ROCVFeb 4, 2025

HeRCULES: Heterogeneous Radar Dataset in Complex Urban Environment for Multi-session Radar SLAM

arXiv:2502.01946v316 citationsh-index: 7ICRA
Originality Synthesis-oriented
AI Analysis

This dataset addresses a gap for robotics researchers working on multi-session SLAM and sensor fusion, though it is incremental as it builds on existing single-radar datasets by adding heterogeneity.

The authors tackled the lack of heterogeneous radar datasets for robotics by introducing HeRCULES, a multi-modal dataset integrating 4D radar, spinning radar, FMCW LiDAR, IMU, GPS, and cameras, which enables improved localization, mapping, and place recognition in diverse urban conditions.

Recently, radars have been widely featured in robotics for their robustness in challenging weather conditions. Two commonly used radar types are spinning radars and phased-array radars, each offering distinct sensor characteristics. Existing datasets typically feature only a single type of radar, leading to the development of algorithms limited to that specific kind. In this work, we highlight that combining different radar types offers complementary advantages, which can be leveraged through a heterogeneous radar dataset. Moreover, this new dataset fosters research in multi-session and multi-robot scenarios where robots are equipped with different types of radars. In this context, we introduce the HeRCULES dataset, a comprehensive, multi-modal dataset with heterogeneous radars, FMCW LiDAR, IMU, GPS, and cameras. This is the first dataset to integrate 4D radar and spinning radar alongside FMCW LiDAR, offering unparalleled localization, mapping, and place recognition capabilities. The dataset covers diverse weather and lighting conditions and a range of urban traffic scenarios, enabling a comprehensive analysis across various environments. The sequence paths with multiple revisits and ground truth pose for each sensor enhance its suitability for place recognition research. We expect the HeRCULES dataset to facilitate odometry, mapping, place recognition, and sensor fusion research. The dataset and development tools are available at https://sites.google.com/view/herculesdataset.

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