Indoor SLAM mapping method and system based on semantic information fusion

A semantic information and semantic map technology, applied in control/regulation systems, two-dimensional position/channel control, instruments, etc., can solve problems such as high complexity and inability to judge

Active Publication Date: 2020-09-15
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For outdoor positioning and navigation, GPS can be considered. However, for indoor environments, d

Method used

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  • Indoor SLAM mapping method and system based on semantic information fusion
  • Indoor SLAM mapping method and system based on semantic information fusion
  • Indoor SLAM mapping method and system based on semantic information fusion

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0036] figure 1 A schematic diagram of the indoor SLAM mapping method based on semantic information fusion of this embodiment is given.

[0037] Such as figure 1 As shown, the indoor SLAM mapping method based on semantic information fusion of this embodiment includes:

[0038] S101: Construct a planar grid map of the indoor environment based on the lidar information.

[0039] In the specific implementation, the Gmapping laser SLAM algorithm based on particle filter is used to construct the planar grid map of the indoor environment. The Gmapping algorithm is based on the filter SLAM framework and integrates the Rao-Blackwellized particle filter algorithm to separate the positioning from the mapping process. In small scenes, the calculation amount is small, the accuracy is high, and the robustness is high. At the same time, the frequency requirement of lidar is low.

[0040] The Gmapping algorithm introduces the RBpf algorithm to separate the two processes of positioning an...

Embodiment 2

[0114] Such as Figure 7 As shown, the indoor SLAM mapping system based on semantic information fusion of this embodiment includes:

[0115] (1) A planar grid map construction module, which is used to construct a planar grid map of an indoor environment based on lidar information.

[0116] In the specific implementation, the Gmapping laser SLAM algorithm based on particle filter is used to construct the planar grid map of the indoor environment. The Gmapping algorithm is based on the filter SLAM framework and integrates the Rao-Blackwellized particle filter algorithm to separate the positioning from the mapping process. In small scenes, the calculation amount is small, the accuracy is high, and the robustness is high. At the same time, the frequency requirement of lidar is low.

[0117] (2) A three-dimensional bounding box calculation module, which is used to obtain three-dimensional point cloud information of the indoor environment and category semantic labels, spatial pos...

Embodiment 3

[0134] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps in the indoor SLAM mapping method based on semantic information fusion as described in Embodiment 1 are implemented.

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Abstract

The invention belongs to the field of indoor map construction, and provides an indoor SLAM mapping method and system based on semantic information fusion. The indoor SLAM mapping method based on semantic information fusion comprises the following steps: constructing an indoor environment planar grid map based on laser radar information; acquiring three-dimensional point cloud information of an indoor environment and category semantic tags, spatial positions and sizes of objects existing in the indoor environment, and calculating three-dimensional bounding boxes of all space objects; and projecting the bounding boxes of all the space objects to the planar grid map to construct an indoor SLAM semantic map.

Description

technical field [0001] The invention belongs to the field of indoor map construction, and in particular relates to an indoor SLAM map construction method and system based on semantic information fusion. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] With the gradual development and improvement of robot technology, robots are gradually changing from doing heavy work at the beginning to being able to achieve some goal requirements autonomously and intelligently. People expect robots to have the ability to analyze the surrounding environment. Cognitively and autonomously make decisions to accomplish required tasks. To achieve such a requirement, it is hoped that the robot can firstly identify the surrounding environment, and establish a map model of the surrounding environment, and then locate the position of the robot and plan the path of ...

Claims

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Application Information

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IPC IPC(8): G05D1/02
CPCG05D1/0221G05D1/0223G05D1/024G05D1/0242G05D1/0251G05D1/0257G05D1/0276G05D1/028
Inventor 周风余顾潘龙万方于帮国庄文秘杨志勇
Owner SHANDONG UNIV
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