研究目的
Investigating the effectiveness of a cost-effective and lightweight multi-sensor system for 3D modelling of UAV environments using 2D laser scanner and IMU data.
研究成果
The proposed system demonstrates good performance in real-time 3D modelling of indoor environments using a cost-effective and lightweight multi-sensor setup. Future work includes testing with other concurrent methods, incorporating additional sensor readings for more accurate 3D mapping and localization, and addressing IMU bias correction for long-term operations.
研究不足
The system's localization algorithm only determines two coordinates position and one angle of rotation (3DOF), limiting its application to scenarios where the laser scanner is aligned with the XY plane of the fixed coordinate frame. Additionally, the system's performance in long-term operations may be affected by IMU bias.
1：Experimental Design and Method Selection:
The system involves a UAV equipped with a 2D laser scanner and IMU for data acquisition, a single board computer (Odroid XU4) for data fusion, and a remote PC for 3D mapping and localization. The methodology includes the use of quaternions for orientation description, ICP algorithm for localization, and Octree-based algorithm for 3D mapping.
2：Sample Selection and Data Sources:
Data is acquired from a Sweep LiDAR laser scanner and IMU-BNO055 inertial sensor mounted on an octorotor UAV.
3：List of Experimental Equipment and Materials:
Sweep LiDAR laser scanner, IMU-BNO055, Odroid XU4 SBC, and a remote PC.
4：Experimental Procedures and Operational Workflow:
The laser scanner and IMU data are fused on the SBC under ROS, producing 3D points which are transmitted to the remote PC for localization and mapping.
5：Data Analysis Methods:
The ICP method is used for UAV localization, and the Octree-based algorithm is employed for incremental 3D mapping.
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