Alessia SAGGESE | COGNITIVE ROBOTICS
Alessia SAGGESE COGNITIVE ROBOTICS
cod. 0622700056
COGNITIVE ROBOTICS
| 0622700056 | |
| DEPARTMENT OF INFORMATION AND ELECTRICAL ENGINEERING AND APPLIED MATHEMATICS | |
| EQF7 | |
| COMPUTER ENGINEERING | |
| 2023/2024 |
| OBBLIGATORIO | |
| YEAR OF COURSE 2 | |
| YEAR OF DIDACTIC SYSTEM 2022 | |
| AUTUMN SEMESTER |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| ING-INF/05 | 3 | 24 | LESSONS | |
| ING-INF/05 | 3 | 24 | LAB |
| Objectives | |
|---|---|
| THE GOAL OF THIS COURSE IS TO PROVIDE THE ARCHITECTURAL, METHODOLOGICAL AND DESIGN ELEMENTS FOR THE CONSTRUCTION OF INTELLIGENT ROBOTS THAT MUST INTERACT WITH OTHER HUMAN AND ROBOTIC SUBJECTS. KNOWLEDGE AND UNDERSTANDING MACHINE LEARNING-BASED METHODOLOGIES FOR THE CONTROL AND PLANNING OF ROBOT ACTIVITIES. METHODOLOGIES BASED ON COMPUTER VISION AND PATTERN RECOGNITION FOR THE ANALYSIS OF THE ENVIRONMENT (INTERPRETATION OF THE SCENE BASED ON 2D AND 3D ROBOTIC VISION) AND THE RECOGNITION AND CHARACTERIZATION OF THE OTHER SUBJECTS, BOTH HUMAN AND ROBOTIC (RECOGNITION OF ACTIONS AND GESTURES, AUTOMATIC LEARNING OF BEHAVIORS, SPEECH UNDERSTANDING). APPLYing KNOWLEDGE AND UNDERSTANDING DESIGN AND IMPLEMENTATION OF SOLUTIONS TO INTELLIGENT ROBOTICS PROBLEMS BY CHOOSING AND APPLYING THE METHODOLOGIES STUDIED DURING THE LESSONS AND USING THE SOFTWARE ENVIRONMENTS AND OPERATING SYSTEMS SPECIFIC TO ROBOTICS. |
| Prerequisites | |
|---|---|
| IN ORDER TO ACHIEVE THE GOALS OF THE COURSE, THE KNOWLEDGE OF THE C AND PYTHON PROGRAMMING LANGUAGE IS REQUIRED. |
| Contents | |
|---|---|
| DIDACTIC UNIT 1: INTRODUCTION TO COGNITIVE ROBOTICS AND ROS (LECTURE/PRACTICE/LABORATORY HOURS 5/3/0) - 1 (3 HOURS LECTURE): INTRODUCTION: COGNITIVE ROBOTICS - 2 (2 HOURS LECTURE): ROBOTIC OPERATING SYSTEMS - ROS - 3 (3 HOURS PRACTICE): ROBOTIC OPERATING SYSTEMS - ROS [EXERCISE] KNOWLEDGE AND UNDERSTANDING: ACQUIRING THE SKILLS RELATED TO THE CONCEPTS OF COGNITIVE ROBOT AND TO THE FRAMEWORK ROS APPLYING KNOWLEDGE AND UNDERSTANDING: KNOWING HOW TO CREATE A SIMPLE ROS APPLICATION BASED ON THE PUBLISHER - SUBSCRIBER PARADIGM DIDACTIC UNIT 2: SOCIAL ROBOTS AND SENSORS FOR SOCIAL ROBOTS (LECTURE/PRACTICE/LABORATORY HOURS 7/3/0) - 4 (2 HOURS LECTURE): SOCIAL ROBOTS - 5 (3 HOURS LECTURE): SOCIAL ROBOTS. EXAMPLE OF AN ARCHITECTURE OF A SOCIAL ROBOT IN ROS - 6 (2 HOURS LECTURE): SENSORS FOR SOCIAL ROBOTS - 7 (3 