Autonomous Driving System Design for Formula Student Driverless Racecar
This work addresses the specific challenge of autonomous racing in the Formula Student competition, representing an incremental application of existing methods to a new domain.
The paper tackled the problem of building an autonomous driving system for a Formula Student driverless racecar, proposing a LIDAR-vision method for detecting traffic cones and integrating GPS-INS with LIDAR odometry for localization, and tested the system on a closed loop track.
This paper summarizes the work of building the autonomous system including detection system and path tracking controller for a formula student autonomous racecar. A LIDAR-vision cooperating method of detecting traffic cone which is used as track mark is proposed. Detection algorithm of the racecar also implements a precise and high rate localization method which combines the GPS-INS data and LIDAR odometry. Besides, a track map including the location and color information of the cones is built simultaneously. Finally, the system and vehicle performance on a closed loop track is tested. This paper also briefly introduces the Formula Student Autonomous Competition (FSAC) in 2017.