EECS227: Robot Perception

Overview:

Robot Perception is the cornerstone of modern robotics, enabling machines to interpret, understand, and respond to an array of sensory information they encounter.  In the course, students will study the basic principles of typical sensor hardware on a robotics system (e.g., vision, tactile, and acoustic sensors), the algorithms that process the raw sensory data, and make actionable decisions from that information. We will discuss both modular-based perception systems and end-to-end policy learning.

Throughout the course, students will incrementally build their own vision-based robotics system in simulation via a series of homework coding assignments. Students will also get hands-on experience in the iterative improvement process for robotics system design, which includes testing and evaluating the developed system, identifying issues and weaknesses of the system, and making improvements to the system based on the evaluation.

Instructor: Shuran Song

TA:  Neil Nie, Austin Patel, Xiaomeng Xu

Email: Please direct questions to ee227-fall-2024-staff@googlegroups.com

Time:  11:30 AM - 12:50 PM 

• Location:  NVIDIA Auditorium

• Credit: 3 or 4 credit 

• Office Hour:  

TA office hour. Questions  related to homework:
Tue 3:00 -5:00 pm  (Huang Engineering Building Basement)
Mon 6:00 - 8:00 pm (Online Zoom). Appointment is needed.  

Shruan's office hour. Questions  related to lecture: Wed 1:00 - 2:00 pm (Huang Engineering Building Basement)

• Lecture Slides: https://www.dropbox.com/scl/fo/2dftkv4d16xmrl49z79qu/AHoFU-5jYpPNfkxz9LvBCjA?rlkey=svqzj042gs45p4uxau8pgcqip&dl=0 (Dropbox)

• Lecture Recordings: on Canvas

• Ed Discussion: https://edstem.org/us/courses/67522/discussion/ 

Pre-requisites:

• Data Structures

• Knowledge of  Python. We will be using Python extensively in this course.

• Knowledge of elementary linear algebra (e.g. MATH 51)

We will use matrix transpose, inverse, and other operations to do algebra with matrix expressions. We’ll use transformation matrices to rotate/transform points. These topics are important for the homework.  

• If you are not sure whether you are ready for the course, please check with the course instructor. 

Grading:

• 5 HW (10 % each) + 2 Quizzes (25% each)

• 4-credit students are required to submit an additional 2-page report in the last assignment: 

Write a literature review or survey on topics we discussed in the lecture. For example, a survey on "single-view depth estimation." In the survey please categorize the works into three categories.  For each category, describe the general idea, the work that belongs to this category, and the general pros and cons for this category of approach. 

Late Policy: 

• DDL is always at 5 pm. 

• You have 2 late days for the whole quarter (count by day, e.g., an hour late == a day)

• No more exceptions beyond the 2 late days.  

• No more TA support after the deadline. If you choose to use late days, there will be no TA support for those days. 

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