HOURS PRACTICE): NAOQI LIBRARIES. INTERACTING WITH PEPPER [EXERCISE] KNOWLEDGE AND UNDERSTANDING: UNDERSTANDING THE CONCEPT OF SOCIAL ROBOT AND KNOWING THE SENSORS A SOCIAL ROBOT CAN BE EQUIPPED WITH; LEARNING ABOUT LIBRARIES TO INTERACT WITH A SOCIAL ROBOT APPLYING KNOWLEDGE AND UNDERSTANDING: KNOWING HOW TO CREATE AN APPLICATION IN ROS TO ALLOW A SIMPLE INTERACTION WITH THE PEPPER ROBOTIC PLATFORM DIDACTIC UNIT 3: NATURAL LANGUAGE PROCESSING ALGORITHMS (LECTURE/PRACTICE/LABORATORY HOURS 7/3/2) - 8 (2 HOURS LECTURE): MACHINE LEARNING FOR NLP: INTRODUCTION - 9 (3 HOURS LECTURE): NLP: INTENT, ENTITY RECOGNITION. - 10 (2 HOURS LECTURE): NLP: DIALOGUE MANAGEMENT. RASA LIBRARY - 11 (3 HOURS PRACTICE): CHATBOT DESIGNING [EXERCISE] - 12 (2 HOURS LABORATORY): CHATBOT DESIGNING [LABORATORY] KNOWLEDGE AND UNDERSTANDING: KNOWING THE NLP ALGORITHMS AND THE RASA FRAMEWORK. APPLYING KNOWLEDGE AND UNDERSTANDING: KNOWING HOW TO CREATE A CHATBOT THAT EXPLOITS NLP ALGORITHMS USING THE RASA FRAMEWORK DIDACTIC UNIT 4: AUDIO ANALYSIS (LECTURE/PRACTICE/LABORATORY HOURS 5/3/0) - 13 (3 HOURS LECTURE): AUDIO ANALYSIS: PROBLEM DEFINITION, LIBRARY FOR DATA ACQUISITION, SPEECH2TEXT - 14 (2 HOURS LECTURE): AUDIO ANALYSIS: SPEAKER RE-IDENTIFICATION - 15 (3 HOURS PRACTICE): AUDIO ANALYSIS: EXAMPLE IN ROS WITH PEPPER [EXERCISE] KNOWLEDGE AND UNDERSTANDING: KNOWING THE AUDIO ANALYSIS ALGORITHMS FOR SPEAKER RECOGNITION APPLICATIONS. APPLYING KNOWLEDGE AND UNDERSTANDING: KNOWING HOW TO CREATE AN AUDIO ANALYSIS ALGORITHM FOR SPEAKER RECOGNITION DIDACTIC UNIT 5: VIDEO ANALYSYS MODULES ON A REAL ROBOTIC PLATFORM (LECTURE/PRACTICE/LABORATORY HOURS 0/5/5) - 16 (2 HOURS PRACTICE): OBJECT DETECTION. INTEGRATION IN PEPPER WITH ROS [EXERCISE] - 17 (3 HOURS PRACTICE): SENTIMENT ANALYSIS FROM FACE. INTEGRATION IN PEPPER WITH ROS [EXERCISE] - 18 (2 HOURS LABORATORY): FINAL PROJECT [LABORATORY] - 19 (3 HOURS LABORATORY): FINAL PROJECT [LABORATORY] KNOWLEDGE AND UNDERSTANDING: UNDERSTANDING HOW TO INTEGRATE KNOWN VIDEO ANALYSIS ALGORITHMS ON THE PEPPER ROBOTIC PLATFORM. APPLIED KNOWLEDGE AND UNDERSTANDING: KNOWING HOW TO INTEGRATE VIDEO ANALYSIS ALGORITHMS ON THE PEPPER ROBOTIC PLATFORM TOTAL LECTURE/PRACTICE/LABORATORY HOURS 24/17/7 |
| Teaching Methods | |
|---|---|
