CN115840449A - Cargo handling method, cargo handling system, electronic device, and storage medium - Google Patents

Abstract

The embodiment of the application discloses a cargo handling method, a cargo handling system, electronic equipment and a storage medium, which are applied to a cargo handling system, wherein the cargo handling system comprises an unmanned forklift and a sensor module; the method comprises the following steps: determining zero position poses respectively corresponding to a plurality of carriers placed on the truck, wherein the carriers are used for loading cargoes, and the zero position poses are the poses of each carrier relative to a reference sensor in the sensor module; acquiring the offset of the actual pose of each carrier relative to the corresponding zero pose; determining an actual path for the unmanned forklift to fork the multiple vehicles according to the offset; and controlling the unmanned forklift to finish loading and unloading the goods based on the actual path of forking the plurality of carriers. By implementing the embodiment of the application, the efficiency of loading and unloading goods can be improved.

Description

Cargo handling method, system, electronic device and storage medium

technical field

The present application relates to the field of automation technology, and in particular to a cargo loading and unloading method, system, electronic equipment and storage medium.

Background technique

In industrial logistics, the loading and unloading of goods is an important link. The existing loading and unloading methods for goods usually use manual forklifts to load or unload the goods, but this method consumes a lot of labor, and each time the goods are forked, the goods must be manually aligned for forking, resulting in high loading and unloading efficiency. Low. Therefore, how to efficiently load and unload goods has become an urgent problem to be solved.

Contents of the invention

The embodiment of the present application discloses a cargo loading and unloading method, system, electronic equipment and storage medium, which can improve the efficiency of cargo loading and unloading.

The embodiment of the present application discloses a method for loading and unloading cargo, which is applied to a cargo loading and unloading system. The system includes an unmanned forklift and a sensor module; the method includes:

Determine the zero-position poses corresponding to the plurality of carriers placed on the truck, the carriers are used to load goods, and the zero-position poses are the references of each of the carriers relative to the sensor module The pose of the sensor;

Obtain the offset of the actual pose of each vehicle relative to the corresponding zero pose;

According to the offset, determine the actual path for the unmanned forklift to pick up the plurality of carriers;

The unmanned forklift is controlled to complete the loading and unloading of the cargo based on the actual path for forking the plurality of carriers.

In one embodiment, the sensor module is located on both sides of the unloading area of the truck, the detection area corresponding to the sensor module covers the unloading area, and the plurality of carriers determined to be placed on the truck correspond to The zero pose of , including:

Recognizing a plurality of vehicles placed on the truck from the trucks parked in the unloading area through a target recognition algorithm;

According to the detection data of each of the vehicles in the sensor module, calculate the global pose of each of the vehicles relative to the reference sensor, and each of the vehicles relative to the reference The global pose of the sensor is the zero pose of each vehicle.

In one embodiment, after the determination of the zero poses corresponding to the plurality of vehicles placed on the truck, the method further includes:

Determining the transformation pose of the unmanned forklift relative to the zero pose of each of the carriers when the unmanned forklift is aligned with the center of each of the carriers;

Based on the transition pose of the unmanned forklift relative to the zero pose of each of the vehicles, generating a preset path for the unmanned forklift to pick up the plurality of vehicles;

The determining the actual path for the unmanned forklift to pick up the plurality of carriers according to the offset includes:

According to the offset, the preset path for the unmanned forklift to pick up the plurality of carriers is adjusted to obtain an actual path for the unmanned forklift to pick up the plurality of carriers.

In one embodiment, the determination of the conversion position of the unmanned forklift relative to the zero position of each of the vehicles when the unmanned forklift is aligned with the center fork of each of the vehicles posture, including:

determining a reference vehicle from the plurality of vehicles;

According to the zero pose of the reference vehicle, and the pose of the unmanned forklift on the map when the unmanned forklift is aligned with the center of the reference vehicle, determine the unmanned The transformation pose of the forklift relative to the zero pose of the reference vehicle;

Based on the transformation pose of the unmanned forklift relative to the zero pose of the reference vehicle, the fixed distance between the multiple vehicles, and the size of each of the vehicles, determine the relative position of the unmanned forklift Transform poses based on the zero pose of each of the vehicles.

In one embodiment, according to the offset, the preset path for the unmanned forklift to pick up the plurality of carriers is adjusted, so that the unmanned forklift picks up the plurality of carriers Before the actual path of the tool, the method also includes:

Binding the plurality of carriers to different location identifiers respectively; wherein the location identifier is used to indicate the corresponding location of the carrier in the unloading area;

According to the offset, the preset path for the unmanned forklift to pick up the plurality of carriers is adjusted to obtain the actual path for the unmanned forklift to pick up the plurality of carriers, including:

According to the offset between the actual pose of each of the carriers relative to the corresponding zero pose, determine the offset between the actual pose of each of the carriers relative to the storage location indicated by the corresponding storage location identification displacement;

Adjusting the preset path for the unmanned forklift to pick up the plurality of carriers based on the offset between the actual pose of each of the carriers relative to the storage location indicated by the corresponding storage location identification, The actual path for the unmanned forklift to pick up the plurality of carriers is obtained.

In one embodiment, after the determination of the zero poses corresponding to the plurality of vehicles placed on the truck, the method further includes:

Inspecting the zero-position poses corresponding to the plurality of vehicles respectively, and obtaining a test result corresponding to each of the zero-position poses;

According to the inspection result corresponding to each of the zero-position poses, it is determined that the calibration of the zero-position poses is successful.

In one embodiment, before the target recognition algorithm is used to identify multiple carriers placed on the truck from the trucks parked in the unloading area, the method further includes:

When the truck is parked in the unloading area, fork the carrier in the truck to both sides of the compartment of the truck according to a fixed distance.

