Less is More: Physical-enhanced Radar-Inertial Odometry

Autor:	Huang, Qiucan, Liang, Yuchen, Qiao, Zhijian, Shen, Shaojie, Yin, Huan
Rok vydání:	2024
Předmět:	Computer Science - Robotics
Druh dokumentu:	Working Paper
Popis:	Radar offers the advantage of providing additional physical properties related to observed objects. In this study, we design a physical-enhanced radar-inertial odometry system that capitalizes on the Doppler velocities and radar cross-section information. The filter for static radar points, correspondence estimation, and residual functions are all strengthened by integrating the physical properties. We conduct experiments on both public datasets and our self-collected data, with different mobile platforms and sensor types. Our quantitative results demonstrate that the proposed radar-inertial odometry system outperforms alternative methods using the physical-enhanced components. Our findings also reveal that using the physical properties results in fewer radar points for odometry estimation, but the performance is still guaranteed and even improved, thus aligning with the ``less is more'' principle. Comment: Accepted by ICRA 2024
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2402.02200 Zobrazit plný text záznamu View this record from Arxiv