Cooperative Robotics

Credits

4.5

Types

Optional

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

Laboratory

0.9

Guided learning

Autonomous learning

4.8

Objectives

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

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

Activities

Activity Evaluation act

Development of the theory and simulations

Objectives: 1 2
Contents:

1 . Multi-robot auto-localization
2 . Cooperative exploration and perception
3 . Multi-robot tasks coordination
4 . Dynamical physical systems
5 . Cooperation related Architectures

Theory

27h

Problems

Laboratory

Guided learning

Autonomous learning

36h

Homework by teams, with real robots

Theory

Problems

Laboratory

7.5h

Guided learning

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

Any academic fraud, plagiarism or use or possession of unauthorised means in an assessment activity leads to a mark of zero (0) for the affected test or assignment. Furthermore, in accordance with the University's regulations, if disciplinary proceedings are initiated the subject is recorded as "Pending Assessment" until a decision is reached. These incidents are managed in accordance with the Action Framework for Academic Integrity in Assessment at the UPC.

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