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Point cloud map construction method and device, equipment and storage medium

A map construction and point cloud technology, applied in the field of point cloud maps, can solve the problems of tailing and poor map rendering effect, and achieve the effect of avoiding tailing

Pending Publication Date: 2020-07-10
BEIJING JINGDONG 360 DEGREE E COMMERCE CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

When the movable object is in a moving state, using the existing mapping method to construct a scene with dynamic objects will cause tailing phenomenon, resulting in poor presentation of the constructed map

Method used

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  • Point cloud map construction method and device, equipment and storage medium
  • Point cloud map construction method and device, equipment and storage medium
  • Point cloud map construction method and device, equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0031] figure 1 It is a flow chart of a point cloud map construction method provided by Embodiment 1 of the present invention. This embodiment is applicable to mapping scenarios such as city simulation and high-precision map construction. The purpose is to realize mapping of static scenes based on point clouds. At the same time, the trailing phenomenon caused by the temporarily existing dynamic objects in the static scene is eliminated, and the dynamic objects refer to objects that keep moving. The static scene specifically refers to a scene that does not include movable objects, and the movable objects refer to objects that have motion attributes but do not necessarily move, such as pedestrians and vehicles. The specific movable object is an object customized according to the application scenario. For example, in the high-precision map production industry, pedestrians, buses, cars, and bicycles in the street view scene can all be defined as movable objects; in the indoor scen...

Embodiment 2

[0058] image 3 It is a flowchart of a point cloud map construction method provided by Embodiment 2 of the present invention. On the basis of the above embodiments, this embodiment provides the segmentation results of the same instance under multiple continuous single-frame point clouds, and the same The process of determining the state of the instance in each single-frame point cloud realizes the accurate determination of the state of the instance, and provides a reliable basis for determining the target patching algorithm. The explanations of terms that are the same as or corresponding to those in the foregoing embodiments are not repeated here.

[0059] see image 3 The point cloud map construction method provided in this embodiment specifically includes the following steps:

[0060] Step 310 , for multiple consecutive single-frame point clouds of the scene to be mapped, perform instance segmentation based on the current single-frame point cloud, and obtain an instance se...

Embodiment 3

[0118] Figure 4 It is a flowchart of a method for constructing a point cloud map provided by Embodiment 3 of the present invention. This embodiment is further optimized on the basis of the foregoing embodiments. Specifically: if hole patching is only performed in the world coordinate system, whether using the multi-view projection patching algorithm or the deep learning patching algorithm for patching, the patching results are often dense and uneven, because the multi-view projection patching algorithm will combine all neighbors All the relevant point cloud points in a single frame point cloud are projected into the convex bounding box, and the deep learning patching algorithm has a probabilistic deviation, so the point cloud points in the patched hole area are dense and uneven, and the visual effect is poor. In view of this problem, this embodiment further provides a solution for performing point cloud thinning on the patched hole area. The explanations of terms that are th...

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Abstract

The embodiment of the invention discloses a point cloud map construction method and device, equipment and a storage medium, and the method comprises the steps: carrying out the instance segmentation of a plurality of continuous single-frame point clouds of a to-be-constructed scene based on a current single-frame point cloud, and obtaining an instance segmentation result of the current single-frame point cloud; according to the instance segmentation result of the current single-frame point cloud, removing point cloud points belonging to instances in the current single-frame point cloud to obtain a removed current single-frame point cloud, wherein the example includes a movable object; projecting each removed single-frame point cloud to a world coordinate system for map reconstruction to obtain a first intermediate map of the scene to be mapped; and performing hole repair on the first intermediate map according to the state of each instance to obtain a first target map of the to-be-mapped scene, wherein the state includes a static state and a motion state. Through the technical scheme of the embodiment of the invention, the mapping effect of only the immovable object based on the point cloud is realized, and the trailing phenomenon caused by the dynamic object is avoided.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of point cloud maps, and in particular, to a point cloud map construction method, device, device, and storage medium. Background technique [0002] In industries such as autonomous driving, high-precision map making, and robot navigation, SLAM (Simultaneous Localization and Mapping, simultaneous positioning and mapping) has always been a research hotspot and difficulty. [0003] However, in the course of realizing the present invention, the inventor finds that there are at least the following problems in the prior art: [0004] Most of the mapping methods assume that the scene that needs to be mapped is a static scene that only includes immovable objects, that is, the scene that needs to be mapped does not include movable objects, such as pedestrians and vehicles. However, in applications such as urban simulation and high-definition maps, the scenes that need to be mapped often include...

Claims

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Application Information

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IPC IPC(8): G06T17/05G06T7/10G06T5/00G06T3/00G06T7/246
CPCG06T17/05G06T7/10G06T7/246G06T2207/10028G06T2207/10016G06T3/08G06T5/77
Inventor 李艳丽贾魁
Owner BEIJING JINGDONG 360 DEGREE E COMMERCE CO LTD