This course covers basic methods and concepts in order to explain how
robots work. We will study how they sense things in the world, how you
make a robot move, and how robots can make their own decisions. We will
study mechanisms (kinematics and dynamics), actuators, sensors (with a
focus on machine vision), signal processing, feedback control theory,
machine learning, and path planning. Students will build software
systems for simulated robots and logged control, image processing, and
path planning to reinforce the material presented in class.
Prerequisites: MATH 235 or 236 and COMPSCI 220 or 230
The honors section of the class will meet on Tuesdays at 2:30PM in CS
140. Materials for the honors section will be posted to the shared UMass
Grades will be evaluated based on assignments, scribing notes, and a
final project. There will be 7 assignments, accounting for 70% of the
class grade, and the project will account for 25% of the class grade.
The scribing duties will account for 5% of your grade.
All assignments are due at 11:55PM on the day listed on the course
schedule. All (typed) scribing notes are due 1 week from the lecture at
11:55PM. You may use a total of five late days in any
combination over all the assignments without penalty. Late assignments
will be determined by their submission time on Moodle. After the late
days are used up, the value of the assignment decreases by 10% for
every additional day taken. Additional days are computed by rounding
up: for example, 2 minutes late, 2 hours late, and 23 hours late all
count as one late day. Submissions close 5 days after the listed due
Academic Honesty and Collaboration Policy:
Unless otherwise noted, all assignments submitted by you, including
your writeup and code, must be your own, coded by you, formulated by
you, and explained by you. You may discuss the general topics of the
course and the assignment problems with anyone, however, the solution
you turn in must be based entirely on your understanding of the problem.
As a rule of thumb, to distinguish discussion from plagiarism, feel
free to discuss problems verbally or via temporary written means
(e.g. whiteboard) but do not share any written matter or code. On each
assignment, you must list all collaborators and people you have
discussed the assignment with and credit all sources.