Hardware-based LiDAR and imaging fusion sensing system

The fusion of LiDAR and multispectral image data is critical for enhancing the performance of intelligent unmanned systems. Current fusion approaches, such as early fusion, deep fusion, and late fusion, are typically implemented at the data level. However, due to the independent operation of LiDAR and imaging sensors, these approaches often require complex algorithms for spatial alignment and temporal synchronization. To address these challenges in multi-source data fusion, we propose a novel hardware-based fusion sensing system that integrates LiDAR and multispectral imaging. The system adopts a common-path optical configuration to ensure spatial alignment between LiDAR point clouds and imaging data, while dedicated hardware circuitry enables precise temporal synchronization between the two sensing modalities. Outdoor field experiments verify that the proposed system achieves high-quality fusion of LiDAR point clouds and multispectral imagery, thereby confirming the effectiveness of the hardware-based fusion sensing approach and underscoring its potential for future applications in intelligent unmanned systems.