Robotics

Objectives

  1. Knowing
    1. Fundamental Concepts of Autonomous Systems
    2. Fundamental concepts of tele-operated systems
    3. What are architectures and the different types that characterize autonomous systems
    4. The reactive functionality of autonomous systems: sensors and perception 
    5. The deliberative functionality of autonomous systems: navigation, location and mapping.
    6. Fundamental planning concepts
    7. Fundamental Learning Concepts
    8. Fundamental concepts of Human Robot Interaction
    9. Fundamental concepts of multi-robot systems
  2. Doing
    1. Addressnew problems and strategies for implementing heterogeneous autonomous robotic systems
    2. Increase the ability to implement heterogeneous robotic systems
    3. Develop creativity and innovation.
  3. Non-technical skills
    1. Develop the ability to synthesis and critical analysis
    2. Work as a team and increase written and oral communication
    3. Time management capacity and meeting deadlines

General characterization

Code

7309

Credits

6.0

Responsible teacher

José António Barata de Oliveira, Luís Manuel Camarinha de Matos

Hours

Weekly - 4

Total - Available soon

Teaching language

Português

Prerequisites

Fundamental to know Computer Programming

It is recommendable to have basic knowledge in robotics

Bibliography

  1. TRSA - Supporting Notes.
  2. Bonabeau, E., Dorigo, M. and Theraulaz, G. (1999) Swarm Intelligence: From Natural to Artificial Intelligence. New York ; Oxford: Oxford Univ. Press.
  3. Ghallab, M., Nau, D. and Traverso, P. (2004) Automated Planning, Automated Planning: Theory and Practice. Elsevier. doi: 10.1016/B978-1-55860-856-6.X5000-5
  4. Kernbach, S. (2013) Handbook of Collective Robotics. Jenny Stanford Publishing. doi: 10.1201/b14908.
  5. Murphy, R. R. (2019) Introduction to AI ROBOTICS - Second Edition. Cambridge, Massachusetts; London, UK: MIT Press

Teaching method

Theoretical component: Exhibition classes followed by exemplifying and discussion.
Laboratory component: For each work: Presentation of the utterance, tutorial on the technology / tools to be used, discussion of the work method, accomplishment of the work by the students accompanied by a teacher and preparation of report.

Evaluation method

Evaluation has a theoretical and practical component.

The weight of the Theory is 30% and that of practice 70%.

The practical component is carried out through 3 practical papers and discussion.
A minimum score of 9.5 Values is required in the practical component.

The theoretical component has no minimum grade.

WARNING: The practical component is mandatory.

Subject matter

A.     Introduction [1]

  1. What is the subject of the chair
  2. Historical Development
  3. Robot Components - Link, Joint, Manipulator, Wrist, End-effector, Actuators, Sensors, Controller
  4. Robot Classifications – Geometry, Workspace, Actuation, Control, Application
  5. Robot Parameters – Repeatability, Precision, …

B.     Representing Position and Orientation [1]

  1. Referentials
  2. Homogeneous Transformation Matrices
  3. Orientation

C.     Robot Arm Kinematics [2]

  1. Forward Kinematics
  2. Inverse Kinematics

D.     Trajectory Planning [1] 
E.      Robot Sensors [1]

  1. Principles of Sensing 
  2. Sensors of Movement 
  3. Contact Sensors
  4. Proximity and Ranging Sensors 

F.      Robot Vision [1]

  1. Light and Color
  2. Camera Calibration
  3. Images and Image Processing
  4. Feature Extraction 
  5. Vision Based Control 

G.     Robot Programming [1]

H.     Mobile Robots Introduction and Locomotion [1]

I.       Mobile Robots Kinematics [1]

J.       Mobile Robots Perception [1]

  1. Sensors for Mobile Robots 
  2. Place Recognition
  3. Feature Extraction Based on Range Data (Laser, Ultrasonic)

K.     Mobile Robots Localisation [1]

  1. The challenge of Localising
  2. Dead Reckoning 
  3. Localise with a map 
  4. SLAM 

L.      Mobile Robots Planning & Navigation [2]

  1. Reactive Navigation 
  2. Path Planning 
  3. Obstacle Avoidance – Bug algorithm and others
  4. Map Based Planning