CN-122015889-A - Long-period digital map updating method and system applied to unmanned forklift

CN122015889ACN 122015889 ACN122015889 ACN 122015889ACN-122015889-A

Abstract

The invention provides a long-period digital map updating method and a system applied to an unmanned forklift, and relates to the field of digital maps. The method comprises the steps of determining size parameters of a carriage through a mobile base station on an unmanned forklift and a plurality of positioning labels on the carriage, loading an initial temporary map corresponding to the carriage based on the size parameters and a historical temporary map of the carriage, determining scanning auxiliary information corresponding to the carriage based on the size parameters and the historical temporary map of the carriage, collecting internal point cloud data of the carriage through a point cloud collecting device on the unmanned forklift, constructing a temporary map corresponding to the carriage, executing a loading task, completing the loading task, returning to the initial position, deleting the temporary map corresponding to the carriage, reloading a fixed map of a warehouse, and improving the positioning capability and the operation efficiency of the unmanned forklift in a complex and changeable environment.

Inventors

LI YAN
ZHANG JIE
CHEN XIAOGANG
HUANG JI
TIAN MIAO

Assignees

四川联众供应链服务有限公司
泸州骐骊智能系统技术有限公司

Dates

Publication Date: 20260512
Application Date: 20260128

Claims (10)

