Signals, instruments and systems
ENG-366
Media
This file is part of the content downloaded from Signals, instruments and systems.
Objectives
The goal of this course is to transmit knowledge in sensing, computing, communicating, and actuating for programmable field instruments and, more generally, embedded systems. The student will be able to put in practice the knowledge acquired using concrete software and hardware tools.
Support
Please send questions and concerns to the TA mailing list: sis-ta@groupes.epfl.ch
Course webpage
Part of the information that will be posted on Moodle is also available on the official webpage of the course: https://disal.epfl.ch/teaching/signals_instruments_systems
In particular, a rich information about previous editions of the course is available here:
- News forum (Forum)
- Discussion Forum (Forum)
- Course syllabus and exam guidelines (copy) (Text and media area)
- Course syllabus (URL)
- Final exam guidelines (URL)
- Tools (copy) (Text and media area)
- Webots Installation Guidelines (File)
- Matlab programming material for self-study (Text and media area)
- Matlab material by Jean-Daniel Bonjour (former teacher of Informatique pour l'ingénieur) (URL)
- C programming material for self-study (copy) (Text and media area)
- Linux Cheat Sheet (File)
- C programming lab - assignment (File)
- C programming lab - solution (File)
- C programming lab - code (File)
Lecture
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.
- Lecture notes week 1 (URL)
- Video recording of week 1 lecture, AY 2021-2022 (URL)
- Lab Self-assessment test for Matlab and C programm... (Text and media area)
- Self Verification Test Results (Questionnaire)
- Self-verification Test (File)
- Self-verification test material (.zip) (File)
- Self-verification test solutions (.zip) (File)
- Lecture notes week 2 (URL)
- Video recording week 2 lecture, AY 2021-2022 (URL)
- Fourier series demo in Matlab (File)
- Continuous convolution demo in Matlab (File)
- Discrete convolution demo in Matlab (File)
- Lab Exercise in Matlab on signal processing conce... (Text and media area)
- Lab 1 assignment (URL)
- Lab 1 material (.zip) (File)
- Lab 1 matlab cheatsheet (URL)
- Lab 1 tutorial (URL)
- Lab 1 feedback (Questionnaire)
- Lab 1 solution (URL)
Lecture
Introduction to signal processing – sampling, reconstruction, and aliasing.
- Lecture notes week 3 (URL)
- Video recording week 3 lecture, AY 2021-2022 (URL)
- Audio examples (File)
- Video examples (File)
- Lab Exercise in Matlab on signal processing co... (Text and media area)
- Lab 2 assignment (URL)
- Lab 2 material (zip) (File)
- Lab 2 tutorial (URL)
- Lab 2 feedback (Questionnaire)
- Lab 2 solution (URL)
Lecture
Introduction to signal processing – the Laplace transform for continuous-time signals and systems; frequency response, impulse response and transfer function; analog filter analysis and synthesis.
- Lecture notes week 4 (URL)
- Video recording of week 4 lecture, AY 2021-2022 (URL)
- Convolution Theorem from a system perspective (File)
- LabExercise in Matlab on signal processing concep... (Text and media area)
- Lab 3 assignment (URL)
- Lab 3 solution (File)
- Lab 3 (.zip) (File)
- Lab 3 tutorial (URL)
- Lab 3 feedback (Questionnaire)
- Lab 3 solution (URL)
Lecture
Introduction to signal processing – Bode plots; the Z-Transform for discrete-time signals and systems; filter order and type; digital filter analysis and synthesis.
- Lecture notes week 5 (URL)
- Video recordings week 5 lecture, AY 2022-2023 (URL)
- Lab Exercise in Matlab using available data sets o... (Text and media area)
- Lab 4 assignment (URL)
- Lab 4 tutorial (URL)
- Lab 4 material (zip file) (File)
- Lab 4 feedback (Questionnaire)
- Lab 4 solution (URL)
Lecture
Introduction to embedded systems – terminology, main modules (perception, communication, computation, and actuation); sensor types and performance, power consumption, management, generation, and storage.
