Cooperative Robotics

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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 of intelligent coordination among mobile robots will be studied. These techniques will be applied within a robot's simulator and in real robots as well.

Weekly hours

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

Objectives

  1. Understand some cooperative techniques for locating, exploring and perceiving with multiple robots
    Related competences: CG3, CEA14, CEP3, CEP4, CT3, CT4, CT5,
    Subcompetences:
    • prrr
    • Analise the possibilities of application
  2. Understand the limitations of the cooperative techniques in real environments
    Related competences: CG3, CEA14, CEP3, CEP4, CT3, CT4, CT5,
    Subcompetences:
    • Knowing how to apply the theory in simulations
    • Knowing how to apply the theory in simulations

Contents

  1. Multi-robot auto-localization
    SLAM, probabilistics methods, particle filters, perceptions-based methods
  2. Cooperative exploration and perception
    Coordinated exploration in unknown environments, map generation
  3. Multi-robot tasks coordination
    Task assignment (explicit, emergent), swarms, auctions. ALLIANCE, BLE, M+.
  4. Dynamical physical systems
    Multi-agent systems: software and logical versus physical ones. Dynamics and capacities.
  5. Cooperation related Architectures
    Subsumption, Swarms, InteRRap, ALLIANCE, DPA2

Activities

Activity Evaluation act


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