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  3. FERRENTINO ENRICO
  4. Teaching

ROBOTICS

ENRICO FERRENTINO ROBOTICS

0622700082
DIPARTIMENTO DI INGEGNERIA DELL'INFORMAZIONE ED ELETTRICA E MATEMATICA APPLICATA
EQF7
COMPUTER ENGINEERING
2022/2023



OBBLIGATORIO
YEAR OF COURSE 2
YEAR OF DIDACTIC SYSTEM 2017
AUTUMN SEMESTER
CFUHOURSACTIVITY
324LESSONS
324EXERCISES
PASQUALE CHIACCHIO T Curriculum
ENRICO FERRENTINO Curriculum
Objectives
THIS COURSE WILL GIVE A BASIC UNDERSTANDING OF CONTROL METHODS FOR ROBOTIC ARMS (MANIPULATORS) AND IT WILL ALSO COVER MOBILE ROBOTS. THE FOCUS OF THE COURSE WILL BE BOTH ON METHODOLOGICAL AND APPLICATION-ORIENTED ASPECTS. THIS WILL BE DONE BY FIRST INTRODUCING THE THEORETICAL ASPECTS AND THEN BY EXPLORING THESE NOTIONS BOTH VIA SIMULATIONS AND COMPUTER-AIDED DESIGN TOOLS.

KNOWLEDGE AND UNDERSTANDING
ROBOT KINEMATIC MODELING, JOINT-LEVEL CONTROL TECHNIQUES FOR ROBOTS, TASK PLANNING; MOBILE ROBOTS.

APPLYING KNOWLEDGE AND UNDERSTANDING
WRITE THE KINEMATIC EQUATIONS FOR A GIVEN ROBOTIC STRUCTURE. DESIGN A JOINT-LEVEL CONTROLLER FOR ROBOT. USING SIMULATION ENVIRONMENTS AND COMPUTER-AIDED DESIGN TOOLS FOR ROBOTIC APPLICATIONS.
Prerequisites
THERE ARE NO MANDATORY PREREQUISITES. HOWEVER, FOR THE SUCCESSFUL ACHIEVEMENT OF THE COURSE GOALS KNOWLEDGE ABOUT AUTOMATIC CONTROL OF DYNAMIC SYSTEMS IS REQUIRED (BOTH IN CONTINUOUS AND DISCRETE-TIME). THIS KNOWLEDGE CAN BE ACQUIRED IN THE COURSES: AUTOMAZIONE.

FURTHERMORE, BASIC KNOWLEDGE OF COMPUTER SCIENCE IS REQUIRED.
Contents
Didactic Unit 1 – KINEMATICS
(LECTURE/PRACTICE/LABORATORY HOURS 8/4/12)
- 1 (2 HOURS Lecture): Introduction to the course. Robotic manipulators structure. Rigid body pose. Rotation matrix. Elementary rotations.
- 2 (2 HOURS Lecture): Representation and rotation of a vector. Sequencing of rotation matrices with respect to fixed and moving frames.
- 3 (2 HOURS Lecture): Homogeneous transformations. Forward kinematics. Denavit-Hartenberg notation.
- 4 (4 HOURS Practice): Applications of D-H notation to derive forward kinematic equations of real robots (e.g., COMAU Racer, FANUC Scara).
- 5 (2 HOURS Lecture): Euler angles (ZYZ, RPY). Axis-angle. Joint space and task space. Workspace. Kinematic redundancy. Inverse kinematics problem.
- 6 (3 HOURS Laboratory): Assignment and discussion of the final project. Introduction to robot programming through the Robot Operating System (ROS).
- 7 (3 HOURS Laboratory): Software tools to support the project: ROS nodes and topics; building tools; launch files; coding ROS nodes and publisher/subscriber patterns.
- 8 (3 HOURS Laboratory): Software tools to support the project: URDF robot modeling; ROS transformation matrices (TF); Quaternions; RQT GUIs.
- 9 (3 HOURS Laboratory): Software tools to support the project: robot configuration packages for kinematic calculations and 3D visualization in a digital environment; ROS Services; ROS Actions; ROS Time; bagfiles; forward kinematics in MATLAB.
KNOWLEDGE AND UNDERSTANDING: Description of position and orientation of rigid bodies in 3D space. Conversion between joint space and task space: forward and inverse kinematics. Robot Operating System (ROS).
APPLYING KNOWLEDGE AND UNDERSTANDING: Derivation of robots forward kinematics through the usage of a standard procedure. Analysis of a ROS network. Coding of ROS nodes and relating communication patterns. Kinematic calculations in ROS and MATLAB. Creation of virtual robot models.