The embodiment of the present application discloses a cargo handling system. The cargo handling system includes an unmanned forklift and a sensor module. The system includes:

The sensor module is used to determine the zero position and posture corresponding to a plurality of carriers placed on the truck, and the carriers are used to load goods, and the zero position and posture are each of the carriers relative to The pose of the reference sensor in the sensor module;

The sensor module is used to obtain the offset of the actual pose of each vehicle relative to the corresponding zero pose;

The unmanned forklift is used to determine the actual path for the unmanned forklift to pick up the plurality of carriers according to the offset;

The unmanned forklift is configured to control the unmanned forklift to complete the loading and unloading of the goods based on the actual path for forking the plurality of carriers.

The embodiment of this application discloses an electronic device, including:

a memory storing executable program code;

a processor coupled to the memory;

The processor invokes the executable program code stored in the memory to execute the method described in any of the foregoing embodiments.

The embodiment of the present application discloses a computer-readable storage medium, where the computer-readable storage medium stores a computer program, wherein, when the computer program is executed by a processor, the processor executes any of the above-mentioned embodiments. described method.

Through the cargo handling method, system, electronic equipment, and storage medium disclosed in the embodiments of the present application, the cargo handling system includes an unmanned forklift and a sensor module; the cargo handling system determines each The zero pose of the vehicle, wherein the zero pose is based on the pose of each vehicle relative to the reference sensor in the sensor module; obtain the actual pose of each vehicle relative to the corresponding zero pose , and based on the offset, determine the actual path for the unmanned forklift to pick up multiple carriers; according to the actual path, the unmanned forklift is controlled to complete the loading and unloading of the goods. In the embodiment of the present application, based on the offset of the actual pose of each carrier relative to the corresponding zero pose, the actual path for the unmanned forklift to pick up the carrier can be accurately determined, improving the efficiency of loading and unloading goods.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the accompanying drawings that need to be used in the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For Those of ordinary skill in the art can also obtain other drawings based on these drawings without making creative efforts.

FIG. 1A is a schematic diagram of an application scenario of a cargo loading and unloading method disclosed in an embodiment of the present application;

Fig. 1B is a schematic diagram of a scene of an unloading area disclosed in the embodiment of the present application;

Fig. 2 is a schematic flow chart of a cargo loading and unloading method disclosed in the embodiment of the present application;

Fig. 3 is a schematic flow chart of another cargo loading and unloading method disclosed in the embodiment of the present application;

Fig. 4 is a schematic flow chart of another cargo loading and unloading method disclosed in the embodiment of the present application;

Fig. 5 is a schematic structural diagram of a cargo handling system disclosed in the embodiment of the present application;

FIG. 6 is a schematic structural diagram of an electronic device disclosed in an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

It should be noted that the terms "comprising" and "having" and any variations thereof in the embodiments of the present application are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or process that includes a series of steps or units. The apparatus is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to the process, method, product or apparatus.

The embodiment of the present application discloses a cargo loading and unloading method, system, electronic equipment and storage medium, which can improve the efficiency of cargo loading and unloading.

A detailed description will be given below in conjunction with the accompanying drawings.

As shown in FIG. 1A , FIG. 1A is a schematic diagram of an application scenario of a cargo loading and unloading method disclosed in an embodiment of the present application. The application scenario may include a sensor module 10 and an unmanned forklift 20 .

The sensor module 10 may include multiple sensors, and the sensors may be laser sensors, radar sensors, camera sensors, etc., and the sensor module 10 may also include a combination of the above sensors, which is not specifically limited. The sensor module 10 can be used to obtain the pose information of each vehicle placed on the truck.

In one embodiment, each sensor included in the sensor module 10 can be a composite sensor that combines a camera sensor and a three-dimensional laser sensor, and monitors the unloading area through a combination of vision and laser; specifically, the U-shaped bracket can be used to The camera sensor is fixed on the three-dimensional laser sensor, and the installation height of the sensor module 10 can be about 1.6 meters above the ground level, and the installation height can be about 10 centimeters higher than the compartment height of the truck.

The unmanned forklift 20 is an automatic guided vehicle (Automated Guided Vehicle, AGV), which may include but not limited to a latent AGV, a backpack AGV, and a counterweight AGV.

In one embodiment, the sensor module 10 can determine the zero poses corresponding to the multiple vehicles placed on the truck, and obtain the deviation of the actual pose of each vehicle relative to the corresponding zero pose. displacement;

Optionally, the application scenario may also include locally deployed electronic devices, which may include but not limited to mobile phones, tablet computers, wearable devices, notebook computers, PCs (Personal Computers, personal computers), etc.; the sensor module 10 may Send the zero pose of each vehicle and the actual pose of each vehicle to the locally deployed electronic device, and calculate the actual pose of each vehicle relative to the corresponding zero pose through the locally deployed electronic device further, the locally deployed electronic device can be used to run the unloading program to control the truck to unload the goods.

In one embodiment, the sensor module 10 can directly send the offset to the unmanned forklift 20;

Optionally, the application scenario can also include a central controller, which can include but not limited to mobile phones, tablet computers, wearable devices, notebook computers, PCs (Personal Computers, personal computers), etc.; the sensor module 10 can The offset is sent to the central controller, and the central controller sends the offset to the unmanned forklift 20; or, the sensor module 10 can send the offset to a locally deployed electronic device, and the locally deployed electronic device can send the offset to The displacement is directly sent to the unmanned forklift, or the locally deployed electronic device can send the displacement to the central controller, and the central controller then sends the displacement to the unmanned forklift, which is not limited; exemplary, local The deployed electronic equipment can send the offset to the central controller through the HTTP+JSONRPC communication method, and then the central controller will send the offset to the unmanned forklift.

In one embodiment, the unmanned forklift 20 can determine the actual path for the unmanned forklift 20 to fork multiple carriers according to the offset; the unmanned forklift 20 controls the unmanned forklift based on the actual path for the multiple carriers 20 Complete the loading and unloading of the goods, so as to achieve self-adaptive unloading of the goods.

