This Ph.D. course provides an overview on modelling and design of robotic machines using the embodied mechanical intelligence concept for pursuing sustainable goals.
Basic concepts on dynamics, modelling, and design of mechanisms, machines, and robots will be studied during the course. Additionally, the course will provide an outline of sensors and actuators that are typically employed in robotic intelligence machines (such as legged robots and exoskeletons). Methodologies for designing simplified machines and robots will be learned during the course. One important content of the course will be focused on handle problems for modelling and simulating the mechanical behaviour of a sustainable machine.
Physical interaction (human-machine, machine-machine, machine-environment) will be designed with a sustainable approach using the intelligence embodied in mechanical systems (e.g., using variable stiffness sensors and actuators).
The Ph.D. course will be focused on understanding the mechanical and mechatronic behaviour of a system with the general approach underlined in the Italian S.S.D. (Settore Scientifico Disciplinare) ING-IND/13 - Meccanica Applicata alle Machine
(National Declaratory (in Italian): http://attiministeriali.miur.it/media/265757/allegato_b.pdf).
Ph.D. course is divided in two parts:
• First part: examples of real robots and machines will be studied, underlining critical points of sustainability in mechanical design;
• Second part: each Ph.D. candidate will start a Sustainable Mechanical Intelligence Project (SMIP) for studying the behaviour of a sustainable machine (or robot).
• (2h) An Introduction to Sustainable Embodied Mechanical Intelligence (SEMI)
• (2h) Sustainable Embodied Mechanical Intelligence Project (SEMIP)
• (2h) Fundamentals of Mechanics and Mechanical Intelligence
• (2h) Functional Design of Sustainable Machines - part 1
• (2h) Functional Design of Sustainable Machines - part 2
• (2h) Elements of Dynamic of Machinery - part 1
• (2h) Elements of Dynamic of Machinery - part 2
The final validation of the course will be performed analysing the submitted SEMIP (Sustainable Embodied Mechanical Intelligence Project) report by each participant.
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