|
CS 371 - Introduction to Artificial Intelligence
4th Hour Project: Monte Carlo Localization |
Due:
- Office hours or scheduled meeting during week 11: Demonstration of improvements over previous group accomplishments and plans for further improvements.
-
During last class 28: Class demonstration of work.
-
All archivable documentation due by the end of the final exam.
Note: Work is to be done in pre-assigned groups.
Mobile Robotics Monte Carlo Localization Challenge
Using the Anki Cozmo robotics platform, implement or improve upon an implementation of
Monte Carlo
Localization with an attempt to solve the
Kidnapped Robot
Problem. Demonstrate and document your work such that future
generations of students could duplicate your results and improve upon them.
Tips:
- Set simple goals. Follow the
KISS Principle.
(You can always set more ambitious goals if you achieve these early.)
Example:
- 1D state space:
- Have a fixed robot that can rotate a camera or
other localizing sensor to determine state θ.
- When you start the system, let initial state θ0 be
the "home state".
- Have the system rotate and sense to build a mapping from sensor
inputs to probable locations.
- After it has terminated mapping, put it in a new mode seeking to
return to home state θ0 when it does not appear to be
home.
- "Kidnap" it by rotating the robot and demonstrate that it can
relocalize and return home.
- Divide labor: project lead, documentation, version control, sensor
model, motor model, etc.
- Plan team meeting times in advance. Budget for approximately 28 total hours for each person including team meetings. Log hours.
Deliverables:
- (30%) Physical demonstration of project
- (30%) Emailed log of each team member's hours along with summary time totals for each team
member. Format for each log line:
- Name, date, time range, brief one-line description of activity
- (40%) Accessible web documentation of project, including goal(s), necessary
instructions to recreate the project (e.g. assembly instructions, software
prerequisites and installation instructions, code developed, use
instructions, etc.), and assessment of functionality (i.e. how well did it
work). NOTE: This should be created within a single folder with
relative links such that it can be easily archived within my web space and
still work.
Anki Cozmo Localization
- Programming tools:
- Possible projects:
- Create a new project where the robot is restricted to rotational
movement only and uses visual camera sensing to localize.
- Find and build upon prior Cozmo 2D localization and mapping work you
might find.
-
Java demonstration of MCL framework for simple 1D MCL problem.
-
MCL Slides
-
Recommended text: "Probabilistic Robotics" by S. Thrun, W. Burgard, and D. Fox
MCL Past Project Documentation
- Spring 2024:
-
J. Dressler, M. Dolan, C. Whitlow, J. Hillesland, T. Verneuil, G. Paresishvili
-
H. Duong, H. Ngo, H. Phung, P. Pham, Y. Amatya
-
C. Boye, J. Llano, K. Estrada, A. Yao, A. Rosas
- Spring 2023:
- Spring 2022:
- Spring 2019:
-
M. Ainsworth, J. Poff, P. Sorenson, C. Stewart, N. Weinel
- W. Churchill, T. Shi, S. Zhan
- M. Maccieri, T.
Mitchell, J. Skinner, O. Wilson, J. Wright