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Intelligent Robotics

Code: PRODEI010     Acronym: RI

Keywords
Classification Keyword
OFICIAL Intelligent Systems

Instance: 2018/2019 - 1S Ícone do Moodle

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 2 Syllabus 1 - 6 28 162

Teaching Staff - Responsibilities

Teacher Responsibility
Luís Paulo Gonçalves dos Reis
Armando Jorge Miranda de Sousa

Teaching - Hours

Recitations: 2,00
Type Teacher Classes Hour
Recitations Totals 1 2,00
Armando Jorge Miranda de Sousa 1,00
Luís Paulo Gonçalves dos Reis 1,00

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 to create precise world estates and mobile robots’ control 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 cooperative robotics and robots' teams construction.

 

    • To analyze the main national and international robotic 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.

 

    • Improve healthy scientific approach.

 

Learning outcomes and competences

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

  • Define Robotic Autonomy
  • Define Intelligent Robotic System (IRS)
  • Explain relation of Artificial Intelligence (IA) and IRSs
  • List Applications for Robotic Systems
  • List and use classical Robotic Architectures
  • Know the current State of the Art in Robotics
  • Know frequently used sensors and actuators (in robotics)
  • Evaluate usage of vision systems compared to other sensors
  • Use methodologies from: Data Fusion, IA, data processing and vision processing in order to build perceptions of the world state
  • Know and use methods for Localization, Planning and Navigation in robotics
  • Know and use one or more robotic systems or simulators
  • Know and use cooperation techniques for several types of collaborative robotics

 

Working method

Presencial

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

Experience in computer language programming is needed - any language, frequentely used languages include Java, C++ or Object Pascal, ...

Program


  •  Introduction




    • Artificial Intelligence





    • Basic concepts of Robotics





    • Artificial Intelligence in Robotics





    • History, Evolution, and Current Trends in Intelligent Robotic




  • Architectures for Robotic Agents




    • Reactive, Deliberative, Hybrid




    • Belief, Desire and Intentions (BDI)




    • Cooperative Architectures




  • Perception in robotics




    • Odometry, Rotation and Compass Sensors




    • Sensors commonly used in robotics including artificial vision and depth





    • Sensor Fusion Techniques




  • Localization and Mapping




    • Creation, representation and updating of World States.




    • Markov and Gaussian Localization




    • Grid and Monte-Carlo Localization




    • Mapping: Occupancy Grid and SLAM




    • World Exploration




  • Actuation and control in robotics




    • Locomotion modes, issues with kinematics and dynamics




    • Actuators and associated physical parameters





    • Robot locomotion and its simulation




  • Navigation




    • Algorithms of navigation in known/unknown environments





    • Voronoi Diagrams





    • A* and D* Algorithms





    • Cellular Decomposition




  • Cooperative Robotics




    • Introduction to the cooperation between robots for teamwork





    • Joint Intentions, TAEMS, Role-Based, Social Rules





    • Communication and Mutual Modeling





    • Locker-Room, Strategical Coordination, Partial Hierarchical




  • Applications




    • National and International Robotic Competitions: RoboCup, RoboOlympics, Fira Cup, DARPA Grand-Challenge, Portuguese Robotics Open, Autonomous driving, Micro-Mouse (Micro-Rato) and fire fighting Robots




    • Robotic simulators: Soccerserver 2D and 3D, RoboCup Rescue, Virtual Rescue, Ciber-Mouse





    • Robotic Platforms: MindStorms, ERS210A e ERS-7 (Sony Aibos): Hardware, Software Architectures and Robotic Programming Languages.


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

 

  • Use of simulators for mobile robots navigation (Ciber Mouse - “ciber-rato”)

 

  • Assignments on cooperative robotics (“robosoccer” and “Robocup rescue”)

 

  • Exploration of mobile robotic platforms

 

  • Challenge students to higher level learning

 

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

 

  • Detailed feedback 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

 

  • Attendence

 

  • 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 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 previously presented works.

 

    • To improve homeworks, one must improve and present all homeworks

 

    • Improvements must be turned in until last exam season ("appeal" exam season)

 

Observations

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

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