FIG. 1B is a schematic diagram of a scene of an unloading area disclosed in an embodiment of the present application. The unloading area is used for parking trucks, and goods on the trucks can be loaded and unloaded in the unloading area. The two sides of the unloading area 120 are provided with sensor modules 10; the number of sensors in the sensor module 10 can be determined according to the size of the unloading area, which is not specifically limited.

As shown in FIG. 1B , in the unloading area 120 , the FOV of each sensor in the sensor module 10 can be used to calculate the installation position of each sensor, so as to ensure that there is an overlapping portion of field of view between two adjacent sensors to prevent loss of field of view. Optionally, the reference sensor can be determined from the multiple sensors of the sensor module 10, with the reference sensor as the origin, the detection areas corresponding to each sensor are spliced into a detection area sufficient to cover the unloading area through multi-sensor calibration to realize Monitoring of the unloading area. Optionally, multi-sensor fusion technology can be used to stitch the detection areas corresponding to each sensor into a point cloud image, and the pose information of each vehicle can be obtained on the point cloud image. As shown in FIG. 1B , the reference sensor 100 in the sensor module 10 corresponds to a field of view (FOV) 110 .

Implementing this embodiment, the cargo handling system scans the multiple vehicles placed on the truck based on the multi-sensor fusion technology through the sensor modules reasonably arranged on both sides of the unloading area, and determines the zero positions corresponding to the multiple vehicles. pose, that is, perform zero calibration for each vehicle, and then obtain the offset of the actual pose of each vehicle relative to the corresponding zero pose. After the unmanned forklift receives the offset, the forklift can be determined. The actual path of multiple vehicles, so as to efficiently and accurately perform unloading tasks, and realize self-adaptive unloading.

As shown in Figure 2, Figure 2 is a schematic flow chart of a cargo handling method disclosed in the embodiment of the present application. The cargo handling method can be applied to the cargo handling system in the above embodiment, and the cargo handling system can include unmanned forklifts and A sensor module; the cargo handling method may include the following steps:

201. Determine the zero poses corresponding to the multiple vehicles placed on the truck.

The carrier is a device used to load goods in the process of logistics transportation, for example, it can be a pallet, a coaming box, etc., which is not limited in detail. When the unmanned forklift is loading and unloading the goods, it can fork the carrier, so that the carrier and the goods can be loaded and unloaded as a whole.

The truck can be a van, a flatbed truck, a container truck, a panel truck, etc., and is not specifically limited; wherein, the van can be a flying wing truck, and the flying wing truck can open the side panels on both sides of the compartment when loading and unloading goods.

The sensor module can determine the zero poses corresponding to the multiple vehicles placed on the truck, wherein the zero pose is the pose of each vehicle relative to the reference sensor in the sensor module.

The reference sensor can be any one of the multiple sensors included in the sensor module; for the convenience of calculation, the reference sensor can also be the sensor located in the lower left position among the multiple sensors included in the sensor module, as shown in Figure 1B, without limitation.

Specifically, the xOy coordinate axis can be established with the reference sensor as the origin, and the x-axis coordinate value and the y-axis coordinate value of each vehicle relative to the coordinate system with the reference sensor as the origin can be obtained as each vehicle relative to the reference sensor. The pose of the sensor, that is, the zero pose.

202. Acquire the offset of the actual pose of each vehicle relative to the corresponding zero pose.

When a truck full of goods enters the unloading area, the sensor module can obtain the actual pose of each vehicle, and calculate the offset of the actual pose of each vehicle relative to the corresponding zero pose. As a result, there are deviations in the position of the truck every time it stops at the unloading area and the position of the goods placed on the truck every time. Therefore, if the route of the unmanned forklift to pick up the goods is completely planned according to the pre-set zero pose, it will lead to no Human forklifts cannot accurately pick up the vehicle loaded with cargo; therefore, during the actual cargo loading and unloading process, the sensor module can obtain the actual pose of each vehicle, and calculate the actual pose of each vehicle relative to the corresponding Offset for the zero pose.

203. According to the offset, determine the actual path for the unmanned forklift to pick up the multiple carriers.

According to the offset, the unmanned forklift determines the actual path for the unmanned forklift to fork multiple carriers.

Specifically, the sensor module can send the zero poses corresponding to multiple vehicles placed on the truck to the unmanned forklift, and the unmanned forklift can first generate a preset path according to the zero poses corresponding to each vehicle ; After the unmanned forklift obtains the offset of the actual pose of each vehicle relative to the corresponding zero pose, the unmanned forklift can adjust the preset path according to the offset to obtain multiple the actual path of the vehicle;

Alternatively, the unmanned forklift does not need to generate a preset path in advance, and can directly generate the unmanned forklift fork Get the actual paths of multiple vehicles.

In the embodiment of the present application, the unmanned forklift generates the actual path for forking multiple carriers by obtaining the zero offset of each carrier, which improves the accuracy of the actual path planned by the unmanned forklift, and improves the accuracy of the actual path for the unmanned forklift. Efficiency in cargo handling.

204. Control the unmanned forklift to complete the loading and unloading of the goods based on the actual path for forking multiple carriers.

The unmanned forklift controls the unmanned forklift to complete the loading and unloading of goods based on the actual path of forking multiple vehicles; the actual path can include the actual pose of multiple vehicles; the unmanned forklift accurately travels to each The carrier completes the unloading of the carrier, thereby realizing the loading and unloading of the goods.

