. CSE397/497-013: An Introduction to Mobile Robotics TR 1045:1200 PM, Fall 2005

Announcements

• 14 Dec 05:  Homework 7 is posted.  It is due on 20 Dec, 1045AM.
  
• 29 Nov 05:  FYI, there is an error in the Jacobian H on slide 1, page 11, lecture 13. 
  
• 29 Nov 05:  Homework 6 is posted.   Due date is  13 Dec 05. 
  
• 25 Nov 05:  Due to popular demand, there WILL be a 7th homework assignment.   However, it is optional. 
  
• 22 Nov 05:  Because of the scope of homework 5 and the remaining assignments, there will not be a class final. 
  
• 16 Nov 05:  Homework 5 clarifications part deux:
• You probably want to reduce the velocity of the robot to <= 2.5m/s for your motion planner to work well
• You probably will need the wheelbase of the robot to infer its change in orientation from noise.  It is 0.5 meters.
• In the interest of computational efficiency, your paticle motion can be updated at 1 Hz.  However, the robot motion must still be updated at 10Hz. 
  
• 15 Nov 05:  Homework 5 clarification:  Only use the forward 180 degree sonars for motion planning. 
  
• 15 Nov 05:  I've updated the link to Beard's potential field paper. 
  
• 14 Nov 05:  Unfortuntately,  class is canceled for 1 Dec 05.  We will make up the class if necessary.
• 10 Nov 05:  Homework 5 is posted.  This is NOT a trivial assignment, and the deadline will not be extended!  Start today!!!
  
• 03 Nov 05:  I have appended a statement on plagiarism to the course syllabus FYI.
  
• 03 Nov 05:  Homework 4 is due 10 Nov before class. 
  
• 02 Nov 05:  Here is a .m file for showing the use of the mpgwrite toolbox which you can download here.
  
• 31 Oct 05:  Happy Halloween!  Homework 4 is posted. 
  
• 13 Oct 05:  Plan on meeting for our vision lab on 18 Oct 05.  I will send out an email with the details.  If you do not receive an email from me prior to the start of class, then come to MG105 for lecture.
  
• 13 Oct 05:  Homework 3 is posted and is do on 20 Oct 05 BEFORE class.
  
• 04 Oct 05:  Here are supplementary lectures for filtering and edge detection.
  
• 03 Oct 05:  Homework 2 clarifications/expansions:
• You must draw the trajectory that the robot follows.  You can do this using the plot function
  
• All units are SI.  This means meters, seconds, radians, etc.  Please do NOT use cm, degrees, etc. 
  
• When you submit your homework, it MUST be as lehighUserName.zip
  
• Again, late homeworks will NOT be accepted.
  
• 29 Sep 05:  Homework 2 is due 1 week from today (6 Oct 05).
  
• 29 Aug 05:  I will be at a workshop in DC for the first day of class.  However, there WILL be a lecture by Jason Derenick.  If possible please attend. 
  

Course Description
In this course, we will cover the fundamentals of mobile robot kinematics, perceptiom, localization, navigation, and planning.  The objective of this course is to build a toolkit of algorithms allowing students to implement autonomous robot behaviors.   To accomplish this, we will implement these algorithms in both simulation (Matlab) as well as on a mobile robot platform which you will construct over the course of the semester.   The hardware implementation will be a class-wide exercise.  The intent is for the students to implement fundamental behaviors (e.g. GPS waypoint navigation) on a mobile platform by then end of the semester. 

