COGNITIVE ROBOTICS

Ingegneria Informatica COGNITIVE ROBOTICS

0622700056
DIPARTIMENTO DI INGEGNERIA DELL'INFORMAZIONE ED ELETTRICA E MATEMATICA APPLICATA
EQF7
COMPUTER ENGINEERING
2018/2019



YEAR OF COURSE 2
YEAR OF DIDACTIC SYSTEM 2017
SECONDO SEMESTRE
CFUHOURSACTIVITY
324LESSONS
324LAB
Objectives
The goal of the course is to provide the student with the architectural, methodological and practical elements for the design and implementation of intelligent robots. In particular, the course focuses on sensorial (2D/3D vision, speech understanding) and cognitive aspects (recognition of actions and gestures, machine learning of complex behaviors, interpretation of the environment structure, interaction with humans and other robots).

Knowledge and understanding
The course presents the methodologies based on machine learning for the control and activity planning of a robot. Furthermore, it presents the methods based on artificial vision and pattern recognition for the analysis of the environment and the recognition of the other subjects in the scene (humans and other robots).

Applied knowledge and understanding
Ability to design and implement solutions to intelligent robot problems, by choosing and applying the appropriate methods presented in the course, and the software environments specifically devised for cognitive robotics.
Prerequisites
IN ORDER TO ACHIEVE THE GOALS OF THE COURSE, THE KNOWLEDGE OF THE C PROGRAMMING LANGUAGE IS REQUIRED.
Contents
COGNITIVE ROBOTICS: INTRODUCTION (2/0/0)

MOTION PLANNING: DISCRETE ALGORITHMS AND CELL DECOMPOSITION; ROBOTS MODELLING AND OBSTACLE AVOIDANCE; C-SPACE (4/2/0)

SENSORS FOR MOBILE ROBOTS: TACTILE SENSORS; WHEEL/MOTOR SENSORS; HEADING SENSORS; GROUND BASED BEACONS SENSORS; ACTIVE RANGING SENSORS; MOTION/SPEED SENSORS; VISION BASED SENSORS (2/2/0)

HUMAN-ROBOTS INTERACTION: ROBOTIC VISION; STEREO VISION; OBJECTS RECOGNITION THROUGH ARTIFICIAL VISION ALGORITHMS; GESTURES/ACTIONS RECOGNITION THROUGH VISION ANALYSIS; AFFECTIVE COMPUTING; NATURAL LANGUAGE PROCESSING AND UNDERSTANDING; SPEECH RECOGNITION AND SPEECH TO TEXT ALGORITHMS; MULTI-MODAL SYSTEMS FOR HUMAN-ROBOTS INTERACTION (12/10/0)

OPERATING SYSTEMS FOR THE ROBOTIC ROS (ROBOT OPERATING SYSTEM): INTRODUCTION TO THE FRAMEWORK ROS; BASIC CONCEPTS: FILESYSTEM LEVEL, COMPUTATION GRAPH LEVEL, COMMUNITY LEVEL; GAZEBO: 3D ROBOTIC SIMULATOR; TF TRANSFORMATION SYSTEM, ROBOT MODELS BASED ON UNIFIED ROBOT DESCRIPTION FORMAT (URDF); RVIZ: 3D VISUALIZATION TOOL FOR ROS. (4/10/0)
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 THE OPENCV SOFTWARE LIBRARIES.

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 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 40% WHILE THE FINAL TERM PROJECT WILL ACCOUNT FOR 60%. 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
- SLIDES PROVIDED BY THE PROFESSORS
- INTRODUCTION TO AUTONOMOUS MOBILE ROBOTS. ROLAND SIEGWART, ILLAH R. NOURBAKHSH, A BRADFORD BOOK, THE MIT PRESS, 2004
More Information
THE COURSE IS HELD IN ENGLISH.
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