Giulio Campagna

Giulio Campagna
Aalborg University · Technical Faculty of IT and Design

Master of Engineering
The research aims to develop ML algorithms using multi-modal sensor data to improve safety, trust, and ergonomics in HRC

About

7
Publications
62
Reads
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7
Citations
Introduction
Born the 3rd of May 1995 in Siena, Italy. Received B.S. degree in Computer and Information Engineering in 2018 from the University of Siena. Received M.S. degree in Computer and Automation Engineering - Robotics and Automation in 2021 from the University of Siena. PhD Fellow at Aalborg University, Human-Robot Interaction Laboratory. The research aims to develop ML algorithms using multi-modal sensor data to improve safety, trust, and ergonomics in HRC.
Additional affiliations
May 2024 - June 2024
German Aerospace Center (DLR)
Position
  • Visiting Researcher
October 2023 - February 2024
Istituto Italiano di Tecnologia
Position
  • Visiting Researcher
Description
  • The framework leverages Preference-Based Optimization (PBO) and considers three key interaction parameters: the robot's velocity profile, separation distance from the human, and vertical proximity to the user's head. By refining these based on human feedback, the system dynamically adjusts robot trajectories to ensure a safe, ergonomic environment. A chemical scenario served as the testbed.
September 2020 - November 2020
Aarhus University
Position
  • Trainee
Description
  • Simulated a virtual environment in Unity3D and controlled an avatar hand using OptiTrack Motive software. For more details, visit https://www.campagna-robotics.com/commanding-grasping-robot.
Education
January 2022 - January 2025
Aalborg University
Field of study
  • Human-Robot Collaboration
October 2018 - April 2021
Università degli Studi di Siena
Field of study
  • Computer and Automation Engineering - Robotics and Automation
October 2014 - October 2018
Università degli Studi di Siena
Field of study
  • Computer and Information Engineering

Publications

Publications (7)
Article
This paper proposes a novel theoretical framework for promoting trust in human-robot collaboration (HRC). The framework exploits Preference-Based Optimization (PBO) and focuses on three key interaction parameters: robot velocity profile, human-robot separation distance, and vertical proximity to the user's head. By iteratively refining these parame...
Chapter
The role of trust in human-robot interaction (HRI) is becoming increasingly important for effective collaboration. Insufficient trust may result in disuse, regardless of the robot’s capabilities, whereas excessive trust can lead to safety issues. While most studies of trust in HRI are based on questionnaires, in this work it is explored how partici...
Thesis
Nowadays, the need to manipulate objects in hostile environments, through natural movements of the human’s body, has led to the development of several teleoperation interfaces. Nevertheless, during the teleoperation of the robot, the direct vision of the environment and of the robot through the camera involves non-ergonomic user behaviors and occlu...

Network

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