Distinguished Visiting Professor Keith Sullivan, Hopper Hall 453, x36810,
Your final grade will be computed as follows:
If you receive more than three negative peer evaluations, you will receive a 50% penalty on each lab grade.
Plus/minus grades will be assigned based on the following numerical cutoffs:
| - | + | ||
|---|---|---|---|
| A | 90–92 | 93–100 | |
| B | 80–82 | 83–86 | 87–89 |
| C | 70–72 | 73–76 | 77–79 |
| D | 60–66 | 67–69 | |
| F | 0–59 |
In case this course policy needs to be changed during the semester, students will be notified by email and verbally during class. The current version will always be posted on the course website.
The guidance in the Honor Concept of the Brigade of Midshipmen and the Computer Science Department Honor Policy must be followed at all times. See https://www.usna.edu/CS/resources/honor.php. Specific instructions for this course:
All collaboration and outside sources should always be cited. The same rules apply for giving and receiving assistance. If you are unsure whether a certain kind of assistance or collaboration is permitted, you should assume it is not, work individually, and seek clarification from your instructor.
The use of generative AI tools to help complete assignments is treated the same as collaboration or assistance with a human (see above) and is therefore prohibited under most circumstances. Please talk with your instructor if you believe there are ways to use generative AI tools without hindering the course learning objectives.
Students are responsible for all class material including the recommended readings. However, the readings are not exhaustive and students missing class should arrange to copy notes from a classmate.
Remote classes may be recorded for future reference. Remnote attendees will make every effort to connect to class sessions and give them undivided attention. Remote attendees will adhere to the same uniform and grooming standards as those attending in person.
Labs will not be accepted late without a really good reason, which was clearly communicated as early as possible.
Everyone in the classroom will show appropriate respect to each other at all times. All discussions will be civil.
The section leader is responsible for recording attendance, bringing the class to attention, notifying the CS department office if the instructor is more than 5 minutes late, and directing the class in useful work in the instructor’s absence.
Drinks are permitted, but they must be in closable containers. Food, alcohol, smoking, smokeless tobacco products, and electronic cigarettes are all prohibited. Electronic devices must be silent during class and should never serve as a distraction to other students.
Extra instruction (EI) is strongly encouraged and should be scheduled by email. EI is not a substitute lecture; students should come prepared with specific questions or problems.
Robots are everywhere from warehouses to autonomous cars to vacuums. Two big challenges in robotics are moving in the world and sensing the world. This course presents an overview of robot mapping and navigation (state estimation and SLAM) followed by an overview of computer vision on a robot (optical flow, 3D vision, object identification). Course projects and labs will culminate in an autonomous robot performing surveillance of a building.
2-2-3
IC211 and (IC312 or SY301)
Graduates of the program will have an ability to:
There are no required textbooks for this class. All required reading will be the provided class notes. If you are interested in the topics of the class, here are some useful resources: