Scheda programma d'esame
Anno accademico2017/18
PeriodoSecondo semestre

Learning outcomes

The students acquire knowledge and experience in how to build a robot with state-of-the-art technologies. They learn the basic scheme of a robotic system and the fundamental approaches to build and integrate the different components. They include fundamentals of kinematics and control, main proprioceptive and exteroceptive sensors, architectures for robot behavior, basics of humanoid robotics and of robot navigation. They then learn how bioinspired approaches can be applied alternatively to the same problems and acquire knowledge on neurocontrollers, bioinspired sensing, embodied intelligence and neuromorphic computing. When appropriate, focused glimpses on cutting-edge research are also given to the students.

Assessment criteria of knowledge

The knowledge acquired by the students is assessed through an oral exam. A written test may replace the oral exam, once, at the end of classes.


The students also have the opportunity to challenge themselves in building and/or programming a robot, during hands-on and projectual lessons, usually in small groups, in a robotic lab. In this way they acquire additional skills in design and development, in robot programming, in lab work and in experimental activity, as well as in teamwork. This projectual work is accompanied by a presentation, which provides an opportunity to improve the scientific/technical communication skills.

Assessment criteria of skills

The skills acquired are assessed through a presentation with a demonstration of the projectual work done by the students.


Especially through the projectual work, the students will acquire ability of team working and experimental activities.

This course exposes the students to lateral thinking about the implications of robotics, on the ethical or social side at large.

Assessment criteria of behaviors

The behaviors acquired are not assessed directly, but indirectly through the presentation of the projectual work.




Courses on neural networks and artificial intelligence can be beneficially taken together with this course on robotics.

Prerequisites for further study


Teaching methods

The course consists of classes on the different topics of the programme and of hands-on and projectual activities where the knowledge acquired in the classes can be put in practice.

The classes are taught with the support of slides that are provided to the students as material to study, together with possible additional specific materials taken from books and papers.

The hands-on classes are done in a robotic lab with the support of robotic kits or research prototypes. Several projects are proposed to the students, which are recommended to accomplish them in small groups (1 to 3 students).

  • Robot mechanics and kinematics
  • Robot sensors
  • Robot control
  • Robot vision
  • Architectures for behaviour control
  • Robot navigation techniques
  • Bioinspired senses
  • Humanoid robotics
  • Neurocontrollers
  • Embodied intelligence & soft robotics

M. Mataric, A robotics primer, MIT Press, 2007

T. Bajd, M. Mihelj, J. Lenarcic, A. Stanovnik, M. Munih, Robotics, Springer, 2010.

S. Kajita, H. Hirukawa, K. Harada, K. Yokoi, Introduction to Humanoid Robotics, Springer, 2014.

Non-attending students info

 The course materials are thoroughly provided at the course web page:

Assessment methods

 The exam consists of two parts and the final mark is the average of the marks obtained in the two parts:

1. course programme, assessed through an oral test. An optional written test mey be organized by the teacher, once, at the end of the classes. It can replace the oral test.

2. projectual work, assessed through a presentation with demonstration.

Work placement


Additional web pages




Ultimo aggiornamento 31/07/2017 16:29