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Robotics

Objectives

  1. 1.        Understanding
    1. 1.        Industrial Robots Main Components, types of geometry, and main parameters
    2. 2.        Referentials and Homogeneous Transformations
    3. 3.        Robot Kinematics: forward and Inverse
    4. 4.        Trajectory Planning
    5. 5.        Main Robot Sensors and their characteristics
    6. 6.        Robot Vision
    7. 7.        Mobile Robots Main Characteristics
    8. 8.        Robot Perception and Localisation
    9. 9.        Mobile Robots Kinematics
  2. 2.        Able to Do
    1. 1.        Addressing new problems and implementing strategies in the domain of Industrial and Mobile Robots
    2. 2.        Increase the capacity to implement Industrial Robots Programs and simple mobile robots control programs, including accessing and processing their most relevant sensors
    3. 3.        Apply creativity and innovation
  3. 3.        Non-Technical Competences
    1. 1.        Develop synthesis critical thinking
    2. 2.        Team working and increasing oral and writing communication skills
    3. 3.        Improve time keeping and compliance with meeting deadlines

General characterization

Code

11456

Credits

6.0

Responsible teacher

José António Barata de Oliveira, Luís Manuel Camarinha de Matos

Hours

Weekly - 4

Total - 56

Teaching language

Português

Prerequisites

  • Programming Skills

Bibliography

  • Corke, P. (2017) Robotics, Vision and Control. Cham: Springer International Publishing (Springer Tracts in Advanced Robotics).
  • Jazar, R. N. (2010) Theory of Applied Robotics. Boston, MA: Springer US. 
  • Kelly, A. (2013) Mobile Robotics, Mobile Robotics: Mathematics, Models, and Methods. New York: Cambridge University Press. 
  • Mihelj, M. et al. (2019) Robotics. Cham: Springer International Publishing. ~
  • Siegwart, R., Nourbakhsh, I. R. and Scaramuzza, D. (2011) Introduction to Autonomous Mobile Robots, Second Edition, MIT Press. MIT Press. 
  • LaValle, S. (2006). Planning Algorithms. Cambridge: Cambridge University Press. 
  • Edelkamp, S., & Schrödl, S. (2011). Heuristic search: theory and applications. Elsevier.
  • Choset, H. M., Lynch, K. M., Hutchinson, S., Kantor, G., Burgard, W., Kavraki, L., ... & Arkin, R. C. (2005). Principles of robot motion: theory, algorithms, and implementation. MIT press.

Teaching method

Theoretical-practical classes (TP) are directed so that students, through their active participation, understand each of the topics listed in the learning objectives.

 

In laboratory classes (PL) students focus on the experimentation of the concepts exposed in theoretical-practical classes in order to know how to do.

For each practical work:

  • Presentation of the work,
  • tutorial on the technology / tools to use,
  • discussion of the work method,
  • realization of the work by the students accompanied by teachers, and
  • preparation of report.

 

Evaluation Components

  1. 1.      2 Mini-Tests
  2. 2.      3 Practical Works

 

Evaluation Rules

  1. 1.      Theoretical Mark = (Mini-Test 1 + Mini-Test 2) / 2
  2. 2.      Theoretical Mark >= 9.5
  3. 3.      Each Practical Work >= 9.5
  4. 4.      Practical Mark = TP1 * Weight1 + TP2 * Weight2 + TP3*Peso3 ; Weights to be announced at the beginning of UC
  5. 5.      Final Mark = Practical Mark * 0.6 + Theoretical Mark * 0.4

Evaluation method

Evaluation Components

  1. 1.      2 Mini-Tests
  2. 2.      3 Practical Works

 

Evaluation Rules

  1. 1.      Theoretical Mark = (Mini-Test 1 + Mini-Test 2) / 2
  2. 2.      Theoretical Mark >= 9.5
  3. 3.      Each Practical Work >= 9.5
  4. 4.      Practical Mark = TP1 * Weight1 + TP2 * Weight2 + TP3*Peso3 ; Weights to be announced at the beginning of UC
  5. 5.      Final Mark = Practical Mark * 0.6 + Theoretical Mark * 0.4

Subject matter

  1. 1.        INTRODUCTION
    1. 1.      Historical Development
    2. 2.      Robot Components
    3. 3.      Robot Classifications & Parameters
  1. Position and Orientation
    1. Referentials & Orientation
    2. Transformation Matrices
  2. Robot Arm Kinematics
    1. Forward and Inverse Kinematics
  3. Trajectory Planning
  4. Robot Sensors [1]
    1. Principles of Sensing
    2. Sensors of Movement
    3. Proximity and Ranging Sensors
  5. Robot Vision
    1. Camera Calibration
    2. Images and Image Processing
    3. Vision Based Control
  6. Robot Programming
  7. Mobile Robots
    1. Introduction
    2. Locomotion
    3. Kinematics
  8. Mobile Robots Perception
    1. Sensors for Mobile Robots
    2. Place Recognition
    3. Feature Extraction Based on Range Data (Laser, Ultrasonic)
  9. Mobile Robots Localisation
    1. The challenge of Localising
    2. Dead Reckoning (3.6.1)
    3. Localise with a map & SLAM
  10. Mobile Robots Planning & Navigation
    1. Reactive Navigation
    2. Obstacle Avoidance – Bug algorithm and others
    3. Map Based Planning

Programs

Programs where the course is taught: