Scene self-adaptive method for controlling unmanned driving of monorail hoist transportation robot

Patent metadata

Field	Value
Publication number	US-12428271-B2
Application number	US-202318840913-A
Country	US
Kind code	B2
Filing date	Aug 3, 2023
Priority date	Dec 21, 2022
Publication date	Sep 30, 2025
Grant date	Sep 30, 2025

Abstract

The present disclosure discloses a scene self-adaptive method for controlling an unmanned driving of a monorail hoist transportation robot. The method comprises the following steps: constructing an industrial internet of things platform for a monorail hoist; constructing a digital twin system for the monorail hoist; controlling a virtual unmanned driving of the monorail hoist; establishing a shadow following model for the monorail hoist; controlling an entity monorail hoist in real time by a virtual monorail hoist; comparing the entity monorail hoist driven by data with the monorail hoist driven by a driver with the shadow following mode; and designing a self-adaptive program for complex scenes: improving a loading velocity of a new roadway scene through merging root nodes and compressing data, implementing an environment self-adaptation, a platform self-adaptation, and a terminal self-adaptation.

First claim

What is claimed is:

1. A scene self-adaptive method for controlling an unmanned driving of a monorail hoist transportation robot, comprising following steps:
S1, constructing an industrial internet of things platform for a monorail hoist, wherein the industrial internet of things platform comprises a cloud server and a client device, the client device is in communication connection with the cloud server by using a network communication, the client device uses a sensor to acquire data and transmits the data to the cloud server for storage;
S2, constructing a digital twin corresponding an entity monorail hoist as a virtual monorail hoist;
S3, establishing a virtual unmanned driving control model to control driving of the virtual monorail hoist in a virtual scene, wherein when the driving of the virtual monorail hoist in the virtual scene is detected to be abnormal, point cloud data and a scene image of a current driving road of the virtual monorail hoist are acquired, and artificial intelligence training of the virtual unmanned driving control model is performed;
S4, establishing a program for executing a shadow mode in the virtual monorail hoist, and comparing an output instruction of the program with an output instruction of the entity monorail hoist;
S5, controlling the entity monorail hoist in real time by the virtual monorail hoist, wherein a data transmission and a state synchronization between the virtual monorail hoist and the entity monorail hoist through OPC UA (Open Platform Communications Unified Architecture) communication protocol;
S6, comparing the entity monorail hoist driven by data and the entity monorail hoist driven by a person driver with the shadow mode; and
S7, designing a self-adaptive program for complex scenes comprising establishing segmented tiles and the LOD (Level of Detail) loading module for real-scene three-dimensional scene data and performing data compression on the real-scene three-dimensional scene data.

2. The scene self-adaptive method for controlling the unmanned driving of the monorail hoist transportation robot according to claim 1 , wherein in step S1, an ARM processor is served as a control module, and a camera module is served as an acquisition device for data acquisition; driving data for the entity monorail hoist are obtained by utilizing a millimeter-wave laser radar and a multi-sensor fusion; special operating conditions are recorded based on production data for mines; a WIFI technology is served as a network communication technology for implementing a wireless communication; a data processing server, a database server and a Web server are served as cloud servers, and eventually the data are displayed on a display terminal.

3. The scene self-adaptive method for controlling the unmanned driving of the monorail hoist transportation robot according to claim 2 , wherein in step S2, the digital twin corresponding to the entity monorail hoist is constructed layer by layer, a physical layer, a virtual layer, a perception layer and a shared layer are sequentially established to further establish an operation and control model for the monorail hoist, and the client device is in communication connection with the cloud server by utilizing a WIFI or a Socket to establish a digital twin system for the monorail hoist.

4. The scene self-adaptive method for controlling the unmanned driving of the monorail hoist transportation robot according to claim 3 , wherein in step S3, a virtual laser radar is constructed, and the point cloud data for the roadway are acquired; a virtual vision camera is constructed to acquire real-time scene image data for the roadway to perform a controlled driving training, a path following training, and a A*pathfinding algorithm optimization.

5. The scene self-adaptive method for controlling the unmanned driving of the monorail hoist transportation robot according to claim 4 , wherein in step S4, an ADAS (Advanced Driver Assistance Systems) hardware is pre-embedded for the entity monorail hoist, differences between the output instruction of the program and the output instruction of the entity monorail hoist are compared to implement a basic function of the shadow mode.

6. The scene self-adaptive method for controlling the unmanned driving of the monorail hoist transportation robot according to claim 5 , wherein in step S5, in a data transmission system, a PLC is taken as a core, and a data information interaction is performed through a servo drive, a sensor, a touch screen and the entity monorail hoist.

7. The scene self-adaptive method for controlling the unmanned driving of the monorail hoist transportation robot according to claim 6 , wherein in step S6, an input instruction a driving of the entity monorail hoist is compared with an output instruction of the shadow mode, when an instruction difference does not satisfy an accuracy requirement of the unmanned driving, the virtual unmanned driving control model is retrained.

8. The scene self-adaptive method for controlling the unmanned driving of the monorail hoist transportation robot according to claim 7 , wherein in step S7, a scene loading program is pre-processed in a designing of a program, optimization operations of root nodes and data compression are performed on real-scene three-dimensional scene data.

Assignees

• Univ China Mining
• Xuzhou Liren Monorail Transp Equipment Co Ltd

Inventors

• Lu Hao
• Zhu Zhencai
• Peng Yuxing
• Du Mai
• Jiang Hongxiang
• Wang Qingguo

Classifications

• B66C15/00

  Safety gear (for rope, cable, or chain winding mechanisms B66D1/54) · CPC title

• B66C13/46 Primary

  Position indicators for suspended loads or for crane elements · CPC title

• B66C13/48 Primary

  Automatic control of crane drives for producing a single or repeated working cycle; Program control · CPC title

• Y02P90/02

  Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS] · CPC title

• G06F30/20

  Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30) · CPC title