CN117146828B - Method and device for guiding picking path, storage medium and computer equipment - Google Patents
Method and device for guiding picking path, storage medium and computer equipment Download PDFInfo
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Abstract
The utility model provides a pick path guiding method, device, storage medium and computer equipment, can confirm the sight direction of pick person according to warehouse real-time monitoring video, and based on the sight direction of pick person, pick person's real-time position in the warehouse and treat pick person's goods position in the warehouse, confirm pick person's steering information and travel distance respectively, and then can be according to steering information and travel distance generation path guiding text, make pick person can adopt the general electronic terminal of lower cost to receive path guiding text. Therefore, on one hand, the path guidance can be realized by using the existing monitoring equipment of the warehouse and the general electronic terminal with lower cost, and AR equipment is not required to be additionally configured for the pickers, so that the cost of the path guidance can be reduced. On the other hand, the movement of the pickers can be guided accurately according to the steering information and the movement distance. Thus, the cost and the guiding effect can be simultaneously achieved.
Description
Technical Field
The present disclosure relates to the field of image recognition technologies, and in particular, to a method and apparatus for guiding a pick path, a storage medium, and a computer device.
Background
With the continuous development of electronic malls and online shopping, more and more people choose to purchase goods on the internet. After receiving the user order, the merchant needs to pick up and carry the goods related to the user order in the warehouse and package and transport the goods related to the user order.
The warehouse picking modes can be divided into two modes, namely manual sowing type picking and manual picking type picking. The manual sowing type picking means that cargoes related to a plurality of user orders are summarized according to the category of the cargoes, the cargoes are picked in a warehouse according to the summarized cargoes list, and then secondary sorting is carried out according to different users or different user orders. The manual picking type goods picking is a process that a pointer picks and concentrates goods one by one from corresponding storage positions in a warehouse by adopting a manual mode for each user order.
Considering that the goods stored in the warehouse are various and the goods related to each user order are different, in order to improve the efficiency of manual picking, the prior art proposes a scheme of automatically planning a picking path by adopting computer equipment and guiding a picker to move according to the planned picking path. However, as the inventor studies found, in order to accurately guide the movement of pickers, the prior art needs to configure an AR (Augmented Reality ) device for each picker to show an AR navigation path through the AR device, which is cost-prohibitive.
Disclosure of Invention
The object of the present application is to solve at least one of the above technical drawbacks, and in particular, the technical drawbacks of the prior art that the cost and the guiding effect cannot be combined.
In a first aspect, embodiments of the present application provide a method for guiding a pick path, the method including:
determining the position of goods to be picked in a warehouse;
human body detection is carried out on the warehouse real-time monitoring video, and the five sense organ position information of the pickers is determined based on the human body detection result;
determining the sight line direction of the goods picking person based on the five sense organs position information, and determining steering information according to the sight line direction and the goods position of the goods to be picked;
acquiring a real-time position of the picker in the warehouse, and calculating a moving distance according to the real-time position and the goods position of the goods to be picked;
generating a path guiding text according to the moving distance and the steering information, and sending the path guiding text to an electronic terminal carried by the picker.
In one embodiment, the five sense organ position information includes a left ear position coordinate, a right ear position coordinate, and a nose tip position coordinate;
the step of determining the vision direction of the picker based on the facial feature position information includes:
Respectively taking the left ear position coordinate, the right ear position coordinate and the nose tip position coordinate as three vertexes to construct a triangle;
and determining the barycentric coordinates of the triangle, and taking the direction pointing from the barycentric coordinates to the nose tip position coordinates as the sight line direction.
In one embodiment, the steering information includes a steering angle and a steering direction;
the step of determining steering information according to the sight line direction and the goods position of the goods to be picked comprises the following steps:
taking a direction pointing to the goods position of the goods to be picked from the barycentric coordinates as a target direction;
and respectively determining the steering angle and the steering direction according to the sight line direction and the target direction.
In one embodiment, the step of obtaining the real-time location of the picker in the warehouse comprises:
and determining the real-time position based on the human body detection result and preset warehouse pattern information.
In one embodiment, the step of determining the location of the pick-up items in the warehouse comprises:
determining a warehouse picking path corresponding to the picker; the warehouse picking path is pre-generated and is used for indicating the picking sequence of various target cargos and the cargo position of each target cargos; the target goods are goods related to a picking task corresponding to the picker;
Determining the goods position of the goods to be picked in the warehouse according to the warehouse goods picking path and the goods picking progress information; wherein the pick progress information includes a goods identifier for each picked good.
In one embodiment, the generating of the warehouse picking path includes:
acquiring the goods identification of various target goods;
acquiring cargo information of each target cargo according to each cargo identifier; wherein the cargo information of each target cargo comprises the cargo position, the cargo weight and the cargo volume of the target cargo;
and inputting the goods identifications and the goods information of the target goods into a path planning model which is trained in advance to obtain the warehouse picking path which is output by the path planning model.
In one embodiment, the step of acquiring the cargo information of each target cargo according to each cargo identifier includes:
extracting a target video image from the warehouse real-time monitoring video;
inputting each cargo identifier and each target video image into a cargo identification model obtained through training in advance so as to obtain cargo positions of various target cargos output by the cargo identification model;
And inquiring a pre-constructed cargo information database according to each cargo identifier, and obtaining the cargo weight and the cargo volume of each target cargo.
