91411 - INTELLIGENT ROBOTIC SYSTEMS

Anno Accademico 2023/2024

  • Docente: Andrea Roli
  • Crediti formativi: 6
  • SSD: ING-INF/05
  • Lingua di insegnamento: Inglese
  • Modalità didattica: Convenzionale - Lezioni in presenza
  • Campus: Cesena
  • Corso: Laurea Magistrale in Ingegneria e scienze informatiche (cod. 8614)

Conoscenze e abilità da conseguire

At the end of the course, students have acquired knowledge and competencies for designing a system composed of one or more robots (here, we call "robot" an autonomous system which exists in the physical world, can sense its environment and can act on it to achieve some goals). In particular, students know the main models, methods, architectures and tools for programming robots equipped with nontrivial computational and cognitive capabilities.

Contenuti

Introduction to robotics

  • Brief history of robotics
  • Notions of robot and its behavior in a physical environment
  • Main issues in intelligent robotic systems design

 

Behavior-based robotics

  • Overview of main paradigms for coordinating behaviours
  • The Subsumption Architecture
  • Motor schemas
  • Fuzzy logic and fuzzy systems
  • Behaviour trees
  • Experimental evaluation and parameter tuning of control software for robots: practical guidelines
  • Artificial Evolution and Evolutionary Robotics
  • Automatic design of robot programs
  • Swarm robotics

 

 Robot learning

  • Associative learning
  • Reinforcement learning
  • Value-based learning and intrinsic motivation

Deliberative control

  • Informed search algorithms. A* and its variants for path planning problems
  • Robot planning: main definitions and principles
  • STRIPS and its extensions
  • Nonlinear planning
  • Navigation problems and main solution approaches

 


Lab activities
Experiments with robotic simulators with the aim of experiencing with the various kinds of control and testing the knowledge acquired.

Testi/Bibliografia

Course textbooks:

  • S. Nolfi, "Behavioral and Cognitive Robotics - An adaptive perspective", CNR-ISTC, 2021. Available for download: https://bacrobotics.com/
  • R. Pfeifer and C. Scheier, "Understanding intelligence", The MIT Press, 1999.


Additional books:

  • R. Pfeifer and J. Bongard, "How the body shapes the way we think", The MIT Press, 2007.
  • M. Mataric, "The Robotic Primer", The MIT Press, 2007.
  • U. Nehmzow, Robot Behaviour: Design, Description, Analysis and Modelling, Springer, 2009.

 

Papers and further teaching matters are available from the course website. 

Metodi didattici

The course is composed of class lessons and lab activities. The latter activities will be organised such that students will have the opportunity of tackling the main issues in devising control programs for robots and making experience of the knowledge acquired during the lessons in the class. Whenever possible, students will be invited to work in teams.

Modalità di verifica e valutazione dell'apprendimento

The final exam aims at evaluating the extent to which students have reached the teaching objectives, i.e., the knowledge of the subjects taught in the course and the capability of designing and programming a robotic system.

The final assessment is composed of two parts:

  1. Practical activity (50% of the overall final mark)
  2. Oral exam (50% of the overall final mark)

The practical activity can be either of these two:

  • The student has actively participated to the lab sessions and has successfully submitted the solutions produced; or
  • a project developed by the students, possibly in small groups.

The grade of Part 1 is based on the evaluation of the student's attitude to tackle the problem presented, considering the capability of analysing the problem and applying a scientific approach to the design and development of a software control for robots.

The grade of Part 2 is based on the assessment of the knowledge acquired according to four main criteria: context, clarity, precision and depth.

Besides the usual six exam dates per year, students can take the exam also by advance arrangement with the teacher. 

Strumenti a supporto della didattica

Students will be given teaching material prepared by the teacher (slides and papers published in journals and conferences). In addition, lab activities will make use of robotic simulators (e.g., ARGoS).

The course textbooks and the teaching material provided cover all the topics presented in the course.

Orario di ricevimento

Consulta il sito web di Andrea Roli