Aggressive Racecar Drifting Control Using Onboard Cameras and Inertial Measurement Unit

TL;DR

This paper presents a novel control system for autonomous racecar drifting that combines onboard cameras, inertial sensors, and advanced filtering algorithms to achieve stable drifting with precise trajectory control.

Contribution

It introduces a drift controller with dual feedback loops, utilizing an extended Kalman filter and a robust KASA algorithm for accurate state and circle parameter estimation.

Findings

Car drifts stably with specified center and radius

Effective use of onboard sensors for high-precision pose estimation

Successful implementation on a 1/10 scale race car

Abstract

Complex autonomous driving, such as drifting, requires high-precision and high-frequency pose information to ensure accuracy and safety, which is notably difficult when using only onboard sensors. In this paper, we propose a drift controller with two feedback control loops: sideslip controller that stabilizes the sideslip angle by tuning the front wheel steering angle, and circle controller that maintains a stable trajectory radius and circle center by controlling the wheel rotational speed. We use an extended Kalman filter to estimate the state. A robustified KASA algorithm is further proposed to accurately estimate the parameters of the circle (i.e., the center and radius) that best fits into the current trajectory. On the premise of the uniform circular motion of the vehicle in the process of stable drift, we use angle information instead of acceleration to describe the dynamic of the vehicle. We implement our method on a 1/10 scale race car. The car drifts stably with a given center and radius, which illustrates the effectiveness of our method.