Autonomous Formula Racecar: Overall System Design and Experimental Validation
This work addresses the challenge of autonomous racing for student competitions, presenting a replicable system design.
The paper tackles the problem of building an autonomous racecar for the Formula Student Autonomous Competition by developing an integrated system with perception and control, achieving successful testing on a closed-loop track.
This paper develops and summarizes the work of building the autonomous integrated system including perception system and vehicle dynamic controller for a formula student autonomous racecar. We propose a system framework combining X-by-wired modification, perception & motion planning and vehicle dynamic control as a template of FSAC racecar which can be easily replicated. 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).