Lecture notes and reading material
Preliminary lecture notes will be available in PDF format before the class (usually wednesday evening) while definitive lecture notes will be available only after the class has been held, in a timely fashion (usually, at latest a couple of days after the lecture).
Lecture notes will be complemented by possible reading material listed on the syllabus and further pointers, all available on the student area. Due to copyright issues, electronic copies of the material are only available to EPFL students officially enrolled in this course. Students interested in downloading this material can do so from the student area by logging in using with their GASPAR account.
This page will include the information relevant to each week lecture and corresponding material.
Week 1
TOPIC
Organization of the course (team, workload, credits); overview of the course content; introduction to signal processing – signals, time continuity and time discretization, analog and digital signals, baseline concepts.
LECTURERS
Alcherio Martinoli
Week 2
TOPIC
Introduction to signal processing – Fourier series and transform, convolution.
LECTURERS
Alcherio Martinoli
Week 3
TOPIC
Introduction to signal processing – sampling, reconstruction, and aliasing.
LECTURERS
Alcherio Martinoli
Week 4
TOPIC
Introduction to signal processing – additional transforms (Discrete-Time Fourier Transform, Laplace, z-Transform); transfer functions, impulse and step responses; filter analysis and synthesis.
LECTURERS
Alcherio Martinoli
Week 5
TOPIC
Introduction to signal processing – filter order and type; digital filter analysis and synthesis; C programming refresher.
LECTURERS
Alcherio Martinoli and Chiara Ercolani
Week 6
TOPIC
Introduction to embedded systems – terminology, main modules (perception, communication, computation, and action); sensor types and performance, power consumption, and management.
LECTURERS
Alcherio Martinoli
Week 7
TOPIC
Introduction to embedded systems – communication and real-time programming.
LECTURERS
Alcherio Martinoli
Week 8
TOPIC
Introduction to mobile robotics – simple control architectures and high-fidelity simulation.
LECTURERS
Alcherio Martinoli
Week 9
TOPIC
Introduction to mobile robotics – localization and positioning systems.
LECTURERS
Alcherio Martinoli
Week 10
TOPIC
Introduction to mobile robotics – localization in presence of uncertainties and corresponding estimation methods in 1D.
LECTURERS
Alcherio Martinoli
Week 11
TOPIC
Introduction to mobile robotics – filtering methods for 2D localization
LECTURERS
Alcherio Martinoli
Week 12
TOPIC
Sensor systems for environmental monitoring: programmable instruments with different mobility (static and mobile nodes).
LECTURERS
Alcherio Martinoli
Week 13
TOPIC
Sensor systems for environmental monitoring (robotic nodes). The course takes home messages. Discussion of the course evaluation by the students.
LECTURERS
Alcherio Martinoli