Semantic SLAM method and system based on object and plane features

An object and plane technology, applied in the field of computer vision, can solve problems such as lack of semantic information and poor SLAM optimization ability, and achieve the effects of enhanced semantic description, improved performance, and strong robustness

Active Publication Date: 2019-10-11
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

[0006] In view of the above defects or improvement needs of the prior art, the present invention provides a semantic SLAM method and syst...

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  • Semantic SLAM method and system based on object and plane features
  • Semantic SLAM method and system based on object and plane features
  • Semantic SLAM method and system based on object and plane features

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[0046] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0047] Such as figure 1 As shown, a semantic SLAM method based on object and plane features includes: RGB-D data as input needs to go through frame-by-frame tracking, local map construction, plane map construction, object map construction and back-end optimization. Finally, the robot semantic map construction and autonomous positioning tasks are completed. specifically:

[0048] (1) RGB-D data ...

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Abstract

The invention discloses a semantic SLAM method and system based on object and plane features, and belongs to the technical field of computer vision, and the method comprises the steps: obtaining the RGB-D image stream of a scene; performing frame-by-frame tracking on the RGB-D image stream to obtain a key frame image; constructing a local map about the scene by utilizing the key frame image; carrying out plane segmentation on the depth map of the key frame image to obtain a current plane, constructing a global plane map by utilizing the current plane, carrying out object detection on the key frame image to obtain a detection frame and confidence, reconstructing point cloud of an object by utilizing the detection frame and the confidence, and merging feature points in the detection frame into the object to obtain a global object map; and performing loop-back detection by using the key frame image to obtain a loop-back frame, and performing loop-back correction and optimization on the plane constraint and the object constraint by using the loop-back frame to obtain a plane map and an object map of the scene. According to the method, the SLAM optimization performance can be improved,and the semantic description of the environment is enhanced.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and more specifically relates to a semantic SLAM method and system based on object and plane features. Background technique [0002] Simultaneous localization and mapping (SLAM) is a popular research field in recent years. This technology is proposed for the positioning and mapping of robots in unknown environments. After a period of development, the main framework of the current visual SLAM technology has matured, mainly including visual odometer, back-end optimization, loop detection and other parts. [0003] The maps constructed by traditional SLAM technology are mostly composed of low-level geometric elements (points, lines, planes, etc.), which lack high-level semantic information while having a certain ability to describe the environment. When the robot needs to interact with objects in the environment during motion, we need to describe the semantic information of the environment. ...

Claims

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Application Information

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IPC IPC(8): G06T7/73G06T7/10G06T7/50G06F16/587
CPCG06T7/10G06T7/50G06T7/73G06F16/587
Inventor 陶文兵郑龙玉
Owner HUAZHONG UNIV OF SCI & TECH
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