CFU: 9
Prerequisites
Basic knowledge of: linear algebra, modeling of mechanical and electrical systems, closed loop control systems.
Preliminary Courses
None.
Learning Goals
The course aims to provide the basic skills for modeling, planning and motion control of robots.
Expected Learning Outcomes
Knowledge and understanding
The course path aims to provide students with the methodological tools for modeling, planning and control of robots. Robot components, kinematic, static and dynamic models of manipulating robots, trajectory planning techniques and control schemes are introduced. The student must demonstrate that (s)he has learned the requirements of the systems dedicated to the control of robots, on the basis of the models used. The student will also have to demonstrate knowledge in the derivation of models and in the validation of algorithms for kinematic inversion and control using simulation tools.
Applying knowledge and understanding
The student must demonstrate to be able to derive kinematic, static and dynamic models and know how to apply them to practical case studies concerning open-chain robot manipulators. Starting from these, (s)he must demonstrate that (s)he is able to design control schemes that solve the regulation and trajectory tracking problems and know how to validate them in the Matlab / Simulink® environment.
Course Content - Syllabus
- Industrial robotics and advanced robotics
- Description and principles of operation of a robot
- Direct kinematics
- Kinematic calibration
- Differential kinematics and Jacobian
- Redundancy and singularities
- Inverse kinematics algorithms
- Kineto-statics duality
- Planning of trajectories in the joint space and in the task space
- Actuators and sensors
- Control unit
- Lagrangian model
- Remarkable properties of the dynamic model
- Newton-Euler recursive algorithm
- Identification of dynamic parameters
- Direct dynamics and inverse dynamics
- Decentralized control
- Independent joint control
- Centralized control
- Computed torque control
- PD control with gravity compensation
- Inverse dynamics control
- Robust and adaptive control
- Task space control
Readings/Bibliography
- B. Siciliano, L. Sciavicco, L. Villani, G. Oriolo, Robotics – Modelling, Planning and Control, Springer, London, UK, 2009, DOI: 10.1007/978-1-84628-642-1. Italian translation: Robotica – Modellistica, Pianificazione e Controllo, McGraw-Hill Libri Italia, Milano, I, 2008
- B. Siciliano, Robotics Foundations I, MOOC available on the platform www.federica.eu
- B. Siciliano, Robotics Foundations II, MOOC available on the platform www.federica.eu
- Lecture notes available at https://prisma.dieti.unina.it/index.php/education/education-courses/34-robots-foundations
Teaching Method
The teacher will use: a) frontal lessons for about 70% of the total hours, b) classroom exercises for about 30% of the total hours.
Examination/Evaluation criteria
Exam type
Students are admitted to the oral exam after carrying out a design project in Matlab/Simulink® concerning the simulation of inverse kinematics algorithms and control systems for robot manipulators. The exam consists of a critical discussion of the paper and in ascertaining the acquisition of the concepts and contents introduced during the lessons.
Evaluation pattern
The development of the project is binding for the purposes of accessing the oral exam. The project and the oral exam each contribute 50% of the final evaluation and, therefore, the development of the project is not sufficient to pass the exam.