Intelligent Robotics

Code:

PRODEI010

Acronym:

RI

Keywords
Classification	Keyword
OFICIAL	Intelligent Systems

Instance: 2023/2024 - 1S

Active?	Yes
Web Page:	https://moodle.up.pt/course/view.php?id=3194
Responsible unit:	Department of Electrical and Computer Engineering
Course/CS Responsible:	Doctoral Program in Informatics Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
PRODEI	5	Syllabus	1	-	6	28	162

Teaching language

English

Objectives

• To understand the basic concepts of Robotics and the context of Artificial Intelligence in Robotics.


• To study methods of perception and sensorial interpretation (emphasizing computer vision), which allow creating precise world estates and mobile robots’ localization methods.


• To study the methods which allow mobile robots to navigate in familiar or unfamiliar environments using Planning and Navigation algorithms.


• To study the fundamentals of human-robot interaction, robot learning, cooperative robotics and robot teams construction.


• To analyze the main national and international robotics competitions, the more realistic robot simulators and the more advanced robotic platforms available in the market.


• Improve the ability to communicate regarding scientific and technical issues.


• Promote a healthy scientific approach.

Learning outcomes and competences

At the end of this Curricular Unit, students should be able to:

• Define Autonomy for Robotics
• Define Intelligent Robotic System (IRS)
• Explain the relation of Artificial Intelligence (AI) and IRSs
• Identify applications for Intelligent Robotic Systems
• List and use classical Robotic Architectures
• Know the current state of the art in Robotics
• Know frequently used sensors and actuators and perception interpretation methods for robotics
• Evaluate the usage of vision systems compared to other sensors
• Use methodologies from Data Fusion, AI, data processing and vision processing in order to build perceptions of the world state
• Know and use methods for Localization, Mapping, Planning, and Navigation in robotics
• Know and use one or more robotic systems or simulators
• Know and use interaction, learning and cooperation methodologies for robotics.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Experience in computer language programming is needed - any language. Frequently used languages include C++ and Python.

Program

1. Introduction to Intelligent Robotics:
   Basic Concepts of Robotics, Artificial Intelligence in Robotics; Areas and Applications of Intelligent Robots; Perception-Decision-Action Loop; Architectures for Robotic Agents; Robotic Competitions; Simulation and Robotic Simulators; History, Evolution, and Current Trends in Intelligent Robotics.


2. Robotics Middleware and ROS: 
   Middleware and Robotics Middleware; Robotics Middleware Projects; Introduction to ROS – Robot Operating System; ROS Architecture; ROS Console Commands; Creating ROS Packages; ROS C++ Client Library; ROS Simulation; Visualizations and User Interface Tools; ROS Bags.


3. Perception and Sensorial Interpretation: 
   Types of Sensors for Mobile Robots; Proximity/Contact Sensors; Position/Movement Sensors; Robot Vision (Cameras, Depth Sensors, Digital Image, Color Spaces, Image Processing, Image Analysis; Robot Hearing; Uncertainty Analysis and Representation; Sensor Fusion Techniques.


4. Locomotion and Action: 
   Actuators for Mobile Robots; Locomotion Modes and Mechanisms; Wheeled Mobile Robots; Legged Mobile Robots and Biped Walking; Robot Manipulators and its Control; Mobile Robots Kinematics and Motion Control; Simulation of Robot Locomotion and Action.


5. Localization and Mapping: 
   Creation, Representation and Update of Maps and World States; Metric Maps and Topological Maps; Markov, Gaussian and Grid Localization; Kalman Filters and Extended Kalman Filters (EKF) Localization; Particle Filters and Monte-Carlo Localization; SLAM – Simultaneous Localization and Mapping; Methods for SLAM (EKF-SLAM, FastSLAM and Graph SLAM).


6. Planning and Navigation: 
   Path Planning in Known/Unknown Environments; Cellular Decomposition; Visibility Graphs; Voronoi Diagrams; Search, Dijkstra, A* and D* Algorithms; Potential Field Method; Obstacle Avoidance; Navigation Architectures; World Exploration Methods; High-Level Planning.


7. Human-Robot Interaction (HRI): 
   Basics of Human-Computer Interaction; Perception for HRI; Decision-Making for HRI; Action for HRI; Human-Robot Intelligent Cooperation.


8. Robot Learning: 
   Introduction and Challenges in Robot Learning; Dimensionality Reduction; Supervised Robot Learning; Evolutionary Robot Learning; Reinforcement Learning for Robotics; Optimization and Metaheuristics for Robotics; Self-Supervised, Imitation Learning, Deep Learning for Robotics; Multi-Robot Learning.


