ver: 1.0

date: 2018-08-18

Instructor

Adj. Prof. Vladimir Skvortsov

Phone

032-626-1212

E-mail

vlad at sunykorea.ac.kr or vladimir.skvortsov at stonybrook.edu (be sure to include ”[CSE378]” with no spaces, in the subject line of any e-mail message you send to me)

Office

Building B, room 409

Office Hours

Mo, We 1:00-1:45 PM or by appointment. Office hours are only held when classes are in session.

Calendar

Please see below a list of Textbooks, Grading, a tentative Schedule of topics, as well as the deadlines for all assignments

Lectures

See the academic calendar

Objectives

This course aims to introduce the basic concepts in robotics, focusing on popular robot develop-ments and illustrations of current state of the art. The concepts that will be discussed include coordinate transformations, visual perception, sensors, path planning, kinematics, feedback and feedforward control.

Course Learning Outcomes:

  • Working knowledge of basic robotics concepts including coordinate transformation, kine- matics, dynamics, sensor integration, feedback and feedforward control

  • An understanding of the role of these concepts in robot control (reactive, behavior-based, and hybrid), robot learning and multi-robot systems

  • Ability to construct and evaluate real robot systems in course assignments and projects

Major Topics Covered in Course

Matrix Algebra, Basic Linear Control Theory, Frequency Domain Analysis, Introduction to Scilab, R, Python or Matlab/Simulink, Coordinate Transformations, Direct and Inverse Kinematics, Dynamics, Nonlinear Control, Trajectory Planning, Force Control, Sensors & Actuators, Filtering, Optimal Control, Behavior-based control

Structure

  • Two weekly sessions (each 75 minutes)

    • 1st session: lecture, practical exposition, discussion

    • 2nd session: lecture, practical

Textbooks

  1. [book-Cra05] J. J.Craig. IntroductiontoRobotics. 3e. Pearson/PrenticeHall, 2005. ISBN: 978-0201543612

  2. [book-Thr05] S. Thrun et al. Probabilistic Robotics. MIT Press, 2005. ISBN: 0-534- 39528-7

  3. [book-Cho04] Howie Choset et al. Principles of Robot Motion: Theory, Algorithms, and Implementations. MIT Press, 2004

  4. [book-Cor11] Peter Corke. Robotics, Vision and Control : Fundamental Algorithms in MATLAB. vol. 73. Springer Tracts in Advanced Robotics. Berlin: Springer, 2011. ISBN: 9783642201448. URL: https://doi.org/10.1007/978-3-642-20144-8

  5. [book-Spo06] S. Hutchinson M. W. Spong and M. Vidyasagar. Robot Modeling and Control. New York: John Wiley & Sons, 2006. ISBN: 978-0-471-64990-8

  6. [book-Mur94] Richard M. Murray, S. Shankar Sastry, and Li Zexiang. A Mathematical Introduction to Robotic Manipulation. 1st. Boca Raton, FL, USA: CRC Press, Inc., 1994. ISBN: 0849379814

Slides

CSE378 Introduction to Robotics, slides, [cse378p01] part 1, [cse378p02] part 2

Schedule

Current date:

First day of semester:

Last day of semester:

A number of days during semester:

Last day of classes: (Final exams start)

Weekdays of class:

The days of studies from to .

The table lists the sections we will cover in each lecture. Revisions may be made during the semester. It lists the required reading in Notes, and it is important to do the reading before the scheduled class. Lectures falling on Holidays when no classes are held will be made-up in subsequent lectures.

Assignments

There will be some homework assignments, a final project and a midterm exam. You are expected to do homeworks by yourselves. Even if you discuss them with your classmates, you should turn in your own write-up.

  • 2 regular homework assignments (HW1, HW2) plus 1 optional assignment which will be depended upon progress in regular ones

  • Midterm Exam (ME) - This will be a written test

  • Final Project (FP) - submission of the report

Exams/Assignments schedule: TBA

Grading

Course grades will be based on a combination of:

  • HW - 2 (+ 1 optional) homework assignments (30%)

  • ME - Midterm exam (30%)

  • FP - Final Project (35%)

  • AT - Attendance (5%)

Each assignment contributes points to a student’s final grade (there are 100 points total). The total # of points earned at the end of the semester will determine the student’s final letter grade, based on the thresholds below:

F

D

D+

C-

C

0-59

60-65

66-70

71-73

74-77

C+

B-

B

B+

A-

A

78-80

81-83

84-87

88-90

91-93

94+

Example: 90.94 points would award you a B+ grade but 90.95 rounds to 91 and would award you an A- grade.

Course grade calulator:

Enter 4 tab separated values (
HWHomeworks score
MEMidterm score
FPFinal Project score
ATAttendance
) or replace the sample values

Total (points→letter):

Tools

br

RStudio

Shiny

R Packages

RStudio includes a code editor, debugging & visualization tools

Shiny helps you make interactive web applications for visualizing data

Developers created many packages to expand the features of R

br