EE 5351 – Syllabus – Spring 2014
(SENIOR/GRADUATE ELECTIVE COURSE)
Instructor:
Scott R. Norr, PE
Office: 154 MWAH
Phone: 726-8947
Office Hours: Monday: 11-Noon, Thursday: 11-Noon – Office Schedule
Email: snorr@d.umn.edu
Lecture Place & Time:
Chem 251, MWF, 3:00 – 3:50 PM
Textbook: Siciliano, Sciavicco, Villani, Oriolo – Robotics: Modelling Planning and Control, 2009
Springer-Verlag
Computer Usage: Mathematica, Matlab, or equivalent;
Assessment:
Homework will be due at the beginning of lecture, 1 week from the day assigned..
One Mid-Term examination and one Final examination will be given; work must be
shown to receive partial credit.
For Graduate Credit: Additional problems will be added to assigned homework. A paper will be
written on the topic of robotics and presented orally in class.
Course work will be weighted as follows:
Week
1
2
3
4
5
6
7
8
3/17 - 21
9
10
11
12
13
14
15
5/13
Homework: 30%, Midterm: 30%, Final Exam: 40%
Topics
____ _ Reference_______
Introduction, Review of Linear Algebra
Chap 1, App A
Linear Algebra, Review of Control Theory
App A, App C
Kinematics
Chap 2
Kinematics, Inverse Kinematics
Chap 2
Differential Kinematics Exam I
Chap 3
Statics
Chap 3
Actuators
Chap 5
DC Servo Control and Modeling
Chap 5
SPRING BREAK
Internal/External Sensors
Chap 5
Dynamics
Chap 7
Trajectory Planning Exam II
Chap 4
Motion Control
Chap 8
Force Control
Chap 9
Visual Servoing/Motion Planning
Chap 10,11
Graduate Student Presentations
Final Exam - Tuesday, May 13, 2PM-4PM
Individuals who have any disability, either permanent or temporary, which might affect their ability to
perform in the class, are encouraged to inform the instructor at the start of the semester. Adaptations may
be made as required to provide for equitable participation
ABET Outcomes Delivered by this Course:
a. An ability to apply knowledge of mathematics,
science and engineering
e. An ability to identify, formulate and solve
engineering problems
Instructor Signature: _________________________
c. An ability to design a system, component or
process to meet desired needs
k. An ability to use the techniques, skills and
modern engineering tools necessary for engineering
practice
Date: __January 20, 2014____
EE 5351 - Robotics and Mobile Platforms
Spring semester 2014
UMD CATALOG DESCRIPTION:
Basic concepts and tools for the analysis,
design, and control of robotic mechanisms.
Topics include basic robot architecture and
applications to dynamical systems, mobile
mechanisms, kinematics, inverse kinematics,
trajectory and motion planning, mobile roots,
collision avoidance, and control
architectures.
Educational Goals:
This course provides a broad overview of the
engineering concepts associated with design,
analysis and control of robotic platforms. Indepth emphasis is placed on selected topics
including forward and reverse kinematics,
differential kinematics, sensors, actuators,
feedback control schemes, machine vision and
motion planning.
Course Outcomes (indexed to ABET ):
 Apply linear algebra to kinematic modeling of
robotic platforms
 Understand and use Euler Angles, unit
quaternions and translational matrices
 Use inverse kinematics to obtain joint position
 Understand and model the dynamic forces in
robotic motion
 Apply feedback control to robotic motion
 Apply feedback control to robotic manipulators
 Use image processing to facilitate machine
vision
 Understand the canonical problem statement of
motion planning
 Apply artifical potential techniques to motion
planning
The student gains skills and understanding in
the areas of linear modeling of structures,
modeling theory, applied kinematics,
dynamics and motion control, mapping and
motion planning.
MATLAB is used to reinforce concepts in
linear algebra, modeling of kinematic
structures, feedback control theory, robust
control and image processing.
Relationship to ECE Program Objectives:
 Builds on fundamental concepts learned in
physics, linear algebra, differential equations
and control systems
 Incorporates math skills acquired in calculus,
linear algebra and differential equations
 Improves ability to use math and engineering
skills to model and analyze robotic platforms
 Improves ability to design electrical and
electronic components for use in robotic
platforms and their supporting control systems
 Broadens and deepens the range of engineering
skills acquired in curriculum