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Robot semantic SLAM method based on object instance matching, processor and robot

A technology for robots and objects, applied in the field of robot navigation, can solve problems such as individuals who cannot distinguish objects, and achieve the effect of improving positioning accuracy

Inactive Publication Date: 2019-05-28
SHANDONG UNIV
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Problems solved by technology

However, the inventor found that most of the current research work on semantic SLAM requires known 3D models as prior knowledge, or only performs semantic segmentation on a limited number of object categories and cannot distinguish objects.

Method used

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  • Robot semantic SLAM method based on object instance matching, processor and robot

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Embodiment Construction

[0049] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

[0050] It should be noted that the terminology used herein is only for describing specific embodiments, and is not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

[0051] Explanation of terms:

[0052] (1) ORB: Oriented FAST and Rotated BRIEF algorithm is currently the fastest and most sta...

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Abstract

The invention provides a robot semantic SLAM method based on object instance matching, a processor and a robot. The robot semantic SLAM method comprises the steps that acquring an image sequence shotin the operation process of a robot, and conducting feature point extraction, matching and tracking on each frame of image to estimate camera motion; extracting a key frame, performing instance segmentation on the key frame, and obtaining all object instances in each frame of key frame; carrying out feature point extraction on the key frame and calculating feature point descriptors, carrying outfeature extraction and coding on all object instances in the key frame to calculate feature description vectors of the instances, and obtaining instance three-dimensional point clouds at the same time; carrying out feature point matching and instance matching on the feature points and the object instances between the adjacent key frames; and performing local nonlinear optimization on the pose estimation result of the SLAM by fusing the feature point matching and the instance matching to obtain a key frame carrying object instance semantic annotation information, and mapping the key frame intothe instance three-dimensional point cloud to construct a three-dimensional semantic map.

Description

technical field [0001] The disclosure belongs to the technical field of robot navigation, and in particular relates to a robot semantic SLAM method based on object instance matching, a processor and a robot. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] In the field of robot navigation, Simultaneous Localization and Mapping (SLAM) refers to: the robot starts from an unknown location in an unknown environment, locates its own position and posture by repeatedly observing the environmental characteristics during the movement, and then according to its own position At the same time, the location and map construction can be achieved at the same time. The purpose of SLAM technology is mainly to solve the two problems of positioning and map construction. Since it was proposed, it has quickly attracted the attention and research of many schola...

Claims

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Application Information

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IPC IPC(8): G06T7/207G06T7/215G06T7/70G06N3/04
Inventor 吴皓迟金鑫马庆焦梦林
Owner SHANDONG UNIV
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