Il corso è organizzato in due moduli da 3 crediti, scelti tra i 4 moduli del corso di Elective in Robotics. 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 dei 4 moduli di Elective in Robotics tra i quali scegliere: 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) 1. Introduction Motivation. Definition of underactuated system (generalized coordinates vs degrees of freedom). Examples of underactuated robots. 2. 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. 3. 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. 4. 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. 5. 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 6. Energy-based control of underactuated systems The convey-crane and reaction-wheel cases. 7. 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.

Materiale didattico fornito dai docenti.