Three-Dimensional Geometric-Physical Modeling of an Environment with an In-House-Developed Multi-Sensor Robotic System

Abstract

Environment 3D modeling is critical for the development of future intelligent unmanned systems. This paper proposes a multi-sensor robotic system for environmental geometric-physical modeling and the corresponding data processing methods. The system is primarily equipped with a millimeter-wave cascaded radar and a multispectral camera to acquire the electromagnetic characteristics and material categories of the target environment and simultaneously employs light detection and ranging (LiDAR) and an optical camera to achieve a three-dimensional spatial reconstruction of the environment. Specifically, the millimeter-wave radar sensor adopts a multiple input multiple output (MIMO) array and obtains 3D synthetic aperture radar images through 1D mechanical scanning perpendicular to the array, thereby capturing the electromagnetic properties of the environment. The multispectral camera, equipped with nine channels, provides rich spectral information for material identification and clustering. Additionally, LiDAR is used to obtain a 3D point cloud, combined with the RGB images captured by the optical camera, enabling the construction of a three-dimensional geometric model. By fusing the data from four sensors, a comprehensive geometric-physical model of the environment can be constructed. Experiments conducted in indoor environments demonstrated excellent spatial-geometric-physical reconstruction results. This system can play an important role in various applications, such as environment modeling and planning.

Keywords

• multi-sensor fusion
• 3D geometric-physical modeling
• intelligent unmanned system
• millimeter-wave cascaded radar
• multispectral camera