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. Throughout the course, students will incrementally build their own vision-based robotics system in simulation via a series of homework coding assignments.

Instructor: Shuran Song

TA: Neil Nie (neilnie@stanford.edu) 

Time:  TuTh 9:00AM - 10:20AM

• Location:   530-127

• Credit: 3 or 4 credit

• Office Hour: 
  Neil Nie Wed 10:00 -12:00 am -- questions about HWs, held in the basement of the Huang engineering building.
  Shuran Song: Th 10:30 - 11:30  am  -- questions about lectures

• Ed Discussion: https://edstem.org/us/courses/50146/discussion/

• Lecture Slides: https://www.dropbox.com/scl/fo/vqqwy6u36pkm5xx2989gk/h?rlkey=2prtqae1c4bvlueijek9gkwln&dl=0

• Lecture Recordings: https://edstem.org/us/courses/50146/discussion/4104413 

Pre-requisites:

• Data Structures

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

• Knowledge of elementary linear algebra

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

Grading:

• In-class quizzes: 10% + 15% for 2 quizzes 

• Homework assignments:  75% total for 5 HWs

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

1) Write a proposal about ideas to improve the pick-and-place system you have implemented: Describe the motivation, and which aspect of the system you want to improve Describe the method, please free feel to include pseudocode, block diagram, and figures that would help us understand your method. Describe the expected outcome, and how would you set up experiments to validate the improvement. 

2) 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 on Thursday at 5 pm. 

• You have 4 late days for the whole quarter (count by day e.g., an hour late == a day)

• No more exceptions beyond the 4 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. 

Not seeing anything above? Reauthenticate