Towards Robust Velocity and Position Estimation of Opponents for Autonomous Racing Using Low-Power Radar

TL;DR

This paper introduces a low-power radar-based system for accurately estimating the position and velocity of moving obstacles in autonomous racing, demonstrating promising accuracy with minimal power use.

Contribution

The paper presents a novel integration of a low-power radar sensor into an autonomous racing perception pipeline for robust obstacle tracking.

Findings

Tracking error up to 0.21 m in distance estimation

Velocity estimation error of 0.39 m/s

Power consumption in the range of tens of milliwatts

Abstract

This paper presents the design and development of an intelligent subsystem that includes a novel low-power radar sensor integrated into an autonomous racing perception pipeline to robustly estimate the position and velocity of dynamic obstacles. The proposed system, based on the Infineon BGT60TR13D radar, is evaluated in a real-world scenario with scaled race cars. The paper explores the benefits and limitations of using such a sensor subsystem and draws conclusions based on field-collected data. The results demonstrate a tracking error up to 0.21 +- 0.29 m in distance estimation and 0.39 +- 0.19 m/s in velocity estimation, despite the power consumption in the range of 10s of milliwatts. The presented system provides complementary information to other sensors such as LiDAR and camera, and can be used in a wide range of applications beyond autonomous racing.