Multi-Robot Systems

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Credits
4.5
Types
Elective
Requirements
This subject has not requirements, but it has got previous capacities
Department
URV;CS
In this subject, the techniques related to multi-robot systems will be studied. Some of these techniques will be applied within a robot's simulator and others in real robots as well.

Teachers

Person in charge

  • Albert Oller Pujol ( )

Weekly hours

Theory
1.8
Problems
0
Laboratory
0.9
Guided learning
0
Autonomous learning
4.8

Competences

Generic Technical Competences

Generic

  • CG3 - Capacity for modeling, calculation, simulation, development and implementation in technology and company engineering centers, particularly in research, development and innovation in all areas related to Artificial Intelligence.

Technical Competences of each Specialization

Academic

  • CEA14 - Capability to understand the advanced techniques of Vision, Perception and Robotics, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.

Professional

  • CEP3 - Capacity for applying Artificial Intelligence techniques in technological and industrial environments to improve quality and productivity.
  • CEP4 - Capability to design, write and report about computer science projects in the specific area of ??Artificial Intelligence.

Transversal Competences

Teamwork

  • CT3 - Ability to work as a member of an interdisciplinary team, as a normal member or performing direction tasks, in order to develop projects with pragmatism and sense of responsibility, making commitments taking into account the available resources.

Information literacy

  • CT4 - Capacity for managing the acquisition, the structuring, analysis and visualization of data and information in the field of specialisation, and for critically assessing the results of this management.

Appropiate attitude towards work

  • CT5 - Capability to be motivated for professional development, to meet new challenges and for continuous improvement. Capability to work in situations with lack of information.

Objectives

  1. Understand some cooperative techniques for locating, exploring and perceiving with multiple robots
    Related competences: CT3, CT4, CT5, CEA14, CEP3, CEP4, CG3,
  2. Understand the limitations of the cooperative techniques in real environments
    Related competences: CT3, CT4, CT5, CEA14, CEP3, CEP4, CG3,

Contents

  1. Multi-robot auto-localization
    SLAM, probabilistics methods, particle filters, perceptions-based methods
  2. Techniques related to exploration and perception
    Exploration in unknown environments, sensory data management and map generation
  3. Multi-robot tasks coordination
    Task assignment: explicit (Finite-state machines), emergent (behaviour-based), swarms, auctions (market-based, voting)
  4. Dynamical physical systems
    Multi-agent systems: software and logical versus physical ones. Dynamics and capacities.
  5. Multi-robot related Architectures
    Subsumption, Swarms, InteRRap, ALLIANCE, DPA2, others...

Activities

Activity Evaluation act


Development of the theory and simulations


Objectives: 1 2
Contents:
Theory
27h
Problems
0h
Laboratory
6h
Guided learning
0h
Autonomous learning
36h

Homework by teams, with real robots



Theory
0h
Problems
0h
Laboratory
7.5h
Guided learning
0h
Autonomous learning
36h

Teaching methodology

In hours in the classroom exposed to the theoretical computer support.

In the laboratory classroom hours are put into practice the theoretical knowledge from simulation exercises.

At the end of the first month exposed the subject to develop the student (in groups of 3-4)

Evaluation methodology

Homework by teams: 80%
Laboratory simulations: 20%

Bibliography

Basic:

  • Slides "on-line" - Oller, Albert,

Previous capacities

Some knowledge about mobile robots
Some knowledge about computer vision
Some knowledge about agents