# DRT&R：直接雷达示教与复现

> 原文链接：https://robotics.hellobike.com/papers/2026-09-15-2609-17766
> 频道：papers | 更新日期：2026-09-15 | 标签：arxiv, cs.RO
> 核心摘要：提出DRT&R，将直接雷达处理与局部建图结合，并在道路、越野数据和闭环自主导航中验证。

# DRT&R：直接雷达示教与复现

::: v-pre
> 原文链接：[DRT&R: Direct Radar Teach & Repeat](https://arxiv.org/abs/2609.17766)（arXiv 2609.17766 · 发布日期：2026-09-15）

**DRT&R: Direct Radar Teach & Repeat**

提出DRT&R，将直接雷达处理与局部建图结合，并在道路、越野数据和闭环自主导航中验证。

## 核心要点

- 雷达导航可耐受降水、尘雾和烟雾，但直接方法尚未用于越野或闭环系统。
- DRT&R结合直接旋转雷达处理与局部建图，尽量保留视角相关信息。
- 在344 km道路和20 km越野数据上，多数条件定位误差在4 cm内。
- 在Clearpath Warthog上用MPC闭环自主超过10 km，实时运行并达到SOTA越野雷达跟踪性能。

**验证范围与局限**：验证范围包括道路与越野数据，以及一台Clearpath Warthog越野车的闭环实验。

## 英文摘要 (Abstract)

Radar-based navigation is appealing for its robustness to adverse conditions involving airborne particles, such as precipitation, dust, fog, and smoke, that can cause lidar-based systems to fail. Recently, direct methods that retain and use the entire radar scan rather than sparse points have improved on-road global localization performance. However, they have yet to be deployed in off-road environments or in closed-loop systems. Additionally, even direct global maps may lose information: their global nature leads to a smoothing out of viewpoint-dependent radar artifacts, which can provide pose information when mapping and localization occur along similar trajectories. This paper introduces Direct Radar Teach & Repeat (DRT&R): a direct spinning radar-based navigation stack that maximizes the amount of retained information by combining direct radar processing with local mapping. DRT&R yields state-of-the-art (SOTA) localization performance in both on-road and off-road environments. Using 344 km of on-road data and 20 km of off-road data, DRT&R is able to localize to within 4 cm in most on-road and off-road conditions, and 12 cm in geometrically degenerate and sparse environments. DRT&R is also evaluated autonomously in closed loop with an MPC controller for more than 10 km using a Clearpath Warthog off-road vehicle, demonstrating that it runs in real time and achieves SOTA tracking performance for off-road radar navigation.

作者：Alexander Krawciw, Daniil Lisus, Cédric Le Gentil, Timothy D. Barfoot
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## 原始参考来源 (Sources)

- [arXiv 2609.17766：DRT&R: Direct Radar Teach & Repeat](https://arxiv.org/abs/2609.17766)