In the embodiment of the present application, the cargo handling system can determine the zero position and posture of each carrier placed on the truck and used to load the cargo, wherein the zero position and posture is based on the relative position of each carrier in the sensor module. The pose of the benchmark sensor; obtain the offset of the actual pose of each vehicle relative to the corresponding zero pose, and determine the actual path for the unmanned forklift to take multiple vehicles based on the offset; according to The actual path controls the unmanned forklift to complete the loading and unloading of the goods. In the embodiment of the present application, based on the offset of the actual pose of each carrier relative to the corresponding zero pose, the actual path for the unmanned forklift to pick up the carrier can be accurately determined, improving the efficiency of loading and unloading goods.

As shown in Figure 3, Figure 3 is a schematic flow chart of another cargo handling method disclosed in the embodiment of the present application, the cargo handling method can be applied to the cargo handling system in the above embodiment, and the cargo handling method can include the following steps:

301. When the truck is parked in the unloading area, fork the carrier in the truck to both sides of the truck compartment at a fixed distance.

When the truck is parked in the unloading area, the unmanned forklift can fork the carriers in the truck to both sides of the truck compartment at a fixed distance; by regularly forking the loads to both sides of the truck compartment, it is beneficial to improve The efficiency of subsequent unloading of goods.

The sensor module can identify whether there is a truck parked in the unloading area through the target recognition algorithm; when the sensor module recognizes that there is a truck parked in the unloading area, it can send a prompt signal to the unmanned forklift. When the unmanned forklift receives the prompt signal, The unmanned forklift can go to the truck, and fork the vehicles in the truck to both sides of the truck compartment at a fixed distance until the vehicle is fully loaded. Exemplarily, the fixed interval may be 2 centimeters, which is not specifically limited.

302. Using a target recognition algorithm, identify multiple vehicles placed on the truck from the trucks parked in the unloading area.

The target recognition algorithm may be an R-CNN algorithm, a Faster R-CNN algorithm, a YOLO algorithm, etc., and is not specifically limited.

In the embodiment of the present application, the sensor modules are located on both sides of the unloading area of the truck, and the detection area corresponding to the sensor module covers the unloading area. Wherein, the sensor module may include a plurality of sensors, and the detection areas of each sensor may be spliced into a detection area completely covering the unloading area as the corresponding detection area of the sensor module. Specifically, among the multiple sensors included in the sensor module, there is an overlapping portion of field of view between two adjacent sensors to prevent loss of field of view. The sensor module can monitor the complete unloading area through the fusion of multiple sensors.

303. According to the detection data of each vehicle by each sensor in the sensor module, calculate the global pose of each vehicle relative to the reference sensor, and the global pose of each vehicle relative to the reference sensor is each vehicle The zero pose of .

The detection data of each sensor for each vehicle can be the vehicle's orientation data, distance data and image data, etc., which are not limited; for example, when the sensor is a three-dimensional laser sensor, the laser light can be irradiated on the surface of the vehicle, and The orientation data, distance data, etc. of the vehicle are obtained according to the reflected laser light; when the sensor is a depth camera sensor, the depth image data of the vehicle can be obtained.

Optionally, the sensor module can splice the detection areas corresponding to each sensor into a point cloud image to monitor the unloading area according to the detection data of each sensor in the sensor module for each vehicle, wherein the point cloud image is the sensor module The data matrix composed of the point cloud information of all points captured generates a point cloud map covering the unloading area; based on the point cloud map, the global pose of each vehicle relative to the reference sensor is calculated; the reference sensor can be used as the point cloud map The origin of the coordinate system, the global pose of each vehicle relative to the reference sensor can be the coordinate values of the x, y, and z axes of each vehicle in the point cloud image, which can be positive or negative.

By implementing the above steps, the point cloud image is obtained through multi-sensor fusion and splicing, and the global pose of each vehicle relative to the reference sensor is obtained, which improves the accuracy of zero-point calibration for each vehicle.

304 . Check the zero poses corresponding to the multiple vehicles respectively, and obtain a check result corresponding to each zero pose.

The sensor module can directly check the zero poses corresponding to multiple vehicles, and obtain the inspection results corresponding to each zero pose; or, the sensor module can check the zero poses corresponding to multiple vehicles It is sent to the locally deployed electronic device, and the zero position poses corresponding to multiple vehicles are checked through the electronic device, and the test results corresponding to each zero position pose are obtained.

Specifically, the sensor module can obtain the offset of each vehicle relative to the corresponding zero pose as the inspection result corresponding to each zero pose; when the inspection result shows that the offset is greater than 0, it is determined that If the calibration of the zero position and posture fails, re-calibration is performed; when the test result shows that the offset is equal to 0, it is determined that the calibration of the zero position and posture is successful.

Optionally, keep each vehicle still, check the log value of the offset of each vehicle relative to the zero pose, and use the log value of the offset of each vehicle relative to the zero pose as each The test result corresponding to the zero pose.

305. According to the inspection result corresponding to each zero-position pose, determine that the calibration of the zero-position pose is successful.

When the log value determines that the offset of each vehicle relative to the zero pose is 0, it means that the vehicle is in the zero pose, and then it is determined that the zero pose calibration of the vehicle is successful.

In the embodiment of the present application, the zero-position poses corresponding to multiple vehicles are checked, which can further improve the accuracy of the zero-position calibration of the vehicles.

306. Determine the transition pose of the unmanned forklift relative to the zero pose of each vehicle when the unmanned forklift is aligned with the center of each vehicle.

The unmanned forklift determines the transformation pose of the unmanned forklift relative to the zero pose of each vehicle when the unmanned forklift is aligned with the center of each vehicle.

Through step 301, the unmanned forklift first forks the vehicle in the truck to both sides of the truck compartment at a fixed distance; the compartment of the truck is generally rectangular, and the length of one side of the truck is a fixed value; the length of each vehicle and The fixed distance between each vehicle can determine the pose offset between two adjacent vehicles as the sum of the length of the vehicle and the fixed distance.

