Course Logistics

Course Information

Lecture Schedule
  • Time: Wednesday & Friday, 3:30-4:45 PM
  • Location: 0216 Siebel Center for Computer Science
  • Format: In-person lectures
  • Semester: Fall 2025
Course Credits
  • Credit Hours: 3 (undergraduate) or 4 (graduate)
  • Graduate/Undergraduate: Both
  • Area: Technical Elective
  • Course Number: CS 498GC

Communication

Course Platforms
  • Canvas: Course materials, lecture recordings, grades - Link
  • Campuswire: Q&A forum for course-related discussions - Link
  • Gradescope: Assignment submission and autograding
  • Email: For personal matters only (use Campuswire for course questions)
Note: Please use Campuswire for all technical questions. Public posts for general questions, private posts for questions with student code.

Grading

Grade Distribution (1100 points total)
Component Points Percentage
Coding Exercises (3 total) 500 45.5%
Problem Sets (3 total) 300 27.3%
Assignment 4 (Simulation Project) 100 9.1%
Quiz 1 50 4.5%
Quiz 2 75 6.8%
Quiz 3 75 6.8%
Grading Scale
Grade
A+
A
A-
B+
B
B-
C+, C, C-
D+, D, D-
F

Assignment Policies

Submission Guidelines
  • All assignments must be submitted via Gradescope
  • Code must be properly documented and follow Python PEP 8 style guidelines
  • One and only one deliverable can be turned in late by 2 days
  • For every other deliverable, and past the 2 days for the first late deliverable, 20% penalty per day
  • Assignments must be submitted via Gradescope before the deadline
Collaboration Policy
  • Discussion of concepts with classmates is encouraged
  • All code must be written individually
  • Copying code from other students or online sources is strictly prohibited
  • You must cite any external resources used
  • Violations will be reported to the academic integrity board

Technical Requirements

Software Setup

Students will need to set up the following software environment:

  • Operating System: Ubuntu 22.04 LTS (recommended) or compatible Linux distribution
  • ROS2: Humble Hawksbill (latest LTS version)
  • Python: 3.10 or higher
  • Required Python packages: numpy, matplotlib, scipy, rclpy, tf2_ros
  • Development tools: Git, VS Code or preferred IDE
Important: Virtual machines or WSL2 can be used, but native Linux installation is recommended for best performance.
Hardware Requirements
  • Minimum 8GB RAM (16GB recommended)
  • At least 20GB free disk space
  • Dual-core processor (quad-core recommended)
  • Internet connection for downloading packages and submitting assignments

Academic Integrity

Academic integrity is essential to this course. Please review the University's Student Code regarding academic integrity. All work submitted must be your own. Violations of academic integrity will result in a failing grade for the assignment and may result in a failing grade for the course and further disciplinary action.

What is allowed:
  • Discussing general concepts and approaches with classmates
  • Using course materials and documented external resources
  • Seeking help from instructors and TAs
  • Collaborating on the final project (if done in groups)
What is NOT allowed:
  • Sharing or copying code without proper attribution
  • Using material from fellow students or internet without proper attribution
  • Submitting work from previous semesters
  • Posting assignment solutions online
  • Violating the terms of any licensing agreement

Resources and Support

Getting Help
  • Office Hours: Instructor by appointment, TA hours TBD at CSL 157
  • Campuswire: 24/7 Q&A forum monitored by course staff
  • Study Groups: Encouraged for conceptual discussions
  • ROS2 Documentation: Official tutorials and API references
Accommodations

Students with disabilities who require accommodations should contact the instructor and the Division of Disability Resources and Educational Services (DRES) as soon as possible.

Mental Health Resources

If you are experiencing stress or personal difficulties, the Counseling Center provides free and confidential support services.