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Assistive Robotics
Lucio Ciabattoni

Seat Ingegneria
A.A. 2016/2017
Credits 9
Hours 72
Period II
Language ENG

Prerequisites
Basic notions of Electronics, Electrictecnology, Infomatics and Automation.

Learning outcomes
KNOWLEDGE AND UNDERSTANDING:
The course aims to provide expertise in the topics of robotics, addressing not only the simple design of mechatronic devices but also the identification of tools and devices for intervention in the biomedical and functional rehabilitation.
CAPACITY TO APPLY KNOWLEDGE AND UNDERSTANDING:
This course is mandatory and provides insight in the themes of Robotics for the design of mechatronic devices and for the identification of tools and devices for the intervention in the biomedical and functional rehabilitation field.
TRANSVERSAL SKILLS:
Capabilities of: synthesis, autonomy, clarity and work in group.

Program
The Assistive Technologies support the activities of users to improve the quality of the life. In this context the Robotics is giving an important contribution. The course is oriented to the integration of robotic devices in biomedical and rehabilitation applications. A particular attention is reserved to smart wheelchairs and assisted manipulators. List of the main topics: Robot modelling: - dynamics, - control - intelligent control Interaction man-machine: - constraints - functionality - modularity - scalability. Assistive Robotics: assisted locomotion and manipulation. Examples of significant applications in research fields and integrated into the health system

Development of the examination
LEARNING EVALUATION METHODS
Questions with discussion on the different topics of the course and presentation and discussion of the developed project, if scheduled. Of average 6 exams are planned in the fixed periods at the end of the two didactic cycles.

LEARNING EVALUATION CRITERIA
Technical and scientific knowledge of the field and evaluation of the possible applications, ability to analyse the problems of the field, ability to use design tools in the field, ability to extend the acquired tools in similar contexts.

LEARNING MEASUREMENT CRITERIA
Understanding of the questions, correctness and clarity of the exposition, completeness of responses, consistency in the analysis and synthesis, autonomy of judgment or the ability of critical thinking and formulation of judgments.

FINAL MARK ALLOCATION CRITERIA
The exam consists of three questions (the third one will focus on the project if developed), and for each question is assigned a score of 10 equivalent to a optimal assessment, a score of 8 for a good assessment, a score of 7 for a full sufficient assessment and a score of 6 for a just sufficient assessment.

Recommended reading
Bruno Siciliano, Lorenzo Sciavicco, Luigi Villani, Giuseppe Oriolo, Robotics: Modelling, Planning and Control, Springer Science & Business Media, 2009 King Sun Fu, Rafael C. González, C. S. George Lee, Robotics: control, sensing, vision, and intelligence, McGraw-Hill, 1987 . Annalisa Morini, Fiorenza Scotti, “ASSISTIVE TECHNOLOGY – Tecnologie di supporto per una vita indipendente”, Maggioli Editore, 2005 (in Italian language)

Courses

• Biomedical Engineering (Corso di Laurea Magistrale (DM 270/04))