Therefore, by aligning the center fork of each carrier with the unmanned forklift, the unmanned forklift can be manually controlled to align with the reference carrier among the multiple carriers on one side of the carriage, and then based on the difference between the adjacent two carriers, position offset between them, control the unmanned forklift to automatically drive to each vehicle, align the center of each vehicle into the fork; or determine the marker corresponding to the center of each vehicle, and control the unmanned forklift to align Align the marker corresponding to the center of each vehicle, and then manually adjust the unmanned forklift until the unmanned forklift is aligned with the center of each vehicle and enters the fork.

As an optional implementation, the unmanned forklift determines the transformation pose of the unmanned forklift relative to the zero pose of each carrier when the unmanned forklift is aligned with the center of each carrier, which may include The steps are as follows: determine the reference vehicle from multiple vehicles; according to the zero pose of the reference vehicle, and the position of the unmanned forklift on the map when the unmanned forklift is aligned with the center of the reference vehicle. pose, determine the transformation pose of the unmanned forklift relative to the zero pose of the reference vehicle; based on the transformation pose of the unmanned forklift relative to the zero pose of the reference vehicle, the fixed distance between multiple The size of each vehicle determines the transformation pose of the unmanned forklift relative to the zero position of each vehicle;

Among them, the reference vehicle can be the first vehicle placed on the truck at the starting point of one side of the carriage, which is not specifically limited;

The unmanned forklift can receive the zero pose of the reference vehicle sent by the sensor module, or the unmanned forklift can receive the zero pose of the reference vehicle sent by the sensor module through the central controller;

Unmanned forklifts can collect environmental information through sensors, draw maps based on environmental information, and determine the position and posture of unmanned forklifts on the map according to the navigation system; for example, unmanned forklifts can realize map construction and positioning through visual navigation (VSLAM), Obtain the pose of the unmanned forklift on the map;

The unmanned forklift determines the zero position of the unmanned forklift relative to the reference vehicle based on the zero pose of the reference vehicle and the pose of the unmanned forklift on the map when the unmanned forklift is aligned with the center of the reference vehicle. The transformation pose of the pose;

Since the pose offset between two adjacent vehicles is the sum of the length of the vehicle and the fixed distance, after determining the transformation pose of the unmanned forklift relative to the zero pose of the reference vehicle, And the pose offset between two adjacent vehicles, and the pose of the unmanned forklift on the map when the unmanned forklift is aligned with the center of each vehicle, the unmanned forklift can be determined Transition pose relative to the zero pose of each vehicle.

In the embodiment of the present application, when the unmanned forklift enters the center of the vehicle, the unmanned forklift can use the pose of the unmanned forklift on the map and the zero pose of the vehicle to obtain the relative position of the unmanned forklift. A transformation pose based on the zero pose of the vehicle; wherein, the transformation pose is the pose of the unmanned forklift relative to the zero pose of each vehicle. Therefore, the zero pose of each vehicle can be converted into the converted pose of the unmanned forklift relative to the zero pose of each vehicle, and the zero calibration of each vehicle can be completed, which is conducive to the accuracy and efficiency of the unmanned forklift Accurately plan the preset paths for picking up multiple vehicles.

307. Based on the transformation pose of the unmanned forklift relative to the zero pose of each vehicle, generate a preset path for the unmanned forklift to fork and pick up multiple vehicles.

Specifically, the unmanned forklift can generate a preset path for the unmanned forklift to fork multiple carriers based on the transformation pose of the unmanned forklift relative to the zero pose of each carrier and the surrounding environment information of the unloading area; The unmanned forklift can receive the environmental information of the unloading area sent by the sensor module, or can obtain the surrounding environmental information through sensors such as laser scanners installed on the unmanned forklift; The path can adapt to the surrounding environment, avoid obstacles in time, and can accurately fork to each vehicle.

Because there are deviations in the position where the truck stops at the unloading area and the position where the vehicle is placed on the truck every time, it is impossible to accurately pick up the vehicle loaded with goods according to the preset path of the unmanned forklift planned in the early stage; To solve this problem, the embodiment of the present application performs zero calibration on the carrier, so that the unmanned forklift can accurately fork each carrier according to the zero offset of the carrier, and complete the loading and unloading of the goods, which improves the loading and unloading of the goods. s efficiency.

308. Acquire the offset of the actual pose of each vehicle relative to the corresponding zero pose.

For the implementation manner of step 308, reference may be made to the foregoing embodiments, and details are not repeated here.

309. According to the offset, adjust the preset path for the unmanned forklift to pick up the multiple carriers to obtain the actual path for the unmanned forklift to pick up the multiple carriers.

After the unmanned forklift generates the preset path for forking multiple vehicles according to the zero pose of multiple vehicles, after obtaining the offset, it only needs to be adjusted on the basis of the preset path, which improves the determination of the unmanned Human forklifts determine the efficiency of the actual path for forking multiple carriers, thereby increasing the efficiency of loading and unloading cargo.

310. Control the unmanned forklift to complete the loading and unloading of the goods based on the actual path for forking the multiple carriers.

In the embodiment of the present application, the cargo loading and unloading system can regularly fork the loads in the truck to both sides of the truck compartment when it recognizes that the truck is parked in the unloading area, which is conducive to improving the efficiency of subsequent unloading of the cargo; Moreover, through the detection data of each vehicle in the sensor module, the global pose of each vehicle relative to the reference sensor is determined as the zero pose, which improves the accuracy of the zero calibration of the vehicle ;Convert the zero pose of the vehicle into the transformation pose of the unmanned forklift relative to the zero pose of the vehicle, thereby generating a preset path for the unmanned forklift to pick up multiple vehicles; based on each The offset of the actual pose of the vehicle relative to the corresponding zero pose can be adjusted by adjusting the preset paths of multiple vehicles, which can accurately determine the actual path for the unmanned forklift to pick up the vehicle and improve the efficiency of loading and unloading. efficiency.

