Programma
Il corso è organizzato in 4 moduli da 3 crediti. Ciascun modulo ha il suo programma specifico disponibile all'inizio del ciclo di lezioni.
Una descrizione dettagliata e sempre aggiornata dei programmi è disponibile alla pagina: http://www.diag.uniroma1.it/vendittelli/EIR/
Riportiamo qui una sintesi:
Modulo 1: Modeling and control of multi-rotor UAVs (Marilena Vendittelli)
Introduction to the course and aerial vehicles modeling
Quadrotor modeling
Control based on linear approximation
Backstepping-based control
Control based on dynamic feedback linearization
Geometric control on SE(3)
State estimation
Motion planning
Controllers comparison
Fault-diagnosis and fault tolerant control - part I: introduction
Fault-diagnosis and fault tolerant control - part II: application to quadrotors
Modulo 2: Underactuated Robots (Leonardo Lanari, Giuseppe Oriolo)
Introduction
Motivation. Definition of underactuated system (generalized coordinates vs degrees of freedom). Examples of underactuated robots.
Modeling and Properties
Eulero-Lagrange modeling (classic and alternate). State-space form. Control problems of interest. Controllabiity (STLA, STLC, natural controllability). Comparison with fully actuated robots. Integrability conditions for passive dynamics. Equilibrium points and linear controllability.
Case Studies: Acrobot and Pendubot
Modeling. Approximate linearization at equilibria. Linear controllability. Balancing. Partial feedback linearization. Swing-up (1) via analysis of the zero dynamics (2) via energy pumping.
Zero dynamics in underactuated systems
Normal form and zero dynamics. Importance of the zero dynamics in control. Zero-dynamics in linear and nonlinear underactuated systems. The homoclinic orbit.
Passivity
Definition and physical interpretation. Linear and nonlinear mechanical systems examples. Dissipativity in state space representations. Feedback equivalence to a passive system. Output stabilization of passive systems
Energy-based control of underactuated systems
The convey-crane and reaction-wheel cases.
Optimization methods for Planning and Control
Introduction to Dynamic Programming. Hamilton-Jacobi-Bellman equation. Derivation of the Linear Quadratic Regulator
Linear-Time-Varying LQR. Trajectory optimization with Iterative LQR. Constrained optimization. Model Predictive Control (Linear, LTV and Nonlinear). LQR-trees.
Modulo 3: Locomotion and haptic interfaces for VR exploration (Alessandro De Luca)
General introduction to haptic and locomotion interfaces with several illustrative examples.
Two specific hardware devices: the Geomatic Touch haptic interface; the Cyberith Virtualizer locomotion interface (with the Oculus Rift HMD). Possible applications of these interfaces.
Design, construction, actuation, sensing, modelling, and system issues for two locomotion platforms for VR exploration, developed within the CyberWalk project: the CyberCarpet (ball-array) and the CyberWalk platform (2D, omni-directional).
Control design and experimental validation for the CyberCarpet. Control design and experimental validation for a 1D treadmill.
Control design, experimental validation, and perceptual evaluation for the 2D CyberWalk platform.
Modulo 4: Control of Multi-Robot Systems (Andrea Cristofaro)
Examples of applications of multi-robot systems.
Centralized vs. decentralized architectures.
Elements of graph theory.
Connectivity and Consensus; Passivity and Lyapunov stability; Interconnection of mechanical systems.
Application to multi-UAV systems: Formation control with time-varying topology; Formation control with connectivity maintenance; Steady-state behaviors;
Overview of other multi robot problems.
Prerequisiti
Una preparazione generale in robotica (cinematica, dinamica, pianificazione, controllo) è auspicabile ma non obbligatoria.
Testi di riferimento
Materiale didattico fornito dai docenti.
Modalità insegnamento
Lezioni frontali che illustrano le metodologie utilizzate negli ambiti considerati nei diversi moduli del corso. Analisi di casi di studio, esempi di applicazione a sistemi reali. Esercitazioni in laboratorio, se consentito dalle misure imposte dall'emergenza sanitaria in corso.
Frequenza
In generale, non obbligatoria ma i docenti di ciascun modulo potrebbero richiedere l'obbligo di frequenza.
Modalità di esame
Presentazioni o progetti per ogni modulo.
Modalità di erogazione
Lezioni frontali che illustrano le metodologie utilizzate negli ambiti considerati nei diversi moduli del corso. Analisi di casi di studio, esempi di applicazione a sistemi reali. Esercitazioni in laboratorio, se consentito dalle misure imposte dall'emergenza sanitaria in corso.
