Stack-of-Tasks Management for Redundant Robots
Alessandro Adami, Aris Synodinos, Matteo Iovino +2
This paper presents a novel framework for automatically learning complete Stack-of-Tasks (SoT) controllers for redundant robotic systems, including task priorities, activation logi…
Towards Autonomous Reinforcement Learning for Real-World Robotic Manipulation with Large Language Models
Niccolò Turcato, Matteo Iovino, Aris Synodinos +3
Recent advancements in Large Language Models (LLMs) and Visual Language Models (VLMs) have significantly impacted robotics, enabling high-level semantic motion planning application…
Comparison between Behavior Trees and Finite State Machines
Matteo Iovino, Julian Förster, Pietro Falco +3
Behavior Trees (BTs) were first conceived in the computer games industry as a tool to model agent behavior, but they received interest also in the robotics community as an alternat…
A Framework for Learning Behavior Trees in Collaborative Robotic Applications
Matteo Iovino, Jonathan Styrud, Pietro Falco +1
In modern industrial collaborative robotic applications, it is desirable to create robot programs automatically, intuitively, and time-efficiently. Moreover, robots need to be cont…
On the programming effort required to generate Behavior Trees and Finite State Machines for robotic applications
Matteo Iovino, Julian Förster, Pietro Falco +3
In this paper we provide a practical demonstration of how the modularity in a Behavior Tree (BT) decreases the effort in programming a robot task when compared to a Finite State Ma…