As shown in Figure 4, Figure 4 is a schematic flow chart of another cargo handling method disclosed in the embodiment of the present application, the cargo handling method can be applied to the cargo handling system in the above embodiment, and the cargo handling method can include the following steps:

401. Determine the zero poses corresponding to the multiple vehicles placed on the truck.

Vehicles are used to load goods, and the zero pose is the pose of each vehicle relative to the reference sensor in the sensor module.

402. Determine the transition pose of the unmanned forklift relative to the zero pose of each vehicle when the unmanned forklift is aligned with the center of each vehicle.

403. Based on the transformed pose of the unmanned forklift relative to the zero pose of each vehicle, generate a preset path for the unmanned forklift to pick up multiple vehicles.

404. Acquire the offset of the actual pose of each vehicle relative to the corresponding zero pose.

For implementation manners of steps 401 to 404, reference may be made to the foregoing embodiments, and details are not repeated here.

405. Bind multiple carriers to different location identifiers respectively.

Unmanned forklifts can bind multiple vehicles to different location identifiers.

Wherein, the storage location identification is used to indicate the corresponding storage location of the carrier in the truck compartment.

Wherein, the warehouse location is an area for placing vehicles in the compartment of the truck, which is an artificially planned area; for example, the compartment can be divided into two rows, and each row is divided into 10 areas for placing vehicles.

For example, determine the reference vehicle from multiple vehicles and bind it to location ID 0; other vehicles can be bound to location ID 1, location ID 2, location ID 3... , without limitation.

406. According to the offset of the actual pose of each carrier relative to the corresponding zero pose, determine the offset between the actual pose of each carrier and the location indicated by the corresponding location identifier .

The unmanned forklift determines the offset between the actual pose of each carrier relative to the location indicated by the corresponding location identifier according to the offset of the actual pose of each carrier relative to the corresponding zero pose Quantity; by binding the vehicle with the location identification, the zero pose of the vehicle can be converted into the corresponding location of the vehicle, based on the actual pose of each vehicle relative to the corresponding location identification The offset between the indicated storage locations can more accurately determine the actual storage location of each vehicle, which is beneficial for unmanned forklifts to pick multiple forks based on the actual storage location of each vehicle. The preset path of the carrier is adjusted so that each carrier can be forked to the actual location where it will be placed.

407. Based on the offset between the actual pose of each vehicle and the storage location indicated by the corresponding storage location identification, adjust the preset path for the unmanned forklift to pick up multiple vehicles to obtain the unmanned forklift Fork the actual paths of multiple vehicles.

As an optional implementation, the unmanned forklift determines the actual pose of each carrier relative to the corresponding zero position of each carrier based on the offset of the actual pose of each carrier relative to the corresponding The offset between the storage locations indicated by the storage location identification may include the following steps:

According to the offset of the actual pose of each vehicle relative to the corresponding zero pose, determine the actual pose of the target vehicle from multiple vehicles; determine the actual pose of the target vehicle relative to the corresponding The offset between the storage locations indicated by the storage location identification; wherein, the offset of the actual pose of the target vehicle relative to the corresponding zero pose is greater than 0;

Based on the offset between the actual pose of each vehicle and the storage location indicated by the corresponding storage location identification, the unmanned forklift adjusts the preset path for the unmanned forklift to pick up multiple vehicles, and the unmanned forklift obtains The actual path for the forklift to pick up multiple carriers may include the following steps:

Based on the offset between the actual pose of the target vehicle and the storage location indicated by the corresponding storage location logo, the unmanned forklift adjusts the preset path for the unmanned forklift to pick up multiple vehicles to obtain the unmanned forklift Fork the actual paths of multiple vehicles.

By performing the above steps, the target vehicle whose actual pose relative to the corresponding zero pose offset is greater than 0 can be determined from multiple vehicles, which is conducive to quickly screening out the target warehouse location with zero offset. And based on the offset between the actual pose of the target vehicle and the storage location indicated by the corresponding storage location identification, the preset path for the unmanned forklift to pick up multiple vehicles is locally adjusted, which improves the handling of goods. s efficiency.

408. Control the unmanned forklift to complete the loading and unloading of the goods based on the actual path for forking the multiple carriers.

In the embodiment of the present application, the cargo handling system can obtain the zero position and posture of each vehicle relative to the reference sensor through the sensor module, which improves the accuracy of zero position calibration for the vehicle; converts the zero position and posture of the vehicle to The conversion pose of the unmanned forklift relative to the zero position of the vehicle can generate a preset path for the unmanned forklift to pick up multiple vehicles; by binding the vehicle with the location identifier, the load can be Based on the offset between the actual pose of each vehicle and the storage location indicated by the corresponding storage location identification, it can be more accurately determined It is beneficial for the unmanned forklift to adjust the preset path for picking up multiple vehicles based on the actual storage location of each vehicle, so as to accurately fork each vehicle. Pick up the actual location to be placed, which improves the efficiency of loading and unloading goods.

As shown in FIG. 5, FIG. 5 is a modular schematic diagram of a cargo handling system disclosed in the embodiment of the present application. The cargo handling system 500 includes a sensor module 10 and an unmanned forklift 20. The system includes:

The sensor module 10 is used to determine the zero-position poses corresponding to the plurality of vehicles placed on the truck, and the vehicles are used to load goods, and the zero-position pose is each vehicle relative to the reference sensor in the sensor module 10 posture;

The sensor module 10 is used to obtain the offset of the actual pose of each vehicle relative to the corresponding zero pose;

The unmanned forklift 20 is used to determine the actual path for the unmanned forklift 20 to fork multiple carriers according to the offset;

The unmanned forklift truck 20 is used to control the unmanned forklift truck 20 to complete the loading and unloading of goods based on the actual path of picking up multiple carriers.

