Unmanned ship water surface target detection, identification and positioning method based on monocular camera and lidar information fusion

Abstract

The invention belongs to the field of intelligent unmanned intelligent ships, and relates to an unmanned ship water surface target detection, identification and positioning method based on monocular camera and lidar information fusion. The detection, identification and positioning of a water surface target by an unmanned ship are influenced by distances and the fluctuation of the target, so that alidar and a monocular camera are integrated to accurately detect, identify and position the target within a sensing range. According to the method, acquired water surface target images are adopted totrain a neural network-based target detection and recognition model; the lidar employs a conditional removal filter and Euclidean clustering to obtain the position of the water surface target in a world coordinate system; and finally, a camera image information and lidar information fusion method is designed, and therefore, the method is highly robust to uncertain factors. With the method adopted, the unmanned ship is capable of accurately detecting, identifying and positioning the water surface target; and good environment perception can be realized for the target tracking, path planning andautonomous navigation of the unmanned ship. The method has a broad application prospect.

Description

technical field [0001] The invention belongs to the field of intelligent unmanned smart ships, and in particular relates to a method for detecting, identifying and locating unmanned water surface targets based on fusion of monocular camera and laser radar information. Background technique [0002] The unmanned boat is an intelligent platform for navigating on the water surface. Since the water surface environment in which the unmanned boat is located is very complex, it is very important for the unmanned boat to perceive the surrounding environment information. Therefore, how to improve the ability of unmanned vehicles to perceive the environment is a research hotspot. In the existing literature, many scholars have studied the environment perception of unmanned vehicles by means of visual perception, radar perception and multi-sensor perception information fusion. However, these methods have certain limitations, and their adaptability to the environment is low. [0003] Ma ...

AI Technical Summary

Problems solved by technology

However, its algorithm for processing radar data based on the relationship between speed and relative position cannot detect objects such as stationary vehicles, and its fusion algorithm has poor calculation accuracy when there are multiple objects in front

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