Dynamic object detection and static map reconstruction method of dynamic environment hybrid vision system

Abstract

The invention provides a dynamic object detection and static map reconstruction method of a dynamic environment hybrid vision system. The method comprises the steps that S1, conducting external parameter calibration to acquire coordinate transformation parameters between a panoramic camera and a three-dimensional laser sensor; S2, projecting the t-th frame of point cloud as a feature point to thet-th frame of image, obtaining a pixel motion vector of the feature point, and estimating an artificial motion vector of the feature point caused by the motion of the trolley to perform background motion compensation, thereby obtaining a dynamic point in the point cloud; S3, performing cluster segmentation on the point cloud of the current frame; S4, judging through the proportion of dynamic points in the cluster by utilizing the unique characteristic of each point index in the point cloud data and combining the dynamic point detection result and the segmentation result, and extracting a dynamic object; S5, reconstructing the static map by using an octree map tool and the laser radar odometer under the frame; Dynamic object extraction and static three-dimensional map reconstruction can beperformed robustly and more completely.

Description

technical field [0001] The invention relates to the technical field of dynamic object detection and three-dimensional map reconstruction, in particular to a method for dynamic object detection and static map reconstruction of a dynamic environment hybrid vision system. Background technique [0002] In recent years, robot technology has developed vigorously, and its application in positioning and navigation has become more and more extensive. Therefore, 3D map reconstruction technology has become one of the research hotspots in the field of computer vision. Although 3D maps in indoor or outdoor environments can be acquired by visual sensors such as depth cameras and LiDAR, 3D map reconstruction is still a challenging task due to the presence of moving objects in the mapped environment. Dynamic objects will leave a series of "traces" on the map, which will form undesirable features that will affect the robot's judgment of its own position and increase the difficulty of navigat...

AI Technical Summary

Problems solved by technology

When performing 3D map reconstruction outdoors, the capacity of the map will become larger and larger as time goes by, which is a great test for the performance of the computer, and a lot of redundant data will be left in the map; at the same time, the 3D point Cloud data cannot be directly applied to tasks such as path planning

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