Learning outcomes

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.

Program

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.

Examination Methods

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.

Teaching materials e documents

•   Bode chapter   (zip, it, 353 KB, 3/28/18)
•   Chopra-Spong-Lozano algorithm   (zip, it, 544 KB, 5/11/18)
•   DC motors   (zip, it, 2150 KB, 3/9/18)
•   Franken et al. Algorithm   (zip, it, 1281 KB, 5/17/18)
•   Intro Teleoperation Part I   (zip, it, 2911 KB, 3/9/18)
•   Intro Teleoperation Part II   (zip, it, 1546 KB, 3/9/18)
•   Lee-Huang algorithm   (zip, it, 961 KB, 5/17/18)
•   Lee Spong Algorithm   (zip, it, 724 KB, 5/10/18)
•   Modello Simulink teleoperazione   (zip, it, 53 KB, 6/1/18)
•   Niemeyer Slotine Algorithm   (zip, it, 640 KB, 5/3/18)
•   Nyquist chapter   (zip, it, 482 KB, 3/28/18)
•   Passivity   (zip, it, 390 KB, 3/28/18)
•   PID chapter   (zip, it, 244 KB, 3/28/18)
•   PID controllers   (zip, it, 566 KB, 3/28/18)
•   Ryu-Artigas-Preusche algorithm   (zip, it, 831 KB, 5/17/18)
•   Spec chapter   (zip, it, 329 KB, 3/28/18)
•   Statistical filtering   (zip, it, 333 KB, 4/17/18)
•   Teleoperation without delays   (zip, it, 462 KB, 3/28/18)
•   Time series   (zip, it, 2248 KB, 4/19/18)