Intelligent storage inventory method based on SLAM

An intelligent warehousing and sparse point technology, applied in logistics, instrumentation, mapping and navigation, etc., can solve the problems of difficult retrieval, untimely data update, inconvenient warehouse operation, etc., to save manpower and get rid of inefficiency and high costs.

Inactive Publication Date: 2020-09-15
HANGZHOU DIANZI UNIV
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  • Abstract
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Problems solved by technology

This management mode not only requires a lot of human resources, but also has low efficiency, and manual storage planning is not the best solution
And d

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  • Intelligent storage inventory method based on SLAM
  • Intelligent storage inventory method based on SLAM
  • Intelligent storage inventory method based on SLAM

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Embodiment Construction

[0027] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0028] Such as figure 1 As shown, the present invention is based on the fusion of visual SLAM and laser SLAM to obtain the 2D grid image for autonomous navigation of the robot. Do local navigation planning, complete target recognition and cargo barcode scanning.

[0029] Such as figure 2 As shown, it is a schematic diagram of the visual SLAM framework. The functional modules include five parts: data preprocessing, initialization, back-end nonlinear optimization, closed-loop detection and closed-loop optimization, and are processed concurrently by multiple threads. The main function of each functional module is introduced in detail as follows:

[0030] A) Image and IMU preprocessing, obtain the key frame in the image, use the matrix model RANSAC algorithm to remove abnormal points, and correct the distortion of the feature points, and finall...

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Abstract

The invention discloses an intelligent storage inventory method based on SLAM, and the method employs a visual SLAM and laser SLAM fusion method, and enables a storage robot to achieve the autonomousnavigation and positioning and to efficiently complete the operation. The visual SLAM processes image information acquired by a camera to generate 3D sparse point cloud, and generates a 2D grid map through projection. Then, the laser SLAM is fused to improve the observation area, robustness and fault tolerance of the whole map. Laser radar obtains a surrounding environment distance value, and a local map is constructed through laser SLAM particle filtering and a Gmapping algorithm. The grid map and the local map are enabled to be mutually filled to achieve global mapping; a Dijkstra algorithmis adopted for global navigation of coordinates and end point coordinates, and a DWA algorithm is adopted in a local area for planning a local optimal path, so that the robot accurately reaches a destination and performs target recognition through a trained network to complete detection, and high efficiency and accuracy are ensured.

Description

technical field [0001] The invention belongs to the field of computer vision and mobile robot navigation, and relates to an intelligent warehouse inventory method based on SLAM. Background technique [0002] Simultaneous Localization and Mapping (SLAM) is an important research field for autonomous robot navigation. The robot builds a map of the environment while moving in an unfamiliar environment through the sensors on board, and can plan its own movement based on the generated map. SLAM technology enables the robot to plan the shortest path to complete the inventory while avoiding obstacles in real time after obtaining the map. [0003] At present, the warehouse inventory in the market is mainly through the manual way to register, store, inventory and deliver the goods. This management mode not only requires huge human resources, but also has low efficiency, and manual storage planning is not the best solution. And due to the untimely data update, information loss and r...

Claims

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Application Information

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IPC IPC(8): G01C21/16G01C21/00G06Q10/08
CPCG01C21/165G01C21/005G06Q10/087
Inventor 闫泽昊胡莉英孙玲玲李郑慧王煜聪
Owner HANGZHOU DIANZI UNIV
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