1. The long-period digital map updating method applied to the unmanned forklift is characterized by comprising the following steps of: receiving a loading task from a warehouse to a carriage; Loading a fixed map of a warehouse, and acquiring the real-time position of the unmanned forklift until the unmanned forklift moves to an initial position corresponding to a carriage loading task; Determining the size parameter of a carriage through a mobile base station on the unmanned forklift and a plurality of positioning labels on the carriage; loading an initial temporary map corresponding to the carriage based on the size parameter and the historical temporary map of the carriage; determining scanning auxiliary information corresponding to the carriage based on the size parameter of the carriage and the historical temporary map; acquiring internal point cloud data of the carriage through a point cloud acquisition device on the unmanned forklift based on scanning auxiliary information corresponding to the carriage; Constructing a temporary map corresponding to the carriage based on the initial temporary map corresponding to the carriage and the internal point cloud data, and executing a loading task; and after the unmanned forklift completes the loading task and returns to the initial position, deleting the temporary map corresponding to the carriage, and reloading the fixed map of the warehouse.
2. The method for updating a long-period digital map applied to an unmanned forklift according to claim 1, wherein the plurality of positioning tags on the carriage at least comprise a first positioning tag, a second positioning tag, a third positioning tag and a fourth positioning tag which are respectively arranged at four corners of a door of the carriage, and further comprise a fifth positioning tag which is arranged along a depth direction of the carriage, wherein a straight line distance between the fifth positioning tag and one of the first positioning tag, the second positioning tag, the third positioning tag and the fourth positioning tag is the depth of the carriage.
3. The method for updating a long-period digital map applied to an unmanned forklift according to claim 2, wherein determining the size parameter of the car by the mobile base station on the unmanned forklift and the positioning tag on the car comprises: Determining a plurality of key location points; For each key position point, acquiring the characteristics of interaction signals of a mobile base station on the unmanned forklift and a plurality of positioning labels on a carriage; and determining the size parameter of the carriage based on the characteristics of the interaction signals of the mobile base station on the unmanned forklift and the plurality of positioning tags on the carriage corresponding to each key position point.
4. The method for updating a long-period digital map for use with an unmanned forklift of claim 3, wherein determining a plurality of key location points comprises: Randomly sampling a plurality of position points; For each position point, acquiring the characteristics of interaction signals of a mobile base station on the unmanned forklift and a plurality of positioning labels on a plurality of test carriages, wherein the size parameters of any two test carriages are different; for each position point, calculating a response difference value of the position point based on the characteristics of interaction signals of a mobile base station on the unmanned forklift and a plurality of positioning labels on a plurality of test carriages; a plurality of key location points are determined based on the response difference value of each location point by a genetic algorithm.
5. The method for updating a long-period digital map applied to an unmanned forklift according to claim 4, wherein the characteristics of the interaction signals of the mobile base station on the unmanned forklift and the plurality of positioning tags on the carriage at least include the intensities of the interaction signals of the mobile base station on the unmanned forklift and the first positioning tag, the second positioning tag, the third positioning tag, the fourth positioning tag and the fifth positioning tag, respectively: Based on the characteristics of the interaction signals of the mobile base station on the unmanned forklift and the plurality of positioning tags on the carriage corresponding to each key position point, determining the size parameter of the carriage comprises the following steps: Constructing a size determination model based on the characteristics of interaction signals of a mobile base station on the unmanned forklift and a plurality of positioning labels on a plurality of test carriages corresponding to each key position point; And determining the size parameter of the carriage based on the characteristics of the interaction signals of the mobile base station on the unmanned forklift and the plurality of positioning labels on the carriage corresponding to each key position point through a size determination model.
6. The method for updating a long-period digital map applied to an unmanned forklift according to any one of claims 1 to 5, wherein loading an initial temporary map corresponding to a car based on a size parameter of the car and a history temporary map comprises: Screening a plurality of matched historical temporary maps based on the size parameters of the carriage and the size parameters corresponding to the historical temporary maps; and loading an initial temporary map corresponding to the carriage based on the time attenuation coefficients of the plurality of matched historical temporary maps.
7. The method for updating a long-period digital map applied to an unmanned forklift according to claim 6, wherein loading the initial temporary map corresponding to the car based on the time attenuation coefficients of the plurality of matched historical temporary maps comprises: For each matched historical temporary map, calculating the similarity of the matched historical temporary map and other matched historical temporary maps, and calculating the comprehensive priority value of the matched historical temporary map based on the similarity of the matched historical temporary map and other matched historical temporary maps and the time attenuation coefficient of the other matched historical temporary maps; and loading an initial temporary map corresponding to the carriage based on the comprehensive priority value of each matched historical temporary map.
8. The method for updating a long-period digital map applied to an unmanned forklift according to claim 6, wherein determining the scanning assistance information corresponding to the vehicle based on the size parameter of the vehicle and the history temporary map comprises: Dividing a carriage into a plurality of subareas based on a plurality of matched historical temporary maps, and determining the scanning weight of each subarea; And determining the scanning auxiliary information corresponding to the carriage based on the scanning weight of each sub-region, wherein the scanning auxiliary information corresponding to the carriage comprises the scanning parameters of each sub-region.
9. The method for updating the long-period digital map applied to the unmanned forklift according to claim 8, wherein constructing the temporary map corresponding to the carriage based on the initial temporary map corresponding to the carriage and the internal point cloud data comprises: For each sub-area, extracting first point cloud data of the sub-area from an initial temporary map corresponding to the carriage, extracting second point cloud data of the sub-area from the internal point cloud data, calculating the matching degree of the first point cloud data and the second point cloud data of the sub-area, updating the initial temporary map corresponding to the carriage based on the matching degree of the first point cloud data and the second point cloud data of the sub-area, and constructing a temporary map corresponding to the carriage.
10. The long-period digital map updating system applied to the unmanned forklift truck is characterized in that the long-period digital map updating method applied to the unmanned forklift truck according to claim 1 comprises the following steps: the task receiving module is used for receiving a loading task from the warehouse to the carriage; The map loading module is used for loading a fixed map of the warehouse and acquiring the real-time position of the unmanned forklift until the unmanned forklift moves to an initial position corresponding to a carriage loading task; the size pre-judging module is used for determining size parameters of the carriage through a mobile base station on the unmanned forklift and a plurality of positioning labels on the carriage; The map loading module is also used for loading an initial temporary map corresponding to the carriage based on the size parameter and the historical temporary map of the carriage; The point cloud acquisition module is used for determining scanning auxiliary information corresponding to the carriage based on the size parameter and the historical temporary map of the carriage and acquiring internal point cloud data of the carriage through a point cloud acquisition device on the unmanned forklift based on the scanning auxiliary information corresponding to the carriage; the map loading module is also used for constructing a temporary map corresponding to the carriage based on the initial temporary map corresponding to the carriage and the internal point cloud data and executing a loading task; The map loading module is also used for completing a loading task by the unmanned forklift, deleting a temporary map corresponding to the carriage after returning to the initial position, and reloading a fixed map of the warehouse.

