SAE-GFR Calculation of Visual Odometry using Camera Images
Visual odometry offers another solution for localization. Taking successive pictures and
comparing key points on them makes it possible to determine how the vehicle's position has changed
over time. The project for the 2024 season will be to investigate and implement a visual odometry method
using ORB SLAM as well as determine the effectiveness vs. the current odometry pipeline
Objectives
● Fall
○ Background research of previous projects and relevant papers completed.
○ Github and development environment set up.
○ ROS tutorial and assignment completed.
○ Design changes conceptualized.
○ Practice for participation in rules quiz.
○ Documentation for any changes made during Fall.
● Winter
○ Final documentation for code completed - details on wiki as well.
○ Testing and benchmarking completed and documented.
○ UML Diagram detailing system.
○ Final edits to the code by May.
Motivations
GFR's autonomous vehicle uses two cameras and a LiDAR for cone detection and racetrack detection. Camera imaging and processing is critical for accurately identifying the vehicle's position and feeds important data into the motor controllers.
Qualifications
Minimum Qualifications:
None Listed Preferred Qualifications:
None Listed
Details
Project Partner:
Devin Pham
NDA/IPA:No Agreement Required
Number Groups:1
Project Status:Accepting Applicants
Website:https://www.global-formula-racing.com/en/