Didactic Unit 2 – DIFFERENTIAL KINEMATICS
(LECTURE/PRACTICE/LABORATORY HOURS 3/1/2)
- 1 (3 HOURS Lecture): Geometric Jacobian. Kinematic singularities. Redundancy analysis. Higher-order inverse kinematics. Analytic Jacobian. Inverse kinematics algorithms. Statics.
- 2 (1 HOUR Practice): Derivation of geometric and analytic Jacobians of given robots.
- 3 (2 HOURS Laboratory): Software tools to support the project: ROS nodes debug; ROS kinematic solvers.
KNOWLEDGE AND UNDERSTANDING: Link between joint and Cartesian velocities. Link between joint torques and Cartesian forces. Practical issues with ROS kinematic solvers.
APPLYING KNOWLEDGE AND UNDERSTANDING: Computation of geometric and analytic Jacobians. Selection and usage of ROS kinematic solvers depending on application requirements.

Didactic Unit 3 – LINEAR CONTROL OF ROBOTS
(LECTURE/PRACTICE/LABORATORY HOURS 2/2/6)
- 1 (2 HOURS Lecture): Joint space control. Decentralized control. Decentralized feedforward compensation.
- 2 (2 HOURS Practice): Design of independent joint controllers (position feedback, position and velocity feedback).
- 3 (2 HOURS Laboratory): Software tools to support the project: design and implementation of a dynamic simulator through Simulink/Simscape Multibody and visualization in a 3D virtual environment; implementation of a simulated robot; numerical integration of dynamics.
- 4 (2 HOURS Laboratory): Software tools to support the project: design of independent joint controllers with MATLAB and experimental validation with Simulink.
- 5 (2 HOURS Laboratory): Software tools to support the project: introduction to ros-control; control of simulated and real robots through ros-control and dynamic simulator Gazebo.
KNOWLEDGE AND UNDERSTANDING: Joint space decentralized control. Working principles of a dynamic simulator. Simscape Multibody. ROS Control.
APPLYING KNOWLEDGE AND UNDERSTANDING: Technical applications of linear control for the design of joint space controllers. Control of real and simulated robots.

Didactic Unit 4 – TRAJECTORY GENERATION
(LECTURE/PRACTICE/LABORATORY HOURS 3/1/4)
- 1 (3 HOURS Lecture): Path and trajectory. Joint space trajectories. Point-to-point motion. Trapezoidal velocity profile. Motion through a sequence of points. Task space trajectories. Path primitives (segment and circle).
- 2 (1 HOUR Practice): Practical applications of the presented concepts.
- 3 (3 HOURS Laboratory): Software tools to support the project: trajectory planning with MoveIt! (point-to-point planning in joint and task space, Cartesian planning, continuous inverse kinematics along trajectories).
- 4 (1 HOUR Laboratory): Software tools to support the project: generation of task space paths and trajectories with MATLAB; interfacing MATLAB and ROS.
KNOWLEDGE AND UNDERSTANDING: Elementary algorithms for path generation and time parametrization. Path planning and time parametrization with MoveIt!.
APPLYING KNOWLEDGE AND UNDERSTANDING: Applications of elementary algorithms to realistic use cases. Trajectory planning with MATLAB and ROS. Integration between MATLAB and ROS.