- Lecture notes week 6 (URL)
- Video recording of week 6 lecture, part I, AY 2022-2023 (URL)
- Video recording of week 6 lecture, part II, AY 2022-2023 (URL)
- Reading (Text and media area)
- Introduction to Autonomous Mobile Robots, Ch. 4, pp. 89-98 (File)
- Lab An introduction to embedded systems programmin... (Text and media area)
- Lab 5 assignment (URL)
- Lab 5 material (.zip) (File)
- Lab 5 tutorial (URL)
- Lab 5 feedback (Questionnaire)
- Lab 5 solution (URL)
- Lecture notes week 7 (URL)
- Video recording of week 7 lecture, AY 2022-2023 (URL)
- Lab Advanced embedded system programming notions l... (Text and media area)
- Lab 6 assignment (URL)
- Lab 6 tutorial (URL)
- Lab 6 material (.zip) (File)
- Lab 6 feedback (Questionnaire)
- Lab 6 solution (URL)
- Course project (Text and media area)
- Project groups (Group choice)
Lecture
Introduction to mobile robotics - high-fidelity simulation (Webots simulator); simple control architectures.- Lecture notes week 8 (URL)
- Video recording of week 8 lecture, AY 2021-2022 (URL)
- Reading (Text and media area)
- The e-puck, a Robot Designed for Education in Engineering (File)
- Webots: Professional Mobile Robot Simulation (File)
- LabIntroductory Webots lab; programming in C but ... (Text and media area)
- Lab 7 assignment (URL)
- Lab 7 material (File)
- Lab 7 tutorial (URL)
- Lab 7 feedback (Questionnaire)
- Lab 7 solution (URL)
- Course project (copy) (Text and media area)
- Project assignment (URL)
- Project documentation (URL)
- Report example (URL)
- Project material (File)
- Lecture notes week 9 (URL)
- Video recording of week 9 lecture, AY 2021-2022 (URL)
- Reading (Text and media area)
- Introduction to Autonomous Mobile Robots, Ch. 3, pp. 47-53 (File)
- Introduction to Autonomous Mobile Robots, Ch. 4, pp. 145-151 (File)
- Introduction to Autonomous Mobile Robots, Ch. 5, pp. 185-191 (File)
- LabOdometry lab in Webots; programming in C but u... (Text and media area)
- Lab 8 assignment (URL)
- Lab 8 tutorial (URL)
- Lab 8 material (File)
- Lab 8 solution (File)
- Lab 8 feedback (Questionnaire)
- Lab 8 solution (URL)
28 April - 4 May
Lecture
Introduction to mobile robotics – Localization with odometry augmented with exteroceptive sensing; Kalman filtering.
- Lecture notes week 10 (URL)
- Video recording of week 10 lecture, AY 2021-2022 (URL)
- Reading (Text and media area)
- Stochastic Models, Estimation, and Control, Ch. 1, pp. 1-16 (File)
- Introduction to Autonomous Mobile Robots, Ch. 4, pp. 151-154 (File)
- Introduction to Autonomous Mobile Robots, Ch. 5, pp. 227-233 (File)
- Probabilistic Robotics, Ch3, pp. 33-39 (File)
- LabOdometry augmented with exteroceptive sensing ... (Text and media area)
- Lab 9 assignment (URL)
- Lab 9 tutorial (URL)
- Lab 9 material (File)
- Lab 9 solution (URL)
- Lab 9 solution (code) (File)
- Lab 9 feedback (Questionnaire)
5 May - 11 May
Lecture
Environmental sensor systems - robotic localization in practice and sensor networks.
- Lecture notes week 11 (URL)
- Video recording of week 11 lecture, AY 2021-2022 (includes C refresher) (URL)
- Video recording of week 7 lecture, AY 2021-2022 (static sensor networks) (URL)
- Reading (Text and media area)
- Introduction to Autonomous Mobile Robots, Ch. 5, pp. 181-184 (File)
- Introduction to Autonomous Mobile Robots, Ch. 5, pp. 233-244 (File)
- Probabilistic Robotics, Ch3, pp. 48-51 and 62-65 (File)
- Hitchhiker’s Guide to Successful Wireless Sensor Network (File)
- LabAssistance for Course Project. (Text and media area)
12 May - 18 May
- Lecture notes week 12 (URL)
- Video recording of week 12 lecture, AY 2021-2022 (mobile sensor networks) (URL)
- Reading (Text and media area)
- Enhancing Measurement Quality through Active Sampling in Mobile Air Quality Monitoring Sensor Networks (File)
- Mitigating Slow Dynamics of Low-Cost Chemical Sensors for Mobile Air Quality Monitoring Sensor Networks (File)
- Extending Urban Air Quality Maps Beyond the Coverage of a Mobile Sensor Network: Data Sources, Methods, and Performance Evaluation (File)
- LabAssistance for Course Project. (copy) (Text and media area)
19 May - 25 May
- Lecture notes week 13 (URL)
- Video recording of week 13 lecture, AY 2021-2022 (URL)
- Reading (Text and media area)
- Tracking Odor Plumes in a Laminar Wind Field with Bio-inspired Algorithms (File)
- A 3-D Bio-inspired Odor Source Localization and its Validation in Realistic Environmental Conditions (File)
- 3D Odor Source Localization using a Micro Aerial Vehicle: System Design and Performance Evaluation (File)
- Autonomous Feature Tracing and Adaptive Sampling in Real-World Underwater Environments (File)
- LabAssistance for Course Project. (Text and media area)
26 May - 1 June
Lecture
None- LabNone. (Text and media area)
- Course projectSubmission of course project deliver... (Text and media area)
- Course project final schedule (URL)