Robótica Cooperativa

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Créditos
4.5
Tipos
Optativa
Requisitos
Esta asignatura no tiene requisitos, pero tiene capacidades previas
Departamento
URV;CS
En esta asignatura, se explican las técnicas de coordinación inteligente entre robots móviles. Dichas técnica se aplicaran en un simulador y en robots reales.

Horas semanales

Teoría
1.8
Problemas
0
Laboratorio
0.9
Aprendizaje dirigido
0
Aprendizaje autónomo
4.8

Objetivos

  1. Understand some cooperative techniques for locating, exploring and perceiving with multiple robots
    Competencias relacionadas: 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
    Competencias relacionadas: CG3, CEA14, CEP3, CEP4, CT3, CT4, CT5,
    Subcompetences:
    • Knowing how to apply the theory in simulations
    • Knowing how to apply the theory in simulations

Contenidos

  1. Auto-localización multi-robot
    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

Actividades

Actividad Acto evaluativo


Development of the theory and simulations


Objetivos: 1 2
Contenidos:
Teoría
27h
Problemas
0h
Laboratorio
6h
Aprendizaje dirigido
0h
Aprendizaje autónomo
36h

Homework by teams, with real robots



Teoría
0h
Problemas
0h
Laboratorio
7.5h
Aprendizaje dirigido
0h
Aprendizaje autónomo
36h

Metodología docente

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)

Método de evaluación

Homework by teams: 80%
Laboratory simulations: 20%

Bibliografía

Básica:

  • Slides "on-line" - OLLER, Albert,

Capacidades previas

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