Mechanical Engineering

Key Features of robots and basic notions: general definitions of robot, the main configurations, structures and characteristics, notions of applied mechanics. Fundamentals of mechanics of rigid body: representation of position and orientation, rotation matrices and homogeneous transformations, kinematics of rigid bodies, rigid body dynamics. Kinematics of manipulators: the kinematic model of a manipulator, direct kinematic problem, inverse kinematic problem. Dynamics of manipulators: formulation of the mathematical model, direct dynamic problem, inverse dynamic problem. Trajectory planning in robotics: general considerations, point-to-point and multiple-point and continuous trajectories, trajectory optimisation. Introduction to mechanical components and sensors of robotic systems: principles of operation and characteristics of electric actuators, examples and principles of operation of mechanical components, elements and sensors. Preliminary notions on control in robotics: transfer functions of the components involved in the control, basic examples of controls of robots, such as non-ideal control of robots with multiple degrees of freedom.

The course needs a preliminary knowledge of kinematics and dynamics of mechanical systems, as given in undergraduate Mechanics courses, and some background in control systems is also useful.

Robotica industriale G. Legnani Casa Editrice Ambrosiana Robot Dynamics and Control M.W. Spong, M. Vidyasagar John Wiley & Sons Robotica Industriale L. Sciavicco, B. Siciliano McGrawHill Italia

Attendance at all course lectures is required.

The project will be evaluated considering various aspects: 1. Quality of presentation and clarity during the examination through a PowerPoint presentation. 2. Order and clarity of Matlab/Simulink code. 3. Originality of the project. 4. Complexity of the implemented dynamic system and accuracy in modeling. 5. Control part: cases where different algorithms are compared will be rewarded. 6. Physical coherence of the system: the modeling of actuators and the virtualization of sensors used will be analyzed. 7. State estimation and techniques for data fusion and filtering will be evaluated.

Frontal teaching with in-class exercises.

Key Features of robots and basic notions: general definitions of robot, the main configurations, structures and characteristics, notions of applied mechanics. Fundamentals of mechanics of rigid body: representation of position and orientation, rotation matrices and homogeneous transformations, kinematics of rigid bodies, rigid body dynamics. Kinematics of manipulators: the kinematic model of a manipulator, direct kinematic problem, inverse kinematic problem. Dynamics of manipulators: formulation of the mathematical model, direct dynamic problem, inverse dynamic problem. Trajectory planning in robotics: general considerations, point-to-point and multiple-point and continuous trajectories, trajectory optimisation. Introduction to mechanical components and sensors of robotic systems: principles of operation and characteristics of electric actuators, examples and principles of operation of mechanical components, elements and sensors. Preliminary notions on control in robotics: transfer functions of the components involved in the control, basic examples of controls of robots, such as non-ideal control of robots with multiple degrees of freedom.

The course needs a preliminary knowledge of kinematics and dynamics of mechanical systems, as given in undergraduate Mechanics courses, and some background in control systems is also useful.

Robotica industriale G. Legnani Casa Editrice Ambrosiana Robot Dynamics and Control M.W. Spong, M. Vidyasagar John Wiley & Sons Robotica Industriale L. Sciavicco, B. Siciliano McGrawHill Italia

Attendance at all course lectures is required.

The project will be evaluated considering various aspects: 1. Quality of presentation and clarity during the examination through a PowerPoint presentation. 2. Order and clarity of Matlab/Simulink code. 3. Originality of the project. 4. Complexity of the implemented dynamic system and accuracy in modeling. 5. Control part: cases where different algorithms are compared will be rewarded. 6. Physical coherence of the system: the modeling of actuators and the virtualization of sensors used will be analyzed. 7. State estimation and techniques for data fusion and filtering will be evaluated.

Frontal teaching with in-class exercises.