OVERVIEW

The experimental aspect is fundamental in robotics, in which various theoretical skills (automatic controls, computer vision, software architectures, real-time programming, ...) are merged in concrete systems and mechatronic platforms. The course aims to provide students with a methodology to accomplish this fusion and bridge the gap between theory and practical implementation, through lectures, exercises, and projects. In particular, the course will provide elements to perform robotic simulations involving software architecture design, computer vision, planning and mapping.

AIMS AND CONTENT

LEARNING OUTCOMES

The course's aim is to put into action the theoretical knowledge acquired in other courses, providing some robotic setups for specific implementations. The course will also include methodological information on experiments design and validation of results.

AIMS AND LEARNING OUTCOMES

Active participation in the proposed training activities (lectures and laboratory activities), individual study and the realization of projects, students will be able to:

- use software frameworks for robotics (ROS/ROS2);

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

- implement a robotic simulation, using software tools such as Gazebo;

- use AI Planning frameworks for robotics;

- create new robotic models and simulation control plugins, thus having complete control over the simulation environment;

- know, modify and use algorithms for navigating mobile robots in unstructured environments;

- use cloud systems for robot control;

- implement simple controllers for robot manipulators in a simulation environment;

- develop imagination and creativity, critical reflection, strategic thinking (Open Badge: proficiency in project design).

PREREQUISITES

Since the main objective of the course is to practice theoretical aspects learned in other disciplines, the following knowledge is necessary to face the course optimally:

- software architectures for robotics

- ROS (Robot Operating System)

- programming (C ++, python)

TEACHING METHODS

Teaching methods consist of frontal lessons and class exercises.

During frontal lessons, examples related to the implementation of the different aspects will be shown.

There will be practical exercises and projects, to be carried out in groups, using the Rosbots 2.0 robotic platforms. 

Working students and students with certification of DSA, disability, or other special educational needs are advised to contact the teacher at the beginning of the course to agree on teaching and exam methods which, in compliance with the teaching objectives, take into account the methods of individual learning.

SYLLABUS/CONTENT

The course program consists of the following topics:

- ROS/ROS2 and Software Architectures

- Software Designing Process

- Robot Modelling with Gazebo and ROS: URDF and XACRO

- ROSPlan

- OpenCV and ROS

- Path planning and SLAM for mobile robots: theory and implementation

- Manipulators and the MoveIt library

- REST-API

A Docker images, with a full ROS/ROS2 installation and some libraries will be given at the beginning of the course.

Practical exercises will be developed by means of robotic platforms (robot ROSbot 2.0)

RECOMMENDED READING/BIBLIOGRAPHY

All slides shown during the lessons and other teaching materials will be available on the Aulaweb platform. Generally speaking, notes taken during the lessons and teaching materials uploaded on Aulaweb will be sufficient for the course.

TEACHERS AND EXAM BOARD

Exam Board

CARMINE TOMMASO RECCHIUTO (President)

GIOVANNI MOTTOLA

ANTONIO SGORBISSA (President Substitute)

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 course, students will have to implement two projects, individually or in groups, based on the contents of the course.

The final exam will consist of a written exam and practical exercises. 

The final evaluation will be composed of the evaluation of the projects (50%) and the evaluation of the final written / practical exam (50%).

ASSESSMENT METHODS

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

- Acquired knowledge about the implementation of robotic simulations.

- Ability to apply correct methodologies for the practical solution of theoretical problems.

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

Exam schedule