关键词: 数据融合, 无人系统, 流水线, 感知数据, 人工智能

Abstract: Sensors are the basis for unmanned systems to perform intelligent actions. The fusion of multi-sensor data can enhance intelligent perception and autonomous decision-making capabilities of unmanned systems, and improve their reliability and robustness. Data fusion of unmanned systems encounters many challenges such as diverse sensor types, heterogeneous data formats, real-time fusion needs, analysis of varied and complex data, fast evolving models. Traditional methods of developing fusion models through customization on edge equipment and approaches based on fusion platform running on cloud devices are difficult to apply in these cases. To address these problems, the paper proposes a data pipeline platform for data fusion of intelligent sensors on un-manned systems. The architecture has capabilities to support automatic data transformation, seamless algorithm integration, dynamic model configuration, and agile service evolution to achieve quick response to different tasks. Based on the analysis of data fusion process and techniques, it characterizes the key components and functions of the proposed pipeline architecture, discusses relevant significant technologies, gives its running way and actual case, and points out research directions for future development.

Key words: data fusion, unmanned systems, pipeline, sensing data, machine learning