Prerequisites

• Math 23 Analytic Geometry and Calculus III or equivalent
• Math 205 Linear Methods or equivalent or equivalent
• CSE 109 Systems Programming or equivalent programming experience in C/C++

Instructor
John Spletzer
Office Hours:  M/W 6:00-7:00 PM and by appointment

Course Materials
For this course, we will be using the Introduction to Autonomous Mobile Robots text by Siegwart and Nourbakhsh.  We will also be making use of the following online materials (and others), plus selected papers:

1. Particle Filters
• D. Fox et al, Bayesian Filtering for Location Estimation, University of Washington, 2003
  
• S. Thrun, Probabilistic Algorithms in Robotics, Carnegie Mellon University, 2000
2. Kalman Filters
• G. Welch & G. Bishop, An Introduction to the Kalman Filter, University of North Carolina - Chapel Hill, 2001
3. Random Sample Consensus (RANSAC)
• A one page summary from CVOnline
• The original paper (15 pages - you can only access this from the Lehigh server)
  
4. Motion Planning: 
• “Motion Planning Using Potential Fields”,  R. Beard & T. McClain, BYU, 2003
5. Matlab Tutorial & Documentation, Mathworks web site
   

Grading

The breakout of course grading  is as follows:

• Homework assignments:  50%
  
• Class project / final examination:  25%
  
• Class attendance/participation - particularly for the graduate presentations (undergraduate):  25%
• Presentation (graduate):  25%

Homework assignments are individual assignments.  Discussing the homework with another student is fine.  However, each student must submit there own work!

ALL ASSIGNMENTS MUST BE SUBMITTED IN ORDER TO RECEIVE A PASSING GRADE IN THIS CLASS.

Grades will be assigned acording to the following distribution:
.

A	92-100	C	72-76
A-	90-91	C-	70-71
B+	87-89	D+	67-69
B	82-86	D	62-66
B-	80-81	D-	60-61
C+	77-79	F	00-59

Late Policy:  Assignments are due PRIOR to class on the due date.  Late assignments will not be accepted UNLESS you have made arrangements with the instructor prior to the due date. 

Plagiarism: I will submit any case of suspected copying to the University Committee on Discipline. Often, when the discipline committee finds a student guilty of copying, the penalty is a WF in the course. If the Committee on Discipline finds your guilty of the charge of copying and does not assign a WF, I reserve the right to assign the grade of F.   NO COPYING OF PROGRAMMING ASSIGNMENTS WILL BE TOLERATED!

University Policy on Disabilities:  If you have a disability for which you are or may be requesting accommodations, please contact your professor and the Office of Academic Services, Room 212, University Center or call (610-758-4152) as early as possible in the semester.  University policy states that you must notify your professor seven (7) days prior to the exam.

Tentative Schedule
.

DATE	TOPICS	NOTES	ASSIGNMENT
29 Aug 05	Administrative and Introduction	pdf
01 Sep 05	Background	pdf
06 Sep - 08 Sep	Locomotion & Kinematics	pdf pdf	Homework 1 input2.m
13 Sep - 04 Oct	Perception Sensor Systems Probability Review Least Squares RANSAC	pdf pdf pdf pdf	Homework 2 Sample Input File for Hwk2 Homework 3
06-13 Oct 05	Grad Student Presentations (Sermeno-Villalta, Souto)	Joe's Presentation on Line Fitting Humberto's ATRS Presentation
18 Oct 05	Feedback Control	pdf	Homework 4
20 Oct 05	Vision Lab		Edge Detection Hough Transformation
20 Oct - 10 Nov 05	Localization Markov Localization Monte-Carlo Localization Kalman Filtering EKF	pdf pdf pdf	Homework 5 makeMap.m Homework 6 Skeleton m-file Sample mpeg
15 Nov - 17 Nov 05	Motion Planning	pdf	Homework 7 Skeleton m-file
22 Nov 05	Graduate Student Presentations - Mansley
24 Nov 05	Thanksgiving Break
29 Nov 05	Graduate Student Presentations - Zhu & Kowalski	Yaoyao's Data Fusion Presentation Mike's SIFT Presentation
01 Dec 05	Class Cancelled
06 Dec 05	Graduate Student Presentations - Kanitkar & Gianos	Sudhan's Odometry Presentation Tom's RF Navigation Presentation
08 Dec 05	Graduate Student Presentation - Lynch & Course Wrap	Nick's Presentation on the Groundhog Mapping Project