Description

Long-period digital map updating method and system applied to unmanned forklift Technical Field The invention relates to the field of digital maps, in particular to a long-period digital map updating method and system applied to an unmanned forklift. Background In the field of intelligent logistics, an unmanned forklift is used as key equipment for automatic operation, and currently, positioning navigation is realized under a fixed scene mainly by means of a map drawn in advance so as to finish tasks such as material handling. However, with the rapid development of intelligent warehouse logistics, higher requirements are put forward on the operation capability of the unmanned forklift, and the unmanned forklift needs to be accurately positioned in a dynamically-changing complex scene so as to adapt to the diversified and flexible operation requirements of the end-to-end warehouse logistics. The unmanned forklift is used for conveying goods into the boxcar for automatic loading, and is an extremely important and challenging operation scene. As the cabin size varies significantly from truck to truck, the internal configuration varies as well, which places the work environment in a constantly changing state. In the existing positioning technology, positioning operation can only be performed on a preloaded fixed map. Once the operation scene changes, for example, the operation scene enters into the boxcars with different sizes and structures, the position of the unmanned forklift cannot be accurately obtained by a positioning algorithm due to lack of updated map information matched with the operation scene, and further the unmanned forklift is difficult to guide to complete the operation tasks such as automatic loading and the like. The limitation severely restricts the application range and the operation efficiency of the unmanned forklift in a changing scene, and cannot meet the high requirements on the flexibility and the adaptability of the automatic equipment under the rapid development of intelligent warehouse logistics. Therefore, it is necessary to provide a method and a system for updating a long-period digital map applied to an unmanned forklift, which are used for improving the positioning capability and the operation efficiency of the unmanned forklift in a complex and changeable environment. Disclosure of Invention The invention provides a long-period digital map updating method applied to an unmanned forklift, which comprises the steps of receiving a loading task from a warehouse to a carriage, loading a fixed map of the warehouse, acquiring the real-time position of the unmanned forklift until the unmanned forklift moves to an initial position corresponding to the loading task of the carriage, determining the size parameter of the carriage through a mobile base station on the unmanned forklift and a plurality of positioning labels on the carriage, loading the initial temporary map corresponding to the carriage based on the size parameter and a historical temporary map of the carriage, determining scanning auxiliary information corresponding to the carriage based on the size parameter and the historical temporary map of the carriage, acquiring internal point cloud data of the carriage based on the scanning auxiliary information corresponding to the carriage, constructing the temporary map corresponding to the carriage based on the initial temporary map and the internal point cloud data corresponding to the carriage, executing the loading task, and deleting the temporary map corresponding to the carriage after the unmanned forklift returns to the initial position, and reloading the fixed map of the warehouse. Further, the plurality of positioning tags on the carriage at least comprise a first positioning tag, a second positioning tag, a third positioning tag and a fourth positioning tag which are respectively arranged at four corners of a door of the carriage, and further comprise a fifth positioning tag which is arranged along the depth direction of the carriage, wherein the linear distance between the fifth positioning tag and one of the first positioning tag, the second positioning tag, the third positioning tag and the fourth positioning tag is the depth of the carriage. Further, the size parameters of the carriage are determined through the mobile base station on the unmanned forklift and the positioning labels on the carriage, wherein the size parameters of the carriage comprise the steps of determining a plurality of key position points, acquiring the characteristics of interaction signals of the mobile base station on the unmanned forklift and the positioning labels on the carriage for each key position point, and determining the size parameters of the carriage based on the characteristics of the interaction signals of the mobile base station on the unmanned forklift and the positioning labels on the carriage corresponding to each key position point. Further, determining a plurality of key