Formation ECAM LaSalle Ingénieur spécialité Mécanique et Génie Electrique (ENGINEERING PROGRAM)
General Data
Academic program Formation ECAM LaSalle Ingénieur spécialité Mécanique et Génie Electrique (ENGINEERING PROGRAM) :
Type d'EC Classes (LIIEEng06ESensPerc)
Lectures : 8h00
Tutorials : 4h00
Lab Work : 12h00
Total duration : 36h00 		Status :
Period :
Semester 6		 Education language :
English
Learning Outcomes
By the end of this course, students will be able to:
1. Understand the physics and functioning of various sensors used in robotics
2. List all the elements of the Data Acquisition Chain and their features
3. Acquire the know-how for characterizing and calibrating sensors
4. Acquire the methodology to dimensioning sensors for specific applications
5. Apply knowledge in signal processing and statistics to robotic contexts
6. Create a Data Acquisition Chain from scratch
7. Program a microcontroller to sample data accurately
8. Learn the basics of image processing
9. Develop good programming practices (documentation, test, git/gitflow)
Content
-Inertial sensors, GPS and odometry / sonar sensing / vision, bio-inspired sensors, force sensors
-Transformation of information into electric properties and its implication
-Signal conditioning
-ADC: sampling, quantization, windowing
-MCU: Application of data acquisition, data analysis, data processing
-Introduction to image processing
Pre-requisites / co-requisites
-Metrology
-Computer programming
-Object-oriented programming
-Simulation and numerical calculation 1
-Simulation and numerical calculation 2
-Electronics 1 – Components and technology
-Electronics 2 – Functions and applications
-Digital design and embedded software 1
-Digital design and embedded software 2
-Signal processing
Bibliography
Essential resources: None
Recommended resources:
Handbook of Modern Sensors, Fraden J., AIP Press, Springer
Corke P. (2011) Image Processing. In: Robotics, Vision and Control. Springer Tracts in Advanced Robotics, vol 73. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20144-8_12
Assessment(s)
N° Nature Coefficient Observable objectives
1Observable objectives: labs in which students will be evaluated on their ability to define and implement the components of a Data Acquisition Chain, to program a microcontroller and to program an image processing application using good coding practices.

0,36, 7, 8, 9
2Observable objectives: mid-term exam in which students will be evaluated on their ability to analyze a Data Acquisition Chain and all its components from the physical quantity to processing performed on the MCU.

0,31, 2, 3, 4, 5, 9
3Observable objectives: final exam in which students will be evaluated on their ability to analyze a Data Acquisition Chain and all its components and to apply image processing techniques to gray/color images.

0,4Written exam