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General information

Academic year:
2024
Description:
1. Active 3D Perception systems (LIDAR, ToF, laser triangulation, etc.) 2. Operating principles 3. Non-parametric calibration of laser triangulation systems 4. PointCloud registration 5. 3D Surface reconstruction 6. Surface fitting 7. Measurements in point clouds 8. Sensor-Robot integration
Academic credits:
7
Course coordinator:
Josep Forest Collado

Groups

Group A

Duration:
One-semester, 1st semester
Teaching staff:
Josep Forest Collado
Language of the classes:
English (100%)

Competences

  • CG3- Communicate in an effective way both orally and in writing, preparing documents and presenting projects and results with English language
  • CB6- Possess and understand the knowledge that provides a basis or opportunity to be original in the development and/or application of ideas, often in a research context
  • CB7- That students know how to apply the knowledge acquired and their ability to solve problems in new or unfamiliar environments within broader contexts related to their area of ??study
  • CB8- That students are able to integrate knowledge and face the complexity of making judgments based on information that, being incomplete or limited, includes reflections on social and ethical responsibilities linked to the application of their knowledge and judgments
  • CE1- Programming, at an advanced level, in the languages and libraries most used in intelligent field robotics
  • CE2- Analyse a problem related to intelligent autonomous systems and identify the appropriate techniques and tools to solve it
  • CE6- Know and understand when and how to use the main sensors and actuators available for intelligent field robots
  • CE7- Understand and be able to apply the main computer-based perception techniques
  • CE8- Understand the mathematical foundations of intelligent robotic system algorithms

Syllabus

1. Active 3D perception systems

2. Operating principles and algorithms

3. Calibration of active and passive 3D perception systems

4. 3D point cloud reconstruction

5. Point cloud registration

6. Surface fitting

7. Measuring on point clouds

8. Sensor-robot integration

Activities

Activity type Hours with a teacher Hours without a teacher Virtual hours with a teacher Total
Analysis / case study 15,00 54,00 0 69,00
Theory class 30,00 0 0 30,00
Participatory class 6,00 24,00 0 30,00
Hands-on class 4,00 8,00 0 12,00
Total 55,00 86,00 0 141

Bibliography

    Assessment and Grading

    Assessment activities:

    Description of the activity Assessment Activity % Remediable subject
    Exercices Exercices provide a significant percentage of the mark, so resolving and presenting on time is required. However, presenting exercices is not a requirement for passing the threshold. 10 No
    Lab Session 1: Laser Triangulation Lab Assisting to Lab sessions is MANDATORY. Not complying with this rule may lead to not passing the Lab.
    Team work, preparation in advance, resolution on time and report writing are key to obtain a good mark.
    10 No
    Lab Session 2: Structure From Motion Lab Assisting to Lab sessions is MANDATORY. Not complying with this rule may lead to not passing the Lab.
    Team work, preparation in advance, resolution on time and report writing are key to obtain a good mark.
    10 No
    Lab Session 3: Passive Stereo Lab Assisting to Lab sessions is MANDATORY. Not complying with this rule may lead to not passing the Lab.
    Team work, preparation in advance, resolution on time and report writing are key to obtain a good mark.
    10 No
    Lab Session 4: Iterative Closest Point (ICP) Lab Assisting to Lab sessions is MANDATORY. Not complying with this rule may lead to not passing the Lab.
    Team work, preparation in advance, resolution on time and report writing are key to obtain a good mark.
    10 No
    Written Exam A general qualification procedure where all aspects (theory, exercises and practical lab aspects may be assessed) 50 Yes

    Grading

    The minimum mark to pass the subject is 5. However, averaging between all marks (exercices, labs and exam) will be considered from a mark of 4 points. Maximum mark is 10.

    Specific criteria for the "No show" grade:
    If the student does not take the exam or does not complete the evaluable labs, he/she will be considered as not been presented and will be evaluated with this grade.

    Single Assessment:
    Unique qualification (in case it's required) consists of presenting all lab reports (with evidence of real implementation), writing the exam and optionally, present the exercices resolved.

    Minimum requirements to pass:
    The subject will be considered as "passed" with a minumum mark of 5.0

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