New Trends in Robotics

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Credits
3
Types
Elective
Requirements
This subject has not requirements, but it has got previous capacities
Department
URV;CS
The discipline of robotics is now extending its arms towards new applications in new environments, to meet new demands of a new society. Most of the success is motivated by the application of AI techniques.
In this course, some of such AI techniques will be analysed.

Teachers

Person in charge

  • Albert Oller ( )

Weekly hours

Theory
1.2
Problems
0
Laboratory
0.6
Guided learning
0
Autonomous learning
3.2

Objectives

  1. Probabilistic techniques applied in robotics
    Related competences:
    Subcompetences:
    • Bayesian filters, Extended Kalman filters, Ant colony optimization, Particle filtering
  2. Search techniques are applied in robotics
    Related competences:
    Subcompetences:
    • Voronoi teselation, A*, C-space
  3. Decision making techniques applied in robotics
    Related competences:
    Subcompetences:
    • Intelligent control, Action selection, Task assignment

Contents

  1. Probabilistic techniques
    Probabilistic techniques actually applied in robotics
  2. Search techniques
    Search techniques actually applied in robotics
  3. Decision making techniques
    Decision making techniques actually applied in robotics

Activities

Activity Evaluation act


Paper discussion: probabilistic methods


Objectives: 1
Theory
6h
Problems
0h
Laboratory
3h
Guided learning
0h
Autonomous learning
16h

Paper discussion: search methods


Objectives: 2
Theory
6h
Problems
0h
Laboratory
3h
Guided learning
0h
Autonomous learning
16h

Paper discussion: decision making methods


Objectives: 3
Theory
6h
Problems
0h
Laboratory
3h
Guided learning
0h
Autonomous learning
16h

Teaching methodology

For each AI methodology:
Week-1. Classroom slides and paper introduction (by teacher)
Week-2. Homework: paper reading
Week-3. Paper discussion in classroom
Week-4. Report writing
Week-5. Oral presentation. Next paper introduction (by teacher)

Evaluation methodology

Report of Probabilistic methods 33%
Report of Search methods 33%
Report of Decision Making methods 33%

Bibliography

Complementary:

  • Scientific papers will be provided - Múltiple authors, , .

Previous capacities

No previous specific competences are required

Addendum

Contents

There are no changes to the information published in the Academic Guide.

Teaching methodology

Due to COVID19, NTR course will start fully online. This methodology could last till the end of the first term. Only if the clinical and social situation stabilizes in a save condition and classes can turn back to face-to-face, the registered students will be asked to decide if they prefer to continue with online classes or move to in-room classes. No decision will be taken unilaterally by the professor, but as a result of an agreement between all the students.

Evaluation methodology

There are no changes to the information published in the Academic Guide.

Contingency plan

There are no changes to the information published in the Academic Guide.