OVERVIEW

Experimental work is a fundamental aspect of robotics, where theoretical knowledge from automatic control, computer vision, software architectures, and real-time programming is integrated into real robotic systems and mechatronic platforms. The course aims to provide students with a methodology for bridging the gap between theory and practical implementation through lectures, laboratory activities, and projects. In particular, the course introduces methods and tools for robotic simulation, software architecture design, computer vision, planning, and mapping.

AIMS AND CONTENT

LEARNING OUTCOMES

The course aims to provide students with practical and theoretical skills for developing advanced robotic applications. It covers robot modeling for simulation, the integration of computer vision and planning libraries with ROS and ROS2, the use of the ROS and ROS2 navigation stack, and the implementation of REST APIs for robotic systems.

AIMS AND LEARNING OUTCOMES

Through active participation in lectures and laboratory activities, individual study, and the completion of course projects, students will be able to:

- use robotic software frameworks, particularly ROS2;

- design a modular and functional software architecture for a mobile robot;

- develop robotic simulations using tools such as Gazebo;

- use AI planning frameworks for robotic applications;

- create robotic models and simulation-control plugins, achieving full control over the simulation environment;

- use computer vision libraries in robotic simulations;

- understand, modify, and apply navigation algorithms for mobile robots operating in unstructured environments.

PREREQUISITES

Since the course focuses on the practical application of concepts introduced in other subjects, students are expected to have prior knowledge of:

- ROS2 (Robot Operating System)

- programming (C ++, python)

TEACHING METHODS

The course consists of lectures, laboratory activities, and guided practical exercises.

During lectures, practical examples illustrating the implementation of the presented concepts will be discussed.

Students will complete practical exercises and project activities, individually or in small groups, using ROSbot 2.0 robotic platforms.

Students with valid certifications for Specific Learning Disorders (SLDs), disabilities or other educational needs are invited to contact the teacher and the School's contact person for disability at the beginning of teaching to agree on possible teaching arrangements that, while respecting the teaching objectives, take into account individual learning patterns. Contacts of the teacher and the School's disability contact person can be found at the following link Comitato di Ateneo per l’inclusione delle studentesse e degli studenti con disabilità o con DSA | UniGe | Università di Genova

SYLLABUS/CONTENT

The course program consists of the following topics:

- ROS2 and Software Architectures

- Software Designing Process

- Robot Modelling with Gazebo and ROS2: URDF and XACRO

- PlanSys2 for AI Planning

- OpenCV Integration with ROS2

- Path Planning and SLAM for Mobile Robots: Theory and Implementation

A Docker image containing a complete ROS 2 installation and the software libraries required for the course will be provided at the beginning of the semester.

Practical exercises will be carried out using ROSbot 2.0 mobile robotic platforms.

RECOMMENDED READING/BIBLIOGRAPHY

Lecture slides, laboratory material, and additional resources will be made available through AulaWeb. The provided teaching material is sufficient for exam preparation and project development.

Students with valid certifications for Specific Learning Disorders (SLDs), disabilities or other educational needs are invited to contact the teacher and the School's contact person for disability at the beginning of teaching to agree on possible teaching arrangements that, while respecting the teaching objectives, take into account individual learning patterns. Contacts of the teacher and the School's disability contact person can be found at the following link Comitato di Ateneo per l’inclusione delle studentesse e degli studenti con disabilità o con DSA | UniGe | Università di Genova

TEACHERS AND EXAM BOARD

LESSONS

LESSONS START

https://easyacademy.unige.it/portalestudenti/index.php?view=easycourse&_lang=it&include=corso

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

During the semester, students will develop two projects, either individually or in groups, based on the topics covered in the course.

The final examination consists of a written practical assessment.

The final grade is determined by the evaluation of the course projects (35%) and the final written/practical examination (65%).

ASSESSMENT METHODS

The final exam and the projects aim to ascertain the following aspects of the students' preparation:

- Knowledge of methodologies and tools for robotic simulation.

- Ability to apply appropriate methodologies to the practical implementation of theoretical concepts.

- Ability to adopt software architectures suitable for solving robotic problems.