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Robotics and Autonomous Systems

Objectives

Available soon

General characterization

Code

10991

Credits

6.0

Responsible teacher

José António Barata de Oliveira, Luís Manuel Camarinha de Matos

Hours

Weekly - 5

Total - 66

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

Available soon

Evaluation method

Available soon

Subject matter

  1. INTRODUCTION [1]
    1. Intelligent Robots
    2. Brief History of AI ROBOTICS
    3. Automation and Autonomy
  2. SOFTWARE ORGANISATION OF AUTONOMY [2]
    1. Introduction to Architectures
    2. Types of architectures: Operational, Systems, and Technical
    3. Operational Deliberative and Reactive Architectures (old approaches)
    4. Operational Architecture: Hybrid with reactive, deliberative, and interactive functionality
    5. Systems Architecture: Planning, Navigation, Mapping, Motor Schema, and Perception
    6. Systems Architecture Paradigm: Hierarchical, Reactive, and Hybrid
  3. TELEROBOTICS ARCHITECTURES [1]
    1. Concepts Definition
    2. Block Diagram
    3. Main Functionalities
    4. Human Factors
  4. REACTIVE FUNCTIONALITY [2]
    1. Sensors and Sensing
    2. Perception
    3. Behaviours
  5. PLANNING [2]
    1. Introduction
    2. Planning with deterministic Models
    3. STRIPS
  6. NAVIGATION [1]
    1. 4 Questions of Navigation
    2. Spatial Memory
    3. Types of Path Planning
    4. Landmarks and Gateways
  7. LOCALIZATION, MAPPING, and EXPLORATION [1]
    1. Localisation
    2. Mapping
    3. SLAM – Simultaneous Localisation and Mapping
    4. Exploration
  8. LEARNING [1]
    1. Overview
    2. Supervised Learning
    3. Unsupervised Learning
    4. Reinforcement Learning
  9. HUMAN ROBOT INTERACTION [1]
    1. Overview
    2. User Interfaces
    3. Modelling Domains, Users, and Interactions
  10. MULTIROBOT SYSTEMS [2]
    1. Challenges and Opportunities
    2. Types of MRS
    3. Swarm Intelligence

Programs

Programs where the course is taught: