General Information
Location: Horizon Hall 1010
Time: 1:30 pm - 2:45 pm, Tuesday and Thursday
Homework Submissions: Turn in paper copy before classes on Thursdays
Project Submissions: Email to Instructor and TA based on project specific instructions
Discussion Forum: Piazza
Grades: Blackboard
Course Textbook:
Probabilistic Robotics, by Sebastian Thrun, Wolfram Burgard, and Dieter Fox
Principles of Robot Motion Theory, Algorithms, and Implementations, by Howie Choset, Kevin M. Lynch, Seth Hutchinson, George A. Kantor, Wolfram Burgard, Lydia E. Kavraki, and Sebastian Thrun
Planning Algorithms, by Steven M. LaValle
Prerequisites
The recommended prerequisites for this course are CS 262: Introduction to Low-Level Programming, CS 310: Data Structures, MATH 203: Linear Algebra, and CS 480: Introduction to Artificial Intelligence
Familiarity in the following topics and strong mathematical maturity is highly recommended:
- Probability
- Linear algebra
- Calculus
The students will be using C/C++ and Python for the projects. Familiarity with algorithms and data structures is highly recommended.
Class Participation
Students are expected to be present in class and participate actively in the discussions. Quizzes will be conducted in class without notice in advance.
Standardized Project
At the beginning of the semester, all students will form a team of three and finish a standardized project. The goal of this project is to familiarize with the Robot Operating System (ROS) and implement existing or new robotics algorithms. This standardized project will be based on The BARN Challenge in the simulated BARN Dataset. Bonus points can be acquired if the students implement algorithms in the extended DynaBARN Dataset. The student will follow the participation procedure of The BARN Challenge and submit implemented navigation systems for evaluation.
Proofs of project milestones will be submitted based on specific project instructions. Each team will also submit a standardized procedure so that the instructor and TA can replicate the team's project.
Open-Ended Project
While the standardized project will be finished mid-semester, the student teams will propose an open-ended research project to pursue based on the individual team's interest. The initial stages of this open-ended project, including proposal and setup, may overlap with the standardized project. Requirements of the project include but are not limited to the following and are at the discretion of the instructor and TA:
- Must include a robot (simulated or physical)
- At least, must include implementing a state-of-the-art robotics algorithm
- Ideally, design your own algorithm that can outperform the state-of-the-art (may lead to publication opportunity)
- The amount of effort you spend on the project must be commensurate to a 3-credit class
- Hands-On Robotics Pupper
- Clearpath Jackal
- AgileX Hunter SE
- Clearpath Husky
- Fetch Mobile Manipulator
- Unitree Go1
Submitting Projects
Project submissions will base on project specific instructions. In general, there are four types of submissions:
Milestone Proofs
For the standardized project, proofs of specific project milestones will be required, including screenshot pictures and videos and Github repository links.Project Demonstration
The student teams will demonstrate their project live, in simulation or on physical robots, in front of the class during lecture times.Project Presentation
Formal 15-min project presentations in front of the entire class during lecture times will take place at the end of the projects.Project Reports
Formal 6-page project reports in the IEEE Robotics and Automation Society format (ieeeconf.zip) will be emailed to the instructor and TA. To collaborate on writing using LaTex, Overleaf is recommended. For students who are not familiar with Overleaf, please consult this Learn LaTex in 30 minutes tutorial.Grading Policy
- Participation 5%
- Quizzes 5%
- Assignments 15%
- Midterm 20%
- Standardized Project 15%
- Open-Ended Project 15%
- Final Exam 25%
Extension Policy
There is in general no late policy. You either finish the homework or project, or not. Extensions will be considered on a case-by-case basis, but in most cases they will not be granted. The greater the advance notice of a need for an extension, the greater the likelihood of leniency.
Academic Integrity
Students are encouraged to discuss and collaborate with classmates. But all submissions must be the student's or the student team's (as authorized) own work. Please strictly stick to the Department Honor Code and Mason Honor Code.
Accommodations
If you need academic accommodations, please make sure you contact the instructor at the beginning of the semester or as soon as possible. Also make sure to contact GMU's Disability Services, by email (ods@gmu.edu") or by phone (703.993.2474), which coordinates all academic accommodations. After you have contacted Disability Services, you still need to contact the instructor so that appropriate arrangements can be made.