Instance: 2018/2019 - 1S
Cycles of Study/Courses
||No. of Students
||Syllabus since 2009/2010
Teaching Staff - Responsibilities
Last updated on 2018-09-20.
Fields changed: Objectives, Resultados de aprendizagem e competências, Componentes de Avaliação e Ocupação, Programa, Trabalho de estágio/projeto, Métodos de ensino e atividades de aprendizagem
- 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 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 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 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.
Pre-requirements (prior knowledge) and co-requirements (common knowledge)
Experience in computer language programming is needed - any language, frequently used languages include Java, C++, Python or Object Pascal, ...
- 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.
- 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.
- 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.
- 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.
- 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).
- 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.
- Human-Robot Interaction (HRI):
Basics of Human-Computer Interaction; Perception for HRI; Decision-Making for HRI; Action for HRI; Human-Robot Intelligent Cooperation.
- 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.
- 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.
- 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?
Howie Choset, Kevin M. Lynch, Seth Hutchinson, George Kantor, Wolfram Burgard, Lydia E. Kavraki, Sebastian Thrun ; Principles of Robot Motion : Theory, Algorithms, and Implementations
, Bradford Book, MIT Press, Cambridge, Massachussets, London England, 2005. ISBN: 0-262-03327-5
Robin R. Murphy; An Introduction to AI Robotics
, Bradford Book, MIT Press, Cambridge, Massachussets, London England, 2000. ISBN: 0-262-13383-0
Russell, Stuart; Artificial intelligence
. ISBN: 0-13-360124-2
Sebastian Thrun, Wolfram Burgard, Dieter Fox ; Probabilistic Robotics
, MIT Press, Cambridge, Massachussets, London England, 2005. ISBN: 0-262-20162-3
Siciliano, Bruno; Khatib, Oussama (Eds.); Springer Handbook of Robotics
, Springer, 2008. ISBN: 978-3-540-38219-5
Jason M. O'Kane; A Gentle Introduction do ROS
, Independently published, 2013. ISBN: 978-14-92143-23-9 (Free - https://www.cse.sc.edu/~jokane/agitr/)
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
Simuladores Soccer-Server (2D e 3D)
Linguagem de Programação: C++
Simulador RoboCup Rescue
Technological sciences > Engineering > Control engineering > Robótica Robotics
Technological sciences > Engineering > Simulation engineering
Technological sciences > Engineering > Computer engineering
Technological sciences > Engineering > Knowledge engineering
Technological sciences > Technology > Knowledge technology > Agent technology
Distributed evaluation without final exam
Amount of time allocated to each course unit
|Elaboração de projeto
|Frequência das aulas
|Trabalho de investigação
Eligibility for exams
- Assignments 1 and 2 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
- 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)
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)
- Individual improvement of the previously work that must have been previously presented in the final course presentation.
- To improve homeworks, one must improve and present all homeworks
Attention: Classes and course materials will be given to students in English.