ShanghaiTech Mapping Robot is All You Need: Robot System for Collecting Universal Ground Vehicle Datasets

Fuente: arXiv
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Autori principali: Xu, Bowen, Zhao, Xiting, Feng, Delin, Yang, Yuanyuan, Schwertfeger, Sören
Natura: Preprint
Pubblicazione: 2024
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author Xu, Bowen
Zhao, Xiting
Feng, Delin
Yang, Yuanyuan
Schwertfeger, Sören
author_facet Xu, Bowen
Zhao, Xiting
Feng, Delin
Yang, Yuanyuan
Schwertfeger, Sören
contents This paper presents the ShanghaiTech Mapping Robot, a state-of-the-art unmanned ground vehicle (UGV) designed for collecting comprehensive multi-sensor datasets to support research in robotics, Simultaneous Localization and Mapping (SLAM), computer vision, and autonomous driving. The robot is equipped with a wide array of sensors including RGB cameras, RGB-D cameras, event-based cameras, IR cameras, LiDARs, mmWave radars, IMUs, ultrasonic range finders, and a GNSS RTK receiver. The sensor suite is integrated onto a specially designed mechanical structure with a centralized power system and a synchronization mechanism to ensure spatial and temporal alignment of the sensor data. A 16-node on-board computing cluster handles sensor control, data collection, and storage. We describe the hardware and software architecture of the robot in detail and discuss the calibration procedures for the various sensors and investigate the interference for LiDAR and RGB-D sensors. The capabilities of the platform are demonstrated through an extensive outdoor dataset collected in a diverse campus environment. Experiments with two LiDAR-based and two RGB-based SLAM approaches showcase the potential of the dataset to support development and benchmarking for robotics. To facilitate research, we make the dataset publicly available along with the associated robot sensor calibration data: https://slam-hive.net/wiki/ShanghaiTech_Datasets
format Preprint
id arxiv_https___arxiv_org_abs_2406_16713
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle ShanghaiTech Mapping Robot is All You Need: Robot System for Collecting Universal Ground Vehicle Datasets
Xu, Bowen
Zhao, Xiting
Feng, Delin
Yang, Yuanyuan
Schwertfeger, Sören
Robotics
This paper presents the ShanghaiTech Mapping Robot, a state-of-the-art unmanned ground vehicle (UGV) designed for collecting comprehensive multi-sensor datasets to support research in robotics, Simultaneous Localization and Mapping (SLAM), computer vision, and autonomous driving. The robot is equipped with a wide array of sensors including RGB cameras, RGB-D cameras, event-based cameras, IR cameras, LiDARs, mmWave radars, IMUs, ultrasonic range finders, and a GNSS RTK receiver. The sensor suite is integrated onto a specially designed mechanical structure with a centralized power system and a synchronization mechanism to ensure spatial and temporal alignment of the sensor data. A 16-node on-board computing cluster handles sensor control, data collection, and storage. We describe the hardware and software architecture of the robot in detail and discuss the calibration procedures for the various sensors and investigate the interference for LiDAR and RGB-D sensors. The capabilities of the platform are demonstrated through an extensive outdoor dataset collected in a diverse campus environment. Experiments with two LiDAR-based and two RGB-based SLAM approaches showcase the potential of the dataset to support development and benchmarking for robotics. To facilitate research, we make the dataset publicly available along with the associated robot sensor calibration data: https://slam-hive.net/wiki/ShanghaiTech_Datasets
title ShanghaiTech Mapping Robot is All You Need: Robot System for Collecting Universal Ground Vehicle Datasets
topic Robotics
url https://arxiv.org/abs/2406.16713