期刊
XXIV ISPRS CONGRESS: IMAGING TODAY, FORESEEING TOMORROW, COMMISSION I
卷 5-1, 期 -, 页码 203-210出版社
COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/isprs-annals-V-1-2022-203-2022
关键词
Crazyflie; UAV; IMU; micro robot; mobile laser scanning; obstacle avoidance
资金
- European Union
- Korean Government [833435]
This paper presents the operations and mapping techniques of two drones used for mapping indoor spaces. Both the Crazyflie and MAX drones are capable of mapping cluttered indoor environments and providing sufficient point clouds for quick exploration. The results show that the LIDAR scanner-based system can handle larger office environments with minimal drift, while the Crazyflie drone performs well given its limited sensor configuration.
The use of drones to explore indoor spaces has gained attention and popularity for disaster management and indoor navigation applications. In this paper we present the operations and mapping techniques of two drones that are different in terms of size, the sensors deployed, and the positioning and mapping techniques used. The first drone is a low-cost commercial quadcopter microdrone, a Crazyflie, while the second drone is a relatively expensive research quadcopter macrodrone, called MAX. We investigated their feasibility in mapping areas where satellite positioning is not available, such as indoor spaces. We compared the point clouds obtained by a multi-ranger deck, a multi-layer LIDAR scanner and a stereo camera, and assessed each against ground truth obtained with a terrestrial laser scanner. Results showed that both drones are capable of mapping relatively cluttered indoor environments and can provide point clouds that are sufficient for a quick exploration. Furthermore, the LIDAR scanner-based system can handle a relatively large office environment with an accumulated drift less than 0.02% (1 cm) on the Z-axis and 0.77% (50 cm) on the X and Y axes over a length trajectory of about 65 m. Despite the limited features of the sensor configuration of the Crazyflie, its performance is promising for mapping indoor spaces, given the relatively low deviation from the ground truth: cloud-to-cloud distances measured were generally less than 20 cm.
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