Logistics
Course Information
Course Number: 16-280
Course Title: Intelligent Robotic Systems
Semester: Fall 2025
Prerequisites: 21-241 or 18-202 or 21-254. Strong background in C/C++ and Python is expected.
Class Schedule
Lectures: Tuesday & Thursday 15:30-16:50
Location: NSH 3002
Recitations: Thursday 17:00-17:50
Location: CIC Lower Level - Conference Room 2
Office Hours
We are here to help. TA office hours use a queue-based system. The queue will open at the start of office hours - you can find the link to the queue in the top navigation bar of the site. Slots are limited to 15 minutes. Debugging systems takes time. Do your part by starting assignments and seeking help early. For questions that require more assistance, please reach out to the course staff to request a meeting outside of office hours.
All office hours are held in the course space in CIC.
| Day | Time | Staff |
|---|---|---|
| Sunday | 12:00-14:00, 15:00-17:00 | Kacper, Julius |
| Monday | 17:00-19:00 | Alex |
| Wednesday | 15:00-17:00 | Smrithi |
| Thursday | 18:00-19:00 | Varies |
| Friday | 14:00-15:00 | Prof. Silwal |
Helpful Resources
We will add helpful resources throughout the semester for topics that we cover, which you can find in the Schedule tab. The following set of resources will also prove useful over the course of the semester:
Assignments
Assignments are released weekly on Tuesdays and are due the following Monday at 23:59 Eastern Standard Time. Assignments will alternate in being completed either individually or in groups week to week. Group assignments will occasionally involve in-person design reviews, where students will demonstrate the functionality and discuss implementation with the course staff.
Communication
Questions should be asked via the course Piazza page accessible through the course Canvas. Private questions can be addressed to the instructor or TA staff via email.
Grading
| Component | Weight | Description |
|---|---|---|
| Homework | 60% | 11 assignments, variably weighed |
| Exams | 35% | Two exams, weighed equally |
| Attendance | 5% | Attendance form each lecture |
Recitations are not required, but will cover material and examples that will be highly relevant to the homework. Lecture attendance will be collected via a form that will open in the attendance tab in the first 5 minutes of each class. Attendance at at least 80% of lectures is required for a full score, and scores will decrease linearly below the threshold.
Homework Weighting
We try to weigh assignments proportionally to their anticipated difficulty and time input. Please use this for your planning. HW10 is an integrative assignment that will combine work from the prior portions of the semester, not including manipulation topics. You are given 4 weeks to complete the assignment, which will be demo'ed during the class final exam time slot. There will be no extensions, so please plan your work wisely.
| HW | Weight |
|---|---|
| 1 | 3% |
| 2 | 5% |
| 3 | 5% |
| 4 | 4% |
| 5 | 6% |
| 6 | 3% |
| 7 | 4% |
| 8 | 5% |
| 9 | 4% |
| 10 | 15% |
| 11 | 5% |
Boundaries & Curving
We anticipate grade boundaries to follow as below:
| % Cutoff | Letter Grade |
|---|---|
| 90% | A |
| 80% | B |
| 70% | C |
| 60% | D |
Individual assignments and exams will not be curved. Final grades may be adjusted up, but never down. Borderline grades will be evaluated on a case-by-case basis, taking into account attendance, effort, and performance over the course of the semester.
Regrades
We occasionally make mistakes in grading. If you believe your assignment was not graded according to the rubric published in Gradescope, you may submit a regrade request through Gradescope within one week of grade release.
Bonuses
Bonus points will occasionally be offered on assignments throughout the semester to complete challenge or extensions of assignments that will further strengthen and improve your understanding. We encourage you to complete the bonus opportunities that are exciting to you.
Late Policy
4 penalty-free late days are allotted for individual assignments. You may take up to a total of 4 late days on each assignment. We strongly advise students to save late days for the later portion of the course, as deadlines tend to pile up towards the second half of the semester and assignments become more challenging.
After penalty-free late days are used, the maximum score for individual assignments follows:
| Days Late | Maximum Score |
|---|---|
| <1 day | 80% |
| <2 days | 60% |
| <3 days | 40% |
| <4 days | 20% |
| >4 days | 0% |
It is difficult to replace the in-person experience of demonstrating the group assignments, so there are no late days on group assignments. If your group must submit late, we will accept a video demonstration up to 4 days late. The penalties follow:
| Days Late | Maximum Score |
|---|---|
| <2 days | 50% |
| <4 days | 25% |
There will be no extensions on assignments in general. Late days for individual assignments are intended to provide flexibility for circumstances that may arise throughout the semester rather than poor planning. If you believe you really need an extension on an assignment, contact the course staff as soon as possible and before the deadline.
Policy on Artificial Intelligence
Our interest is your learning. Nowadays, it takes even more grit to stay focused and truly engage with the material when AI tools are readily available. You are welcome to use AI as a study tool — to explore concepts, clarify ideas, or deepen your understanding. However, all submitted assignments must be your own original work. Development and debugging are not tasks to outsource, but are rather skills that take practice to build. Short-circuiting this process will ultimately leave you poorly prepared for the exceptional work you’ll do in future coursework and beyond your time at CMU.