16-811: Math Fundamentals for Robotics, Fall 2015

Professor: Michael Erdmann (me at -nospam- cmu.edu)
Teaching Assistants:   Sankalp Arora  (asankalp at -nospam- andrew.cmu.edu)
                                      Chung-Yao Chuang  (chungyac at -nospam- andrew.cmu.edu)
                                      Yen-Chia Hsu  (yenchiah at -nospam- cs.cmu.edu)
Location: HH B103 (Hamerschlag Hall)
Time: TR 3:00-4:20

The last week of office hours is the last week of classes, ending on December 11.
(Feel free though to stop by Michael Erdmann's office.)

Michael Erdmann's Office Hours: After class or by appointment (office is GHC 9203).
Sankalp Arora's Office Hours: Wednesdays, 10am-11am, NSH 4225
Chung-Yao Chuang's Office Hours: Fridays, 1-2pm, in NSH 4211
Yen-Chia Hsu's Office Hours: Mondays, 2-3pm, in NSH 4225

Please note: Office hour times and locations may vary each week depending on conference room availability.


Lecture Synopses

Copies of (handwritten) lecture notes are available online here.


We have set up an instance of Piazza for this course: to answer questions about the assignments, allow for students to discuss course material, and make announcements about the class. You are responsible for being current with the information and discussions that are posted there. (We auto-enrolled everyone for this instance of Piazza who, on September 8, was registered in the course or who indicated on the signup sheet during lecture that day that they plan to hand in assignments.)


This course covers selected topics in applied mathematics, taken from the following list:
1. Solution of Linear Equations.
2. Polynomial Interpolation and Approximation.
3. Solution of Nonlinear Equations.
4. Roots of Polynomials, Resultants.
5. Approximation by Orthogonal Functions (includes Fourier series).
6. Integration of Ordinary Differential Equations.
7. Optimization.
8. Calculus of Variations (with applications to Mechanics).
9. Probability and Stochastic Processes (Markov chains).
10. Computational Geometry.
11. Differential Geometry.

Course Activity

This is a graduate course. You are thus expected to pursue ideas and topics discussed in this course on your own beyond the level of the lectures. My aim is to cover some of the easy early material quickly, then spend more detailed time on the later material. My goal throughout the course is to acquaint you with fundamental algorithms and mathematical reasoning, as well as give you some implementation experience.

The course grade will be determined by performance on assignments, participation in class, and a class project. Class assignments will entail solving some problems on paper or implementing some of the algorithms discussed in the course.

The term project should take about a month of work (40 hours) per person. It should pursue a mathematical topic in a robotics setting that is not otherwise covered in detail in the course. Ideally, the project should be connected to your research. If you are a first year graduate student, you should view the project as a springboard to research involvement. Project writeups should be 5 pages long. Project writeups are due at the end of the last presentation (actually, in 2015, they will be due about a week later). Project presentations will occur near the end of the term, depending on room availabilities. Projects may be individual projects or team projects. Team projects must be commensurately larger in scope than single person projects. Projects that are used in more than one course need to be significantly more substantial than single course projects. A team project that is used in more than one course needs to be very significant.


In order to pass this course you must do all the work required. "Doing all the work" entails coming to class, submitting solutions for the assignments, and doing the project. You must submit a solution for every problem on an assignment by that assignment's due date. Assignments are graded on a "minus, check, plus" scale. You must receive a "check" or a "plus" on every assignment in order to pass the course. If you obtain a "minus" on an assignment, you may and must submit correct solutions by the resubmission deadline for that assignment, in order to try to raise your assignment grade to a "check". (The resubmission deadline is not an alternate deadline for the original assignment; you need to attempt every problem by the original deadline.) For the project, you should submit a project proposal, a project writeup, and present your project publicly (it remains to be determined whether we will have short talks or a poster session). (Not doing all the work as described above within the time frame allotted means you fail the course.)


There is no required text for this course. The lecture material is available online (as scans of handwritten notes). The following is a suggested reading list. Much of the lecture material is taken from these books.
1. W. H. Press, B. P. Flannery, S. A. Teukolsky, and W. T. Vetterling. Numerical Recipes in C. Cambridge University Press. (Any edition.)

2. G. Strang. Introduction to Applied Mathematics. Wellesley-Cambridge Press. 1986.

3. G. H. Golub and C. F. Van Loan. Matrix Computations. Johns Hopkins University Press. 1983.

4. S. D. Conte and C. de Boor. Elementary Numerical Analysis. Third edition. McGraw-Hill. 1980.

5. G. E. Forsythe, M. A. Malcolm, and C. B. Moler. Computer Methods for Mathematical Computations. Prentice-Hall. 1977.

6. D. G. Luenberger. Introduction to Linear and Nonlinear Programming. Addison-Wesley. 1973.

7. R. Weinstock. Calculus of Variations. Dover Publications. 1974. (Reprint of 1952 McGraw-Hill edition.)

8. R. Courant and D. Hilbert. Methods of Mathematical Physics. Volume I. John Wiley and Sons. 1989. (Reprint of 1953 Interscience edition.)

9. W. Yourgrau and S. Madelstam. Variational Principles in Dynamics and Quantum Theory. Dover Publications. 1979. (Reprint of a 1968 edition.)

10. F. P. Preparata and M. I. Shamos, Computational Geometry, Springer-Verlag, New York, 1985. (Corrected and expanded printing: 1988.)

11. J.-C. Latombe, Robot Motion Planning, Kluwer Academic Publishers, Boston, 1991.

12. W. Feller. An Introduction to Probability Theory and Its Applications. Volume 1. Third edition. John Wiley and Sons. 1968.

13. B. O'Neill, Elementary Differential Geometry, Academic Press, New York, 1966. 2nd Edition: 1997.

Use of Recording Devices

Please do not record my lectures or take images of me. University policy on this matter suggests the following formal statement:

No student may record any classroom activity without express written consent from me.  If you have (or think you may have) a disability such that you need to record or tape classroom activities, you should contact the Office of Equal Opportunity Services, Disability Resources to request an appropriate accommodation.
Thank you.