Abstract
AbstractAutonomous obstacle detection technology is the premise to realize autonomous navigation in the Marine environment. The fusion sensing of multi-modal sensors can improve the accuracy and stability of obstacle detection. In this paper, on the premise of analyzing and comparing the performance of sensors, two sensors with different modes are selected to be used, specifically, LIDAR sensor and vision sensor. The system selects the unmanned vehicle open source framework MOOS as the development framework, and realizes the real-time reading of webcam video stream through RTSP and multi-threading. At the same time, the real-time data acquisition of LIDAR is realized through UDP communication and multi-threading architecture. Finally, a set of multi-modal data real-time acquisition system is developed. It has the characteristics of high localization rate, low cost, easy expansion and stable performance, which lays a foundation for the subsequent research on multi-modal data fusion technology.KeywordsUSVMOOSMulti-modal sensorMulti-threading architecture
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