Competencies and objectives
Course context for academic year 2023-24
This course is compulsory for the third year of the degree of Robotics Engineering. This subject deals with concepts related to the perception of a robot. Specifically, everything related to 3D vision (homography, 3D data processing, etc.) and you will see subjects with less depth of touch and other sensory sources such as the voice.
Course content (verified by ANECA in official undergraduate and Master’s degrees) for academic year 2023-24
Specific Competences (CE)
- CE17 : Conèixer diverses classes de dispositius sensors usats per a capturar informació del robot mateix i del seu entorn, a més dels principis de funcionament. Saber aplicar els mètodes i tècniques per a mesurar, processar, fusionar i representar la informació captada.
- CE31 : Conèixer i entendre les tècniques per a detectar, reconèixer o seguir elements dins de l'entorn d'un robot i saber utilitzar o desenvolupar algorismes per a engegar aquestes tècniques.
Transversal Competences
- CT1 : Capacitats informàtiques i informacionals.
- CT2 : Ser capaç de comunicar-se correctament tant de forma oral com escrita.
- CT3 : Capacitat d'anàlisi i síntesi.
- CT4 : Capacitat d'organització i planificació.
Learning outcomes (Training objectives)
No data
Specific objectives stated by the academic staff for academic year 2023-24
- To understand the geometric model of the acquisition process of a visual sensor and the basic calibration techniques, and be able to calibrate a camera.
- To understand the process of correspondence between images of a scene taken from different points of view and know techniques to carry it out.
- To know the basic transformations in geometry of multiple views (Projective, Aim, Euclidean) based on the movement of the sensor and the projection of perspective and to know how to apply it to processes of estimation of movement and / or 3D reconstruction.
- To know how to implement methods of visual and tactile perception for the recognition of 3D surfaces.
- To understand the methodologies of sensorial fusion based on multiple sensors: complementary, cooperative and competitive, and to know sensorial fusion estimators according to the typology of the sensors.
General
Code:
33730
Lecturer responsible:
GOMEZ DONOSO, FRANCISCO RAFAEL
Credits ECTS:
6,00
Theoretical credits:
1,20
Practical credits:
1,20
Distance-base hours:
3,60
Departments involved
-
Dept:
SCIENCE OF COMPUTING AND ARTIFICIAL INTELLIGENCE
Area: SCIENCE OF COMPUTING AND ARTIFICIAL INTELLIGENCE
Theoretical credits: 1,2
Practical credits: 1,2
This Dept. is responsible for the course.
This Dept. is responsible for the final mark record.
Study programmes where this course is taught
-
DEGREE IN ROBOTIC ENGINEERING
Course type: COMPULSORY (Year: 3)