9. Cooperative Robotics and Human-Robot Teams: 
   Cooperation between Robots for Teamwork; Joint Intentions, TAEMS, Role-Based, Social Rules; Multi-Robot Formations; Multi-Robot Communication and Mutual Modeling; Locker-Room, Strategical Coordination, Setplays; Swarm Robotics; Human-Robot Teams.


10. Robotics in the Future: 
    Artificial Intelligence and Robotics in the Future; Visions, Science Fiction and Reality; Advanced Projects in Robotics in Portugal, EU, Japan and USA; Asimov Laws and their Future; Robot Ethics, Robot Rights and Robotic Governance; Industrial, Personal, Ubiquos and Cloud Robots; Robotics Future Trends and Applications; The Singularity?

Mandatory literature

Murphy, Robin R.; Introduction to AI robotics. ISBN: 0-262-13383-0
Thrun, Sebastian; Probabilistic robotics. ISBN: 0-262-20162-3
Choset, Howie 070; Principles of robot motion. ISBN: 0-262-03327-5
Russell, Stuart; Artificial intelligence. ISBN: 0-13-360124-2

Complementary Bibliography

Arkin, Ronald C.; Behavior-based robotics. ISBN: 0-262-01165-4
RoboCup Series (1999-2008)
Manuais dos Simuladores: Soccerserver, RoboCupRescue e Ciber-Rato
Siciliano, Bruno; Khatib, Oussama (Eds.); Springer Handbook of Robotics, Springer, 2008. ISBN: 978-3-540-38219-5

Teaching methods and learning activities

• Exposition with interaction in classes


• Examples are taken from projects coordinated/developed by the lecturers. 


• Use of simulators for mobile robots navigation and humanoid robots


• Assignments on cooperative robotics


• Exploration of mobile robotic platforms


• Challenge students to higher-level learning


• The evaluation includes the ability to search for information, do scientific work, do technical work and disseminate the work done. Higher-order thinking skills are encouraged


• Detailed feedback is given to students about the quality of their research work and learning process

Software

Simuladores Soccer-Server (2D e 3D)
OPEN-R SDK (ERS210A e ERS7)
Simulador RoboCup Rescue
Simulador Ciber-Rato
Linguagem de Programação: C++

keywords

Technological sciences > Engineering > Simulation engineering
Technological sciences > Technology > Knowledge technology > Agent technology
Technological sciences > Engineering > Knowledge engineering
Technological sciences > Engineering > Control engineering > Robótica Robotics
Technological sciences > Engineering > Computer engineering

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Trabalho escrito	30,00
Trabalho laboratorial	70,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Elaboração de projeto	40,00
Estudo autónomo	30,00
Frequência das aulas	42,00
Trabalho de investigação	20,00
Trabalho laboratorial	30,00
Total:	162,00

Eligibility for exams

• Attendance


• Assignments with more than 6 out of 20 in each of them

 

Calculation formula of final grade

• 10% HomeWorks


• 20% Assignment 1 (includes oral presentation)


• 20% Assignment 2 (includes scientific conference short paper)


• 10% Assignment 3 (Half Way Project)


• 40% Assignment 3 (Final Project), detailed as:




• 10% Code & Functionalities & Demonstration


• 10% "Conference" article


• 05% references


• 10% Presentation + Q&A


• 05% video

Examinations or Special Assignments

•  HomeWorks




• Small weekly assignments




• Assignment 1




• Research & Survey about New Trends in Robotics
  OR    Initial small project in intelligent robotics




• Assignment 2




• Simple a reactive robot


• Frequently team of 2 students; individual works allowed; max team size of 4 students (Goals to be defined at the beginning of the work on a case to case basis - depending on team size, etc)




• Course Project




• Assignments 3 and 4 relate to "Course Project", the project in the field of the course


• Assignment 3 - Half way evaluation of the status of the Course Project (design and implementation)


• Assignment 4 - Demonstration of Course Project + Dissemination elements (Oral Presentation + Publishable Scientific Article + Video)

Internship work/project

Class Project: Ciber Mouse simulation agent (such as collaborative or mapping), autonomous driving, robotic soccer, humanoid robots or other scientific research project agreed by students and teacher

Special assessment (TE, DA, ...)

• Attendance not required


• 20% Assignment 1


• 20% Assignment 2


• 60% Assignment 4 - Project + Dissemination (Oral Presentation + Article + Video

 

Classification improvement

• Individual improvement of the previous work that must have been previously presented in the final course presentation.


• To improve homework, one must improve and present all homework.

 

Observations

Attention: Classes and course materials will be given to students in English.