High Speed Autonomous Vehicles Using the Mit Racecar Platform
School Name
Governor's School for Science & Mathematics
Grade Level
12th Grade
Presentation Topic
Engineering
Presentation Type
Mentored
Abstract
Self-driving cars have recently become popular in media. These cars reduce the possibility of accidents and will allow for cars to travel at greater speeds. The Rapid Autonomous Complex-Environment Competing Ackermann-steering Robot is a platform that assists researchers and students in the development of algorithms for high speed autonomous cars. The purpose of this experiment was to determine how best to program a robot to navigate efficiently using environmental stimuli including vision, range scans, and an inertial measurement unit. Through this program, a team was able to develop algorithms for visual analysis for use with the passive stereo camera and navigation algorithms for use with the laser radar range scanner. The team was unable, however, to implement a working solution for the mapping protocol. These algorithms can be applied to most areas of robotics and are the base of many of the popular modern robotic control systems.
Recommended Citation
Cain, Brennan, "High Speed Autonomous Vehicles Using the Mit Racecar Platform" (2017). South Carolina Junior Academy of Science. 92.
https://scholarexchange.furman.edu/scjas/2017/all/92
Start Date
3-25-2017 11:59 PM
Presentation Format
Written Only
Group Project
No
High Speed Autonomous Vehicles Using the Mit Racecar Platform
Self-driving cars have recently become popular in media. These cars reduce the possibility of accidents and will allow for cars to travel at greater speeds. The Rapid Autonomous Complex-Environment Competing Ackermann-steering Robot is a platform that assists researchers and students in the development of algorithms for high speed autonomous cars. The purpose of this experiment was to determine how best to program a robot to navigate efficiently using environmental stimuli including vision, range scans, and an inertial measurement unit. Through this program, a team was able to develop algorithms for visual analysis for use with the passive stereo camera and navigation algorithms for use with the laser radar range scanner. The team was unable, however, to implement a working solution for the mapping protocol. These algorithms can be applied to most areas of robotics and are the base of many of the popular modern robotic control systems.
Mentor
Mentor: Sertac Karaman, Massachussets Institute of Technology