Research on Unmanned Surface Vehicles Environment Perception Based on the Fusion of Vision and Lidar

The research of unmanned surface vehicles (usually called USV) is becoming a research hotspot, and real-time and accurate environmental perception is the key technology for achieving autonomous navigation and completing tasks of USV. In this paper, aiming at the technical problems of environmental perception of the USV, from the perspective of sensor multi-information fusion, we build a complete USV perception system (hardware platform and software system). This paper mainly studies objects on the water detection and obstacle avoidance methods based on the information fusion of lidar and vision. In addition, we also studies the method based on morphology to process the reflection of the objects on the water, and the sea-sky detection based on support vector machine (SVM) to assist the objects on the water detection. Through the construction of the USV environment perception system, improving the ability of USV environment perception, and ensuring the safety of autonomous navigation of USV. Our proposed methods have been tested by simulation experiments and actual marine experiment as well as the Hawaii Unmanned Surface Vehicles Challenge, which proves the practicability and stability of our method in the actual environment.