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Semantic SLAM-based mobile robot automatic navigation and target recognition algorithm

A mobile robot and automatic navigation technology, which is applied in navigation computing tools, character and pattern recognition, machine learning, etc., can solve the problems of V-SLAM technology not being robust enough, achieve model generalization capability enhancement, ensure accuracy, and improve efficiency Effect

Inactive Publication Date: 2021-02-09
XUZHOU UNIV OF TECH
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  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

However, V-SLAM technology is still not robust enough for robot movement or challenging environments (e.g., fast robot dynamics, rapidly changing environments, severe lighting changes, strict visibility constraints or complex scenes with missing textures).

Method used

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  • Semantic SLAM-based mobile robot automatic navigation and target recognition algorithm
  • Semantic SLAM-based mobile robot automatic navigation and target recognition algorithm
  • Semantic SLAM-based mobile robot automatic navigation and target recognition algorithm

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Embodiment Construction

[0040] The present invention will be further described below.

[0041] like Figure 1 to Figure 4 Shown, the concrete steps of the present invention are:

[0042] S1. The autonomous mobile robot collects pictures of the surrounding environment through the camera in the workshop, and then performs preprocessing operations on the collected pictures to obtain picture data with strong generalization ability, consistent scale, and sufficient quantity; the quality of the initial picture determines the semantic features The degree of excellence and the accuracy of subsequent SLAM-related tasks further determine the efficiency and accuracy of autonomous mobile robot-related tasks. The specific steps of the preprocessing operation are:

[0043] S11. Image data enhancement, through which the image sample size is increased and the model generalization ability is enhanced;

[0044] S12, the image is randomly cropped, and the random cropping parameters are set to process, so as to reali...

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Abstract

The invention discloses a semantic SLAM-based mobile robot automatic navigation and target recognition algorithm. Semantic SLAM and a regional convolutional neural network are combined, acquired pictures are processed through the convolutional neural network on the basis of a semantic segmentation mechanism, so that a region where important feature data is located can be conveniently located in advance, unnecessary calculation is reduced, and the operation speed and performance are improved; and meanwhile, a deep residual error network structure is adopted, so that the problem of gradient disappearance is avoided, and the network training efficiency is improved. Therefore, the accuracy of automatic navigation and target recognition of the mobile robot can be ensured, the robustness in theautonomous navigation process and the target recognition process can be effectively improved, and finally, stable operation of the mobile robot is ensured.

Description

technical field [0001] The invention relates to an algorithm for automatic navigation and target recognition of a mobile robot, in particular to an algorithm for automatic navigation and target recognition of a mobile robot based on semantic SLAM. Background technique [0002] In the intelligent manufacturing or Internet of Things production platform, different types of robots or autonomous navigation vehicles work together efficiently, which has a greater impact on the degree of automation of intelligent generation and the efficiency of production cooperation. It is a measure of the Internet of Things and intelligent manufacturing process. Important parameters for information collaboration and efficient interconnection. In addition, the use of visual SLAM technology greatly simplifies a large amount of redundant sensor data, providing a solid hardware foundation for an efficient production platform. [0003] Semantic segmentation requires some special attention when it com...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/20G06K9/00G06K9/62G06N3/04G06N3/08G06N7/00G06N20/00
CPCG01C21/20G06N3/08G06N20/00G06V20/10G06N7/01G06N3/045G06F18/22G06F18/23
Inventor 卑璐璐黄凯
Owner XUZHOU UNIV OF TECH
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