A multi-sensor fusion-based environment perception and three-dimensional mapping method and device

Abstract

This application relates to a method and device for environmental perception and 3D mapping based on multi-sensor fusion. The device performs unified time synchronization and spatial calibration on multi-source perception data acquired by LiDAR, inertial measurement unit, image acquisition unit, and satellite navigation system. It then performs multi-sensor data fusion processing on the main control computing platform to obtain temporally and spatially consistent environmental perception information, achieving high-precision positioning and 3D environmental mapping for the device itself. Specifically, the time synchronization module uniformly triggers or aligns timestamps during the multi-sensor data acquisition process, and determines the spatial pose relationships between the sensors through extrinsic parameter calibration. During device movement, LiDAR acquires 3D point cloud data of the environment, and combines this with motion constraints provided by the inertial measurement unit, visual information acquired by the image acquisition unit, and absolute position information provided by the satellite navigation system to construct a device motion model and an observation model. A fusion algorithm is used to jointly optimize the multi-source sensor data to obtain the optimal pose estimation results of the platform at each moment, and the environmental spatial information is cumulatively updated to gradually construct a 3D environmental map. Based on the fusion and mapping results, a three-dimensional reconstruction and visualization of the surrounding environment structure is achieved, and a modular mechanical structure provides reliable support for the mobile platform's environmental perception, positioning, and spatial understanding.

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