- B. Siciliano, L. Sciavicco, L. Villani, G. Oriolo, 2009. Robotics: modelling, planning and control, Springer.
- T.I. Fossen, 1994. Guidance and Control of Ocean Vehicles, 1st ed., John Wiley & Sons Ltd (to deepen).
- R. Hartley and A. Zisserman, 2003. Multiple View Geometry in Computer Vision, 2nd ed., Cambridge University Press (to deepen).
Learning Objectives
cc1: In-depth knowledge and understanding of the theoretical-scientific aspects of engineering, with a specific reference to mechanical engineering, in which students are able to identify, formulate and solve, even in an innovative way, complex and/or interdisciplinary problems. The ability to understand a multidisciplinary context in the engineering field and to work with a problem solving approach., cc10: Knowledge and understanding of the automation and control industry. Knowledge and understanding of mechatronic systems.
ca4: Applying knowledge and understanding related to the implementation of engineering projects adapted to their level of knowledge and understanding, working in collaboration with engineers and non-engineers. The projects may concern components, equipment and mechanical systems of various kinds and for the widest possible applications., ca7: Applying knowledge and understanding related to the definition, design and implementation of researches useful for understanding problems, through the use of both theoretical and experimental models and techniques., ca12: Applying adequate knowledge and understanding to understand English texts., ca15: Applying knowledge and understanding to achieve adequate preparation for tertiary level university studies (frequency to post-master's degree courses and doctoral schools) in order to further deepen knowledge and skills in research.
Prerequisites
Industrial Robotics (not mandatory).
Teaching Methods
Classroom lectures and exercises.
Type of Assessment
Oral exam is mandatory.
The student can discuss a research work agreed with the teacher during the course (not mandatory).
The oral exam is usually composed of 3 questions; these questions focus on kinematics, dynamics, control theory and related exercises. The student has to demonstrate a sufficient preparation during the examination.
Course program
Selected topics of analytical dynamics. Lagrange coordinates. D'Alembert's equation.
Holonomic and non-holonomic systems. II-type Lagrange Equations. Computation examples for lagrangian components of active forces.
Configuration space of a mechanical system. Differentiable manifolds. Tangent space, vector fields.
Distributions, involutive closure of a distribution, Lie bracket, Chow theorem.
Kinematic model of the unicycle. Lyapunov-based design of a tracking controller for the unicycle: backstepping control then.
Kinematic control techniques for non-holonomic systems: periodic (synusoidal) inputs. Application to the unicycle: change of input and configuration variables and chained form. Parking of the unicycle.
Backstepping control of a tricycle: equivalent unicycle, virtual control inputs for the unicycle.
Sliding mode control of single-input systems.
Control chattering and practical methods to avoid it: boundary layer, second order sliding mode control.
Robust control of robot manipulators.
Introduction to visual servoing. Cameras. CCD and C-MOS sensors. Pinhole camera and focal distance. Full perspective camera model: lens matrix and spatial sampling matrix. Undistortion techniques. Camera calibration. Structure from motion.
Exercises:
1) Classwork on the dynamic modelling of a lumped mass Furuta pendulum.
2) Classwork on the controllability of non-holonomic systems: unicycle, sphere on plane, differential drive vehicle.
3) Classwork on the backstepping control of a 1DOF system.
4) Classwork on the sliding mode control of a 1DOF system.
5) Classwork on the robust control of a 1DOF system.