In one embodiment, the sensor module 10 is located on both sides of the unloading area of the truck, and the detection area corresponding to the sensor module 10 covers the unloading area. Identify a plurality of vehicles placed on the truck; calculate the global pose of each vehicle relative to the reference sensor according to the detection data of each sensor in the sensor module 10, and calculate the global pose of each vehicle relative to the reference sensor. The global pose of the sensor is the zero pose of each vehicle.

In one embodiment, the unmanned forklift 20 is also used to determine that the unmanned forklift 20 is aligning each vehicle after the sensor module 10 determines the corresponding zero poses of the multiple vehicles placed on the truck. The transformation pose of the unmanned forklift 20 relative to the zero pose of each vehicle when the center enters the fork; based on the transformation pose of the unmanned forklift 20 relative to the zero pose of each vehicle, an unmanned forklift is generated 20 forks to take preset paths of multiple vehicles;

The unmanned forklift 20 is also used to adjust the preset path for the unmanned forklift 20 to fork multiple carriers according to the offset, so as to obtain the actual path for the unmanned forklift 20 to fork multiple carriers.

In one embodiment, unmanned forklift 20 is also used to determine the reference carrier from multiple carriers; In the case of the pose of the unmanned forklift 20 on the map, determine the transformation pose of the unmanned forklift 20 relative to the zero pose of the reference vehicle; The conversion pose, the fixed distance between multiple carriers and the size of each carrier determine the transfer pose of the unmanned forklift 20 relative to the zero pose of each carrier.

In one embodiment, the unmanned forklift 20 is also used to adjust the preset path for the unmanned forklift 20 to fork multiple carriers according to the offset, so as to obtain the actual Before the path, multiple vehicles are bound to different location identifiers; where the location identifier is used to indicate the corresponding location of the carrier in the unloading area;

The unmanned forklift 20 is also used to determine the actual pose of the target vehicle among the multiple vehicles corresponding to the target vehicle according to the offset of the actual pose of each vehicle relative to the zero pose corresponding to the vehicle. The offset between the storage locations indicated by the location identification of the target vehicle; the offset of the actual pose of the target vehicle relative to the zero pose of the target vehicle is greater than the offset threshold; according to the actual pose of the target vehicle Relative to the offset between the storage locations indicated by the storage location identification corresponding to the target vehicle, adjust the preset path for the unmanned forklift to pick up multiple vehicles to obtain the actual path.

In one embodiment, the sensor module 10 can be used to check the zero poses corresponding to the multiple vehicles respectively after determining the zero poses corresponding to the multiple vehicles placed on the truck, and obtain each The test results corresponding to the zero poses; according to the test results corresponding to each zero pose, it is determined that the calibration of the zero poses is successful.

In one embodiment, the unmanned forklift 20 can be used to unload the truck when the truck is parked in the unloading area before identifying multiple carriers placed on the truck from the trucks parked in the unloading area through the target recognition algorithm. The carrier in the fork is picked up to both sides of the truck compartment at a fixed distance.

In the embodiment of the present application, the cargo handling system includes an unmanned forklift and a sensor module; the cargo handling system determines the zero pose of each carrier placed on the truck and used to load the cargo, wherein the zero pose The pose is based on the pose of each vehicle relative to the reference sensor in the sensor module; the offset of the actual pose of each vehicle relative to the corresponding zero pose is obtained, and based on the offset, no Human forklifts fork the actual paths of multiple carriers; according to the actual paths, unmanned forklifts are controlled to complete the loading and unloading of goods. In the embodiment of the present application, based on the offset of the actual pose of each carrier relative to the corresponding zero pose, the actual path for the unmanned forklift to pick up the carrier can be accurately determined, improving the efficiency of loading and unloading goods.

As shown in FIG. 6, in one embodiment, an electronic device is provided, and the electronic device may include:

a memory 610 storing executable program code;

a processor 620 coupled to the memory 610;

The processor 620 invokes the executable program codes stored in the memory 610 to implement the cargo loading and unloading methods provided in the foregoing embodiments.

The memory 610 may include a random access memory (Random Access Memory, RAM), and may also include a read-only memory (Read-Only Memory, ROM). Memory 610 may be used to store instructions, programs, codes, sets of codes, or sets of instructions. The memory 610 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playback function, an image playback function, etc.) , instructions for implementing the foregoing method embodiments, and the like. The storage data area can also store data and the like created by the electronic device during use.

Processor 620 may include one or more processing cores. The processor 620 uses various interfaces and lines to connect various parts of the entire electronic device, and executes electronic functions by running or executing instructions, programs, code sets or instruction sets stored in the memory 610, and calling data stored in the memory 610. Various functions and processing data of the device. Optionally, the processor 620 may use at least one of Digital Signal Processing (Digital Signal Processing, DSP), Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA), and Programmable Logic Array (Programmable LogicArray, PLA). implemented in the form of hardware. The processor 620 may integrate one or a combination of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), a modem, and the like. Among them, the CPU mainly handles the operating system, user interface and application programs, etc.; the GPU is used to render and draw the displayed content; the modem is used to handle wireless communication. It can be understood that the above modem may also not be integrated into the processor 620, but implemented by a communication chip alone.

It can be understood that the electronic device may include more or less structural elements than those in the above structural block diagram, for example, including a power module, a physical button, a WiFi (Wireless Fidelity, wireless fidelity) module, a speaker, a Bluetooth module, a sensor, etc., It can also not be limited here.

The embodiment of the present application discloses a computer-readable storage medium, which stores a computer program, where the computer program causes a computer to execute the methods described in the foregoing embodiments.

In addition, the embodiments of the present application further disclose a computer program product. When the computer program product is run on a computer, the computer can execute all or part of the steps in any cargo handling method described in the above embodiments.

Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above-mentioned embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium includes read-only Memory (Read-Only Memory, ROM), Random Access Memory (Random Access Memory, RAM), Programmable Read-Only Memory (Programmable Read-only Memory, PROM), Erasable Programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), One-time Programmable Read-Only Memory (OTPROM), Electronically Erasable Programmable Read-Only Memory (EEPROM), Compact Disc Read-Only Memory (CompactDisc Read -Only Memory, CD-ROM) or other optical disk storage, magnetic disk storage, tape storage, or any other computer-readable medium that can be used to carry or store data.

A cargo handling method, system, electronic equipment, and storage medium disclosed in the embodiments of the present application have been described above in detail. In this paper, specific examples have been used to illustrate the principles and implementation methods of the present application. The descriptions of the above embodiments are only used To help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific implementation and application scope. In summary, this specification The content should not be construed as a limitation of the application.

Claims (10)

1. A cargo handling method is characterized by being applied to a cargo handling system, wherein the system comprises an unmanned forklift and a sensor module; the method comprises the following steps:

determining zero position poses respectively corresponding to a plurality of vehicles placed on a truck, wherein the vehicles are used for loading cargos, and the zero position poses are the poses of each vehicle relative to a reference sensor in the sensor module;

acquiring the offset of the actual pose of each carrier relative to the corresponding zero pose;

determining an actual path for the unmanned forklift to fork the plurality of vehicles according to the offset;

and controlling the unmanned forklift to finish loading and unloading the goods based on the actual path for forking the plurality of carriers.

2. The method of claim 1, wherein the sensor modules are located on two sides of an unloading area of the truck, the detection areas corresponding to the sensor modules cover the unloading area, and the determining zero poses corresponding to the plurality of vehicles placed on the truck respectively comprises:

identifying, by a target identification algorithm, a plurality of vehicles placed on a truck parked in the unloading area from the truck;

and calculating the global position and posture of each carrier relative to the reference sensor according to the detection data of each carrier by each sensor in the sensor module, wherein the global position and posture of each carrier relative to the reference sensor is the zero position and posture of each carrier.

3. The method of claim 1 or 2, wherein after the determining respective zero positions of the plurality of vehicles placed on the truck, the method further comprises:

determining a conversion pose of the unmanned forklift relative to a zero position pose of each carrier under the condition that the unmanned forklift enters a fork by aligning the center of each carrier;

generating a preset path for the unmanned forklift to fork the plurality of carriers based on the conversion pose of the zero position pose of the unmanned forklift relative to each carrier;

the determining an actual path for the unmanned forklift to fork the plurality of vehicles according to the offset includes:

and adjusting the preset paths of the plurality of carriers for forking by the unmanned forklift according to the offset to obtain the actual paths of the plurality of carriers for forking by the unmanned forklift.

4. The method of claim 3, wherein the determining the transformed pose of the zero pose of the unmanned forklift relative to each of the vehicles with the center fork of each of the vehicles aligned comprises:

determining a reference carrier from the plurality of carriers;

determining a conversion pose of the zero position pose of the unmanned forklift relative to the reference carrier according to the zero position pose of the reference carrier and the pose of the unmanned forklift on a map under the condition that the unmanned forklift enters a fork in alignment with the center of the reference carrier;

and determining the conversion pose of the zero position pose of the unmanned forklift relative to each carrier based on the conversion pose of the zero position pose of the unmanned forklift relative to the reference carrier, the fixed intervals among the plurality of carriers and the size of each carrier.

5. The method of claim 3, wherein prior to said adjusting the pre-set path for the auto-forklift to fork the plurality of vehicles based on the offset to obtain the actual path for the auto-forklift to fork the plurality of vehicles, the method further comprises:

binding the carriers with different storage location identifications respectively; the garage position mark is used for indicating a corresponding garage position of the carrier in the unloading area;

adjusting the preset paths of the plurality of carriers for the unmanned forklift to fork according to the offset to obtain the actual paths of the plurality of carriers for the unmanned forklift to fork, comprising:

determining the offset between the actual pose of each carrier and the corresponding position indicated by the corresponding position identifier according to the offset of the actual pose of each carrier relative to the corresponding zero position pose;

and adjusting the preset paths for the unmanned forklift to fork the plurality of carriers based on the offset between the actual pose of each carrier and the corresponding library position indicated by the library position identification, so as to obtain the actual paths for the unmanned forklift to fork the plurality of carriers.

6. The method of claim 1 or 2, wherein after the determining respective zero positions of the plurality of vehicles placed on the truck, the method further comprises:

checking zero position poses respectively corresponding to the multiple carriers, and acquiring a checking result corresponding to each zero position pose;

and determining that the zero position pose is successfully calibrated according to the detection result corresponding to each zero position pose.

7. The method of claim 2, wherein prior to said identifying, by a target identification algorithm, a plurality of vehicles placed on a truck parked in the unloading area from the truck, the method further comprises:

and under the condition that the truck is parked in the unloading area, forking the vehicles in the truck to the two sides of the carriage of the truck according to a fixed distance.

8. A cargo handling system comprising an unmanned forklift and a sensor module, the system comprising:

the sensor module is used for determining zero position poses respectively corresponding to a plurality of vehicles placed on the truck, the vehicles are used for loading cargos, and the zero position poses are poses of each vehicle relative to a reference sensor in the sensor module;

the sensor module is used for acquiring the offset of the actual pose of each carrier relative to the corresponding zero pose;

the unmanned forklift is used for determining the actual path of the unmanned forklift for forking the plurality of carriers according to the offset;

the unmanned forklift is used for controlling the unmanned forklift to complete loading and unloading of the goods based on actual paths of the plurality of carriers.

9. An electronic device, comprising:

a memory storing executable program code;

a processor coupled with the memory;

the processor calls the executable program code stored in the memory to perform the method of any of claims 1 to 7.

10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, causes the processor to perform the method of any of claims 1 to 7.

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