16-811: Math Fundamentals for Robotics, Fall 2007
Professor: Michael Erdmann (me at -nospam- cmu.edu)
TA: Sebastian Scherer (basti at -nospam- andrew.cmu.edu)
Location: Doherty Hall A310
Time: TR 3:00-4:20
Michael Erdmann's Office Hours: by appointment.
Sebastian Scherer's Office Hours: Tuesdays 4:30-5:30, either in Sebastian's Office (NSH 2102) or in the Fredkin Room (next to NSH 1109).
Copies of (handwritten)
lecture notes are available online here.
For related online notes I recommend Professor Yan-Bin Jia's CS 577 notes at Iowa
State.
(Yan-Bin Jia is a former RoboGrad!)
Topics
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). It
should pursue a mathematical topic in detail 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.
Typical project writeups are 5-10 pages long. Projects are due the
last day of class. If there is time we will use the last week of
class for project presentations.
Bibliography
The main text for this course is:
- W. H. Press, B. P. Flannery, S. A. Teukolsky, and W. T. Vetterling.
Numerical Recipes in C. Cambridge University Press. 2nd Edition, 1992.
Secondary references include (in approximate order of the material covered):
- 1. G. Strang. Introduction to Applied Mathematics.
Wellesley-Cambridge Press. 1986.
- 2. G. H. Golub and C. F. Van Loan. Matrix Computations. Johns
Hopkins University Press. 1983.
- 3. S. D. Conte and C. de Boor. Elementary Numerical Analysis. Third
edition. McGraw-Hill. 1980.
- 4. G. E. Forsythe, M. A. Malcolm, and C. B. Moler. Computer Methods
for Mathematical Computations. Prentice-Hall. 1977.
- 5. D. G. Luenberger. Introduction to Linear and Nonlinear
Programming. Addison-Wesley. 1973.
- 6. J.-C. Latombe, Robot Motion Planning, Kluwer Academic Publishers,
Boston, 1991.
- 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. Feller. An Introduction to Probability
Theory and Its Applications. Volume 1.
Third edition. John Wiley and Sons. 1968.
- 10. F. P. Preparata and M. I. Shamos, Computational Geometry,
Springer-Verlag, New York, 1985. (Corrected and expanded printing: 1988.)
- 11. B. O'Neill, Elementary Differential Geometry, Academic Press,
New York, 1966. 2nd Edition: 1997.