Workshop: Neuromorphic and Neurorobotics
A.Y. 2026/2027
Learning objectives
Introduction to the design principles of neuromorphic and neurorobotic systems, with reference to design criteria, analysis of application case studies, and the main technological challenges and experimental approaches in Physical AI.
Expected learning outcomes
By the end of the workshop, students will be able to:
- understand the principles of neuromorphic and neurorobotic system design for human-centered applications, including neurocontrol models, human-machine interfaces, and Physical AI;
- apply design criteria for Physical AI-based systems in relation to specific applications, also through hands-on activities and case studies;
- critically evaluate solutions and case studies in the field of Physical AI and neurorobotics;
- effectively present and discuss project results, working collaboratively and using appropriate disciplinary terminology;
- develop autonomous learning skills to remain updated and operate in interdisciplinary contexts.
- understand the principles of neuromorphic and neurorobotic system design for human-centered applications, including neurocontrol models, human-machine interfaces, and Physical AI;
- apply design criteria for Physical AI-based systems in relation to specific applications, also through hands-on activities and case studies;
- critically evaluate solutions and case studies in the field of Physical AI and neurorobotics;
- effectively present and discuss project results, working collaboratively and using appropriate disciplinary terminology;
- develop autonomous learning skills to remain updated and operate in interdisciplinary contexts.
Lesson period: First semester
Assessment methods: Giudizio di approvazione
Assessment result: superato/non superato
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Lesson period
First semester
Course syllabus
The workshop introduces the design principles of neuromorphic and neurorobotic systems within the framework of Physical AI and the human-centered approach, highlighting the links between neuroscience, artificial intelligence, and robotics. As a workshop, it emphasizes an application-oriented and interactive approach, based on case studies and critical discussion. It covers design principles of neuromorphic systems (neural models, neuromorphic computation, sensor-actuator integration) and bioinspired neurorobotics (embodiment, biorobotics, soft and underactuated systems).
Specific focus is placed on neurocontrol and sensorimotor integration (motor control, learning, motor intention), as well as on human-robot interaction and human-machine interfaces (neural and wearable interfaces, cooperation, teleoperation). The workshop also addresses sensory feedback and artificial touch (sensing systems, feedback strategies, closing the perception-action loop).
Finally, advanced applications of neurorobotics are examined, including cybernetic prostheses and exoskeletons (functional substitution, rehabilitation, personal assistance) and key domains of Physical AI (neurorehabilitation, assistive and humanoid robotics). The programme concludes with technological challenges and future perspectives, including advanced materials, human-machine integration, and ethical and societal implications.
Specific focus is placed on neurocontrol and sensorimotor integration (motor control, learning, motor intention), as well as on human-robot interaction and human-machine interfaces (neural and wearable interfaces, cooperation, teleoperation). The workshop also addresses sensory feedback and artificial touch (sensing systems, feedback strategies, closing the perception-action loop).
Finally, advanced applications of neurorobotics are examined, including cybernetic prostheses and exoskeletons (functional substitution, rehabilitation, personal assistance) and key domains of Physical AI (neurorehabilitation, assistive and humanoid robotics). The programme concludes with technological challenges and future perspectives, including advanced materials, human-machine integration, and ethical and societal implications.
Prerequisites for admission
Students are expected to have an interdisciplinary background in AI and neuroscience. Familiarity with the principles of human-machine interaction and sensory feedback in artificial systems is beneficial. No prior experience in robotics is required. The course is particularly suited for students interested in human-machine interfaces, embodied and Physical AI.
Teaching methods
The workshop combines frontal lectures with in-person interactive activities. The first six hours will consist of introductory lectures aimed at presenting key concepts. The course will then shift to interactive sessions based on the analysis of real-world case studies, including small-group work and class discussions. Students will be actively engaged in the critical discussion of the cases, highlighting key aspects in relation to the workshop learning objectives.
Teaching Resources
Reference materials include the book The Robot and Us. Additional learning materials, including research articles and essays on specific topics in neuromorphic and neurorobotics, will be provided during the course.
The Robots and us, An'Antidisciplinary' Perspective on the Scientific and Social Impacts of Robotics, Springer Nature Switzerland AG 2019, https://doi.org/10.1007/978-3-319-97767-6
The Robots and us, An'Antidisciplinary' Perspective on the Scientific and Social Impacts of Robotics, Springer Nature Switzerland AG 2019, https://doi.org/10.1007/978-3-319-97767-6
Assessment methods and Criteria
Assessment is based on a final project work carried out in groups of three students, focusing on the analysis of a case study selected by the students on Physical AI and neuromorphic and neurorobotic approaches. The project is developed as a presentation and discussed in class during the final two sessions. The outcome is expressed as an approval decision, subject to the completion and discussion of the project.
- University credits: 3
Humanities workshop : 36 hours
Professor:
Carrozza Maria Chiara