| THE COURSE CONTAINS THEORETICAL LECTURES, IN-CLASS EXERCITATIONS AND PRACTICAL LABORATORY EXERCITATIONS. DURING THE IN-CLASS EXERCITATIONS THE STUDENTS ARE DIVIDED IN TEAMS AND ARE ASSIGNED SOME PROJECT-WORKS TO BE DEVELOPED ALONG THE DURATION OF THE COURSE. THE PROJECTS INCLUDE ALL THE CONTENTS OF THE COURSE AND IS ESSENTIAL BOTH FOR THE ACQUISITION OF THE RELATIVE ABILITIES AND COMPETENCES, AND FOR DEVELOPING AND REINFORCING THE ABILITY TO WORK IN A TEAM. IN THE LABORATORY EXERCITATIONS THE STUDENTS IMPLEMENT THE ASSIGNED PROJECTS USING ROS. IN ORDER TO PARTICIPATE TO THE FINAL ASSESSMENT AND TO GAIN THE CREDITS CORRESPONDING TO THE COURSE, THE STUDENT MUST HAVE ATTENDED AT LEAST 70% OF THE HOURS OF ASSISTED TEACHING ACTIVITIES. |
| Verification of learning | |
|---|---|
| THE EXAM AIMS AT EVALUATING, AS A WHOLE: THE KNOWLEDGE AND UNDERSTANDING OF THE CONCEPTS PRESENTED IN THE COURSE, THE ABILITY TO APPLY THAT KNOWLEDGE TO SOLVE PROGRAMMING PROBLEMS REQUIRING THE USE OF ARTIFICIAL INTELLIGENCE AND ARTIFICIAL VISION TECHNIQUES; INDEPENDENCE OF JUDGMENT, COMMUNICATION SKILLS AND THE ABILITY TO LEARN. THE EXAM INCLUDES TWO STEPS: THE FIRST ONE CONSISTS IN AN ORAL EXAMINATIONS AND IN THE DISCUSSION OF MID TERM PROJECTS REALIZED DURING THE COURSES. THE SECOND STEP CONSISTS IS BASED ON THE REALIZATION OF A FINAL TERM PROJECT: THE STUDENTS, PARTITIONED INTO TEAMS, ARE REQUIRED TO REALIZE A SYSTEM, FINALIZED TO A COMPETITION AMONG THE TEAMS, DESIGNING AND METHODOLOGICAL CONTRIBUTIONS OF THE STUDENTS, TOGETHER WITH THE SCORE ACHIEVED DURING THE COMPETITION, ARE CONSIDERED FOR THE EVALUATION. THE AIM IS TO ASSESS THE ACQUIRED KNOWLEDGE AND ABILITY TO UNDERSTANDING, THE ABILITY TO LEARN, THE ABILITY TO APPLY KNOWLEDGE, THE INDEPENDENCE OF JUDGMENT, THE ABILITY TO WORK IN A TEAM. IN THE FINAL EVALUATION, EXPRESSED IN THIRTIETHS, THE EVALUATION OF THE INTERVIEW AND OF THE MID TERM PROJECTS WORK WILL ACCOUNT FOR 60% WHILE THE FINAL TERM PROJECT WILL ACCOUNT FOR 40%. THE CUM LAUDE MAY BE GIVEN TO STUDENTS WHO DEMONSTRATE THAT THEY CAN APPLY THE KNOWLEDGE AUTONOMOUSLY EVEN IN CONTEXTS OTHER THAN THOSE PROPOSED IN THE COURSE. |
| Texts | |
|---|---|
| - LECTURE NOTES PROVIDED BY THE INSTRUCTOR THE TEACHING MATERIAL IS AVAILABLE ON THE UNIVERSITY E-LEARNING PLATFORM (HTTP://ELEARNING.UNISA.IT) ACCESSIBLE TO STUDENTS USING THEIR OWN UNIVERSITY CREDENTIALS. |
| More Information | |
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| THE COURSE IS HELD IN ENGLISH. |
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