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Robotics and Autonomous Systems

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

10991

Credits

6.0

Responsible teacher

José António Barata de Oliveira, Luís Manuel Camarinha de Matos

Hours

Weekly - 5

Total - 66

Teaching language

Inglês

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

  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: