Term
and
Year
of
Offering:
Fall
2013
Course
Number
and
Title:
ECE
780.06
Humanoid
Robotics
Lecture
Times,
Building
and
Room
Number:
Tuesdays,
2:30
–
5:20pm,
EIT
3141
Instructor's
Name:
Dana
Kulić
Office
Location:
E5
5114
Office
Hours:
TBD
Contact:
dana.kulic@uwaterloo.ca
Course
Description:
This
course
provides
an
overview
of
the
fundamentals
and
the
recent
research
in
the
field
of
humanoid
robotics.
The
course
will
cover
kinematics
and
dynamics,
postural
stability,
control,
gait
and
trajectory
generation
and
inertial
parameter
estimation.
Additional
advanced
topics
in
learning,
human-robot
interaction
and
manipulation
and
grasping
and
human
motion
modeling
will
be
covered
as
time
permits.
Course Objectives: At the end of the course you should be able to:
- Develop kinematic and dynamic models for anthropomorphic body structures and simulate their forward and inverse kinematics and dynamics;
- Develop gaits and other trajectories for humanoid robots;
- Implement controllers that ensure postural stability during trajectory execution for humanoid robots;
- Have a good overview of the current research in the field of humanoid robotics;
- Complete a graduate level research project in the field of humanoid robotics.
Course Prerequisites: ECE 486/ECE 687 or equivalent, or permission of the instructor.
Required Text: There is no required text for the course. Reading materials for the course will be available from the course website.
Date | Lecture Topic |
---|---|
Sep 10 | Introduction |
Sep 17 | Kinematics for Humanoids: Forward and Inverse kinematics, structure-varying chains, parallel algorithms |
Sep 24 | Dynamics for Humanoids: Forward and Inverse dynamics, computational issues, parallel algorithms |
Oct 1 | Inertial Parameter Estimation |
Oct 8 | Postural Stability: Zero Moment Point |
Oct 15 | Gait and Trajectory Generation: Off-line methods, inverted pendulum model |
Oct 22 | Gait and Trajectory Generation: CPG and Motion Capture |
Oct 29 | Motion Primitives and Learning from Imitation |
Nov 5 | Dynamic Walking |
Nov 12, 19, 26 | Advanced Topics: Motion Planning, Learning, Human-Robot Interaction, Social Robotics, Emotions, Manipulation and Grasping, Exoskeletons and Assistive Humanoids, Robotic Algorithms for modeling the human body, Ethical Issues. |
Evaluation: The course grade will be based on in-class participation and presentations, a course project, and a final examination which will be held during the Official Examination Schedule. The breakdown is as follows:
-
In
Class
Participation
and
Presentations:
15%
- Weekly Critiques: 20% (Due: every Mon)
- Discussion Leader: 40%
- Lecture: 40%
-
Course
Project
35%
- Project Proposal: 20% (Due: Oct 1)
- Final Project Presentation: 30% (To be scheduled, during last week of lectures)
- Final Project Report: 50% (Due: Dec 1)
- Final Examination 50%
Weekly Critiques: To help prepare for the in-class discussion and learn about recent research, students will be expected to submit a brief analysis of assigned readings each week, consisting of a summary, critical evaluation and questions for further discussion. The critiques will be evaluated based on students' summary and critical analysis of the paper.
Discussion Leader: During the course of the term, each student will lead one in-class discussion, on the topic of that week's assigned readings. Discussion leader scheduling will be decided during the first week of term.
Lecture: During the course of the term, each student will deliver one lecture on a topic of their choice. Lecture selection and scheduling will be decided during the first week of term.
Rules for Group Work: Projects, Discussion Leader and Lectures can be done individually or in groups of up to 3, but groups will have to demonstrate work proportional to their size. Critiques must be done individually.
Late Submissions: No late submission of critiques will be accepted. Late project submissions (proposal or final report) can be handed in via email to the instructor. Late submissions will have 10% of the mark deducted for each day or part of a day that they are late.