TOTAL LECTURE/PRACTICE/LABORATORY HOURS 16/8/24
Teaching Methods
LECTURES SUPPORTED BY PROBLEM-SOLVING TUTORIALS WITH PRACTICAL ASPECTS ALSO COVERED DURING LECTURES.. LABORATORY HOURS WILL BE AIMED AT DEVELOPING A TEAM PROJECT BY USING SOFTWARE TOOLS AND EXPERIENCE WITH REAL ROBOTS.

IN ORDER TO PARTICIPATE TO THE FINAL ASSESSMENT AND TO GAIN THE CREDITS CORRESPONDING TO THE MODULE, THE STUDENT MUST HAVE ATTENDED AT LEAST 70% OF THE HOURS OF ASSISTED TEACHING ACTIVITIES..

LECTURES: 16 HOURS
PRACTICES: 8 HOURS
LABORATORY: 24 HOURS
Verification of learning
THE EXAM IS DESIGNED TO EVALUATE AS A WHOLE: THE KNOWLEDGE AND UNDERSTANDING OF THE CONCEPTS PRESENTED IN THE COURSE, THE ABILITY TO APPLY THAT KNOWLEDGE TO SOLVE PROBLEMS OF MODELING AND CONTROL OF ROBOTS, INDEPENDENCE OF JUDGMENT, COMMUNICATION AND TEAMWORK SKILLS, AND THE ABILITY TO LEARN.

THE EXAM CONSISTS OF A TWO-PARTS TEST: A PROJECT TO ASSESS THE ABILITY TO APPLY THE PRESENTED CONCEPTS, AS WELL AS THE PRACTICAL SKILLS, AND AN INTERVIEW TO ASSESS KNOWLEDGE AND UNDERSTANDING OF METHODOLOGICAL ASPECTS AND PRESENTATION SKILLS.

THE FINAL EVALUATION WILL BE EXPRESSED IN THIRTIETHS (THE PROJECT WEIGHTS FOR 50%, INTERVIEW FOR 50%);

THE MINIMUM LEVEL OF EVALUATION (18/30) IS ATTRIBUTED WHEN THE STUDENT, WHILE SHOWING APPLICATION IN THE LEARNING, DEMONSTRATES UNCERTAINTIES IN THE APPLICATION OF THE LEARNED METHODS, HAS LIMITED KNOWLEDGE OF THEM AND SHOWS LOW EXPOSITORY CAPACITY.

THE MAXIMUM LEVEL (30/30) IS ATTRIBUTED WHEN THE STUDENT DEMONSTRATES A THOROUGH KNOWLEDGE OF THE METHODS AND IS ABLE TO SOLVE THE PROPOSED PROBLEMS BY IDENTIFYING THE MOST APPROPRIATE METHODS.

THE LAUDE IS ATTRIBUTED WHEN THE CANDIDATE SHOWS A SIGNIFICANT MASTERY OF THE THEORETICAL AND OPERATIONAL CONTENTS AND SHOWS THE ABILITY TO PRESENT THE TOPICS WITH REMARKABLE PROPERTIES OF LANGUAGE AND AUTONOMOUS PROCESSING SKILLS EVEN IN CONTEXTS DIFFERENT FROM THOSE PROPOSED BY THE TEACHER.
Texts
B. SICILIANO, L. SCIAVICCO, L. VILLANI, G. ORIOLO, “ROBOTICS: MODELLING, PLANNING AND CONTROL”, SPRINGER, LONDON, 2009, ISBN 978-1846286414, ENGLISH LANGUAGE.

ALSO IN ITALIAN LANGUAGE AS: : B. SICILIANO, L. SCIAVICCO, L. VILLANI, G. ORIOLO, “ROBOTICA. MODELLISTICA, PIANIFICAZIONE E CONTROLLO”, TERZA EDIZIONE, MCGRAW-HILL, MILANO, 2008, ISBN: 978-8838663222

SUPPLEMENTARY TEACHING MATERIAL WILL BE AVAILABLE ON THE UNIVERSITY E-LEARNING PLATFORM (HTTP://ELEARNING.UNISA.IT) ACCESSIBLE TO ENROLLED STUDENTS.

More Information
THE COURSE IS HELD IN ITALIAN
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