The TAIL-Plus dataset is an extension of the previous TAIL (Terrain-Aware MultI-ModaL) dataset, focusing on robot localization and mapping in planetary surface analog environments. The dataset was collected using both wheeled and quadruped robot platforms equipped with a diverse sensor suite, including 3D LiDAR, RGB-D cameras, global-shutter color cameras, RTK-GPS, and IMU.
The dataset features a wide range of conditions, including different types of locomotion, multi-loop trajectories, day-night illumination changes, and varying surface terrain characteristics (coarse and fine sand). These challenging scenarios are designed to test the robustness and accuracy of multi-sensor SLAM algorithms for field robots in unstructured, deformable granular environments, which are representative of planetary exploration tasks.
The dataset provides time-synchronized, spatially-calibrated sensor data, as well as 6-DOF ground truth poses from the IMU-integrated RTK-GPS system. This comprehensive dataset aims to support the development and evaluation of various multi-sensor SLAM approaches, such as LiDAR-inertial, visual-inertial, and LiDAR-visual-inertial fusion.
The authors plan to further expand the dataset by incorporating additional sensor modalities, such as event cameras, infrared thermal cameras, and solid-state LiDARs, as well as exploring more diverse and challenging environments for planetary exploration analog scenarios.
To Another Language
from source content
arxiv.org
ข้อมูลเชิงลึกที่สำคัญจาก
by Zirui Wang,C... ที่ arxiv.org 04-23-2024
https://arxiv.org/pdf/2404.13600.pdfสอบถามเพิ่มเติม