Difference between revisions of "ESE297 - Intro to Undergraduate Research"

From ESE497 Wiki
Jump to navigationJump to search
 
(216 intermediate revisions by 2 users not shown)
Line 1: Line 1:
* Meeting Time: Wednesday 8:30 - 10 am
+
[[File:IMG_1248.jpg|400px]]
* Office Hours: Monday 8:30 - 10 am or by appointment
+
 
* Team Members: Alex Gu, Andrew Wiens, Alexander Benjamin, Anisha Rastogi, Charlie Kang, Edison Kociu, Lisa Goldman, Michael Scholl, Sam Fok, Sarah Fern, Sophia (Xinyuan) Cui, Will Donnelly
+
ESE297 - Introduction to Undergraduate Research was created for students who wish to do Undergraduate Research projects in [[media:Robotic_Sensing_V4.pdf|Robotic Sensing]] under [http://ese.wustl.edu/people/Pages/faculty-bio.aspx?faculty=11 Professor Nehorai], the ESE Department Chair. This course is offered as ESE297 for 2 credits and is typically offered in the spring and summer. Students will learn how to implement sensor array signal processing algorithms on the [[LabVIEW for Robotics|LabVIEW for Robotics Starter Kit robots]] shown above using both Matlab and LabVIEW and develop Brain Computer Interface (BCI) algorithms using EEG signals. Students can then apply this knowledge to individual research projects in Robotic Sensing in subsequent semesters. ESE297 does not qualify as an EE elective.
* PhD Supervisor: Sandeep, Andrew, Phani
+
== Logistics ==
* Faculty Supervisor: Arye Nehorai
+
* '''Meeting Time''': Fri, 1:30-5:30 in Bryan 316
* Goal:
+
* '''Holidays''': Fall Break, Thanksgiving
** Part1: Case Study - Study acoustic source localization using Microphone array
+
* '''Instructor''': Ed Richter, Bryan 201E
*** Background and Theory
+
* '''T/A''': Stephen Gower (sgower@wustl.edu)
*** Data Acquisition Basics
+
* '''Office Hours''': Mon,Tues 2:30-4 (Ed), Thurs 8-10pm (Steve)
*** Introduction to Digital Signal Processing Tools
+
* '''[[media:Syllabus-FL15.pdf‎ |Syllabus]]'''
*** Graphical User Interface and Robot Control
+
* '''Expectations''': The work load is estimated to be 10 hours/week if you take it during the Fall or Spring semesters (20 hours/week for a summer semester). That is, students who earn an A will spend many unsupervised hours outside of the class meeting times. Grading is based on your Homework and your Projects. Late work will be accepted with a penalty of 3 points per day. Please see the syllabus for due dates.
** Part2: Implement algorithm using sbRIO robot and microphone array
+
 
 +
= Announcements =
 +
* Matlab available for Students now! Send email to support@seas.wustl.edu
 
== Lecture Notes ==
 
== Lecture Notes ==
* Week 1: [http://classes.engineering.wustl.edu/ese497/index.php/File:Presentation_Robotic_Microphone_Array.pdf Acoustic Source Location Background and Theory]
+
* [[Accostic Source Location]]
** Additional references:
+
* [[Data Acquisition Basics]]
***[http://ese.wustl.edu/ContentFiles/Research/UndergraduateResearch/CompletedProjects/WebPages/fl08/JoshuaYork/index.html Joshua York, Acoustic Source Localization, ESE497, Fall 2008]
+
* [[Signal Processing Basics]]
***[http://ese.wustl.edu/ContentFiles/Research/UndergraduateResearch/CompletedProjects/WebPages/fl09/rms3/index.htm Raphael Schwartz and Zachary Knudsen, Robotic Microphone Sensing: Data Processing Architectures for Real-Time, Acoustic Source Position Estimation, ESE497, Fall 2009]
+
* [[Brain Computer Interface (BCI)]], [[media:BCI2000.zip|BCI2000.zip]]
** Task 1: Read the material that we discussed in our meeting today and the additional references listed above.
+
 
** Task 2: Derive the expressions presented in slide 10.
+
== Projects ==
* Week 2: Data Acquisition Basics
+
* [[Project1:_Implement_algorithm_using_microphone_array| Project1: Implement algorithm using microphone array]]
** [[media:LabVIEW_Introduction.pdf|LabVIEW Tutorial]]
+
* [[Project2:_Triangulation_with_sbRIO_robots|Project2: Triangulation with sbRIO robots]]
*** Task 3 - Finish Exercises
+
* [[BCI Projects]]
** [[media:Data_Acquisition_Basics.pdf|Data Acquisition Basics]]
+
== 2013 Upgrade work-around ==
*** Task 4 - Finish exercise
+
* Copy [[media:RobotMicSourceLocator.vi|RobotMicSourceLocator.vi]] to RoboticSensing\MicSourceLocator
** Task 5 - Connect wires from A00 and AO1 to AI0 and AI1 (Disconnect the Function Generator output). Modify your vi to collect samples from both AI0 and AI1. Then run [[media:DelayedChirp2DAC.zip|DelayedChirp2DAC.vi]]. Zoom in in the time and frequency domain to examine the waveforms in detail. Describe in detail what you see. Hint: Start and stop your Data Acquisition vi until the entire signal is in the middle of the buffer.
+
* Copy [[media:MoveWheels (Host).vi|MoveWheels (Host).vi]] to RoboticSensing\Examples\MoveWheels (Host).vi (***NOTE*** Change '_' to ' ')
** Task 6 - Using the 4 microphone array and the metal data acquistion box, collect samples from all 4 channels and display them on your graph. Measure the delay between the signals - does it agree with the speed of sound?
+
* Copy [[media:MoveRobot.vi|MoveRobot.vi]] to RoboticSensing\MicSourceLocator
* Week 3: Filters Basics
 
**[[Media:Filters_&_Application.pdf|Tutorial]]
 

Latest revision as of 18:44, 2 October 2015

IMG 1248.jpg

ESE297 - Introduction to Undergraduate Research was created for students who wish to do Undergraduate Research projects in Robotic Sensing under Professor Nehorai, the ESE Department Chair. This course is offered as ESE297 for 2 credits and is typically offered in the spring and summer. Students will learn how to implement sensor array signal processing algorithms on the LabVIEW for Robotics Starter Kit robots shown above using both Matlab and LabVIEW and develop Brain Computer Interface (BCI) algorithms using EEG signals. Students can then apply this knowledge to individual research projects in Robotic Sensing in subsequent semesters. ESE297 does not qualify as an EE elective.

Logistics

  • Meeting Time: Fri, 1:30-5:30 in Bryan 316
  • Holidays: Fall Break, Thanksgiving
  • Instructor: Ed Richter, Bryan 201E
  • T/A: Stephen Gower (sgower@wustl.edu)
  • Office Hours: Mon,Tues 2:30-4 (Ed), Thurs 8-10pm (Steve)
  • Syllabus
  • Expectations: The work load is estimated to be 10 hours/week if you take it during the Fall or Spring semesters (20 hours/week for a summer semester). That is, students who earn an A will spend many unsupervised hours outside of the class meeting times. Grading is based on your Homework and your Projects. Late work will be accepted with a penalty of 3 points per day. Please see the syllabus for due dates.

Announcements

  • Matlab available for Students now! Send email to support@seas.wustl.edu

Lecture Notes

Projects

2013 Upgrade work-around