|Teoria||3||II semestre||Riccardo Muradore|
|Laboratorio||3||II semestre||Riccardo Muradore|
The course aims to provide the theoretical foundations of teleoperation systems and physical interaction with the environment, with particular focus on the design of control architectures able to guarantee the stability of such systems even in the presence of uncertainty and communication delay.
At the end of the course the student should demonstrate that s/he has acquired the knowledge to analyze the technical characteristics and structural properties of a control system for direct or teleoperated interaction with the environment.
This knowledge will allow the student: i) to build the mathematical model of a teleoperation system; ii) to model physical human-robot interaction systems; iii) to design a control architecture to guarantee the stability; iv) to implement the control structure in Matlab/Simulink and/or in ROS (Robot Operating System).
At the end of the course the student will have acquired the ability to define the technical specifications for physical human-robot interaction systems and for bilateral teleoperation systems, and consequently to choose the most appropriate approach of designing the control architecture.
It will also be able: i) to work together with other engineers (e.g. electronic, control, mechanical engineers) to design advanced control architectures for complex physical human-robot interaction systems and teleoperation systems; ii) to enhance his/her knowledge on the design of control architectures based on stochastic and non-linear methods.
Advanced topics that will be addressed during the course:
- manipulator dynamics
- motion control (PID)
- force control (force and impedance)
- passivity theory
- advanced algorithms for teleoperation
- communication time delay compensation
Topics that will be addressed during the lab activity:
- Tuning of PID controllers
- Implementation of velocity estimators
- Data-driven system identification
- Implementation of bilateral teleoperation algorithms in ROS/Matlab-Simulink
TEACHING AIDS: During the course, lecture notes, slides and scientific papers will be provided.
The exam will consist of a project addressing some topics discussed during the course. The student should have to implement in ROS (and/or in Matlab/Simulink) a teleoperation algorithm, test it, and prepare a brief technical document explaining his/her work.
To pass the exam, the student should:
- have understood the principles related to the design of a bilateral teleoperation system,
- be able to use the knowledge acquired during the course to solve the assigned problem,
- be able to describe their work by explaining and motivating the design choices.
|Title||Format (Language, Size, Publication date)|
|Chapter Bode Diagram||zip (it, 353 KB, 31/03/19)|
|Chapter Nyquist||zip (it, 482 KB, 15/04/19)|
|Chapter PID||zip (it, 244 KB, 31/03/19)|
|Chapter Specifications||zip (it, 329 KB, 31/03/19)|
|Chopra-Spong-Lozano Algorithm||zip (it, 544 KB, 11/05/19)|
|Dati Banchetto teleoperazione||zip (it, 2248 KB, 08/04/19)|
|DC motors||zip (it, 2149 KB, 25/03/19)|
|Franken et Al Algortihm||zip (it, 1281 KB, 26/05/19)|
|Intro Teleoperation Part I||zip (it, 2578 KB, 06/03/19)|
|Intro Teleoperation Part II||zip (it, 1224 KB, 06/03/19)|
|Lee-Huang Algortihm||zip (it, 961 KB, 26/05/19)|
|Lee-Spong Algorithm||zip (it, 725 KB, 11/05/19)|
|Niemeyer-Slotine Algorithm||zip (it, 641 KB, 29/04/19)|
|Passivity||zip (it, 390 KB, 15/04/19)|
|PID controllers||zip (it, 566 KB, 11/05/19)|
|Ryu-Artigas-Preusche Algorithm||zip (it, 831 KB, 11/05/19)|
|Statistical filtering||zip (it, 333 KB, 08/04/19)|
|Teleoperation without comm. delay||zip (it, 464 KB, 31/03/19)|