In a second aspect, embodiments of the present application provide a pick path guidance device, the device comprising:
the goods position determining module is used for determining the goods position of the goods to be picked in the warehouse;
the five sense organ position information determining module is used for detecting human bodies of warehouse real-time monitoring videos and determining the five sense organ position information of the pickers based on human body detection results;
the steering information determining module is used for determining the sight line direction of the goods picking person based on the five sense organs position information and determining steering information according to the sight line direction and the goods position of the goods to be picked;
the moving distance calculating module is used for acquiring the real-time position of the picker in the warehouse and calculating the moving distance according to the real-time position and the goods position of the goods to be picked;
and the guiding module is used for generating a path guiding text according to the moving distance and the steering information and sending the path guiding text to an electronic terminal carried by the picker.
In a third aspect, embodiments of the present application provide a storage medium having stored therein computer readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the pick path guidance method of any of the embodiments described above.
In a fourth aspect, embodiments of the present application provide a computer device, comprising: one or more processors, and memory;
the memory has stored therein computer readable instructions that, when executed by the one or more processors, perform the steps of the pick path guidance method of any of the embodiments described above.
According to the method, the device, the storage medium and the computer equipment for guiding the picking path, the sight direction of the picker can be determined according to the warehouse real-time monitoring video, and the steering information and the moving distance of the picker are respectively determined based on the sight direction of the picker, the real-time position of the picker in the warehouse and the position of the goods to be picked in the warehouse, so that the path guiding text can be generated according to the steering information and the moving distance, and the picker can receive the path guiding text by adopting a general electronic terminal with lower cost. Therefore, on one hand, the method and the device can realize path guidance by using the existing monitoring equipment of the warehouse and the general electronic terminal with lower cost, and the AR equipment is not required to be additionally configured for the pickers, so that the cost of path guidance can be reduced. On the other hand, the method and the device can guide the pickers to move according to the steering information and the moving distance, so that the pickers can accurately and quickly determine the goods positions of the goods to be picked. Therefore, the method and the device can accurately guide the pickers to move through a low-cost scheme, and give consideration to cost and guiding effect.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is an application environment diagram of a pick path guidance method in one embodiment;
FIG. 2 is a flow diagram of a method of routing a pick path in one embodiment;
FIG. 3 is a schematic diagram of a pick path guidance device in one embodiment;
fig. 4 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
In one embodiment, the pick path guidance method provided by the present application may be applied in the application environment shown in fig. 1. Wherein, at least one monitoring device 102 can be arranged in the warehouse, and each monitoring device 102 can be used for monitoring the warehouse in real time and generating a warehouse real-time monitoring video. The picker 104 may carry an electronic terminal 106 when picking. The electronic terminal 106 may be a device with communication and text display functions, and may be, but is not limited to, a smart phone, a tablet computer, and a portable wearable device, which may be a smart watch, a smart bracelet, etc. It should be noted that, the electronic terminals 106 carried by each two pickers 104 may be the same type of electronic terminals or different types of electronic terminals. For example, the electronic terminals 106 carried by each two pickers 104 may be smart bracelets, or smart phones and smart watches, respectively. The computer device 108 may be a device having data processing and communication functions, and may be, but is not limited to, various personal computers, notebook computers, and servers.
The computer device 108 may communicatively connect the monitoring device 102 and the respective electronic terminals 106 to obtain warehouse live monitoring video captured by the monitoring device 102 and to send path guidance text to the electronic terminals 106. During the path guidance process, the computer device 108 may acquire warehouse real-time surveillance videos and identify the vision direction of the pickers 104 based on the warehouse real-time surveillance videos. The computer device 108 may determine turn information and travel distance of the pickers 104 based on the line of sight of the pickers 104, the real-time location of the pickers 104 in the warehouse, and the location of the goods to be picked in the warehouse, respectively, and generate path guidance text based on the turn information and travel distance. The computer device 108 may issue route guidance text to the electronic terminal 106 carried by the picker 104, such that the picker 104 may view the route guidance text through the electronic terminal 106 carried by the picker and move as indicated by the route guidance text, implementing route guidance.
In one embodiment, the present application provides a method for guiding a pick path, and the following embodiment is described by taking an example that the method is applied to the computer device shown in fig. 1. As shown in fig. 2, the pick path guiding method provided in the present application may include the following steps:
s202: the location of the item to be picked in the warehouse is determined.
In this step, the goods to be picked up may be goods that the picker needs to pick up. Further, when the picker needs to pick a plurality of cargoes, the computer device may determine one of the plurality of non-picked cargoes as a to-be-picked cargo, and determine a placement position of the to-be-picked cargo in the warehouse, so as to obtain a cargo position of the to-be-picked cargo.
S204: human body detection is carried out on the warehouse real-time monitoring video, and the five sense organ position information of the pickers is determined based on the human body detection result.
The monitoring video can be collected in real time by monitoring equipment arranged in the warehouse, and can be used for recording goods conditions and personnel movement conditions in the warehouse. The facial position information may be position information of at least one facial organ in a video frame of a warehouse real-time monitoring video.
In the step, the computer equipment can perform human body detection on the warehouse real-time monitoring video so as to identify and detect the pickers in the warehouse real-time monitoring video. Because the human body detection result can indicate the position of the pickers in the video picture of the warehouse real-time monitoring video, the computer equipment can position the pickers in the warehouse real-time monitoring video according to the human body detection result and identify the five sense organ position information of the pickers according to the positioning result.
It will be appreciated that the computer device may perform human detection in any manner, and is not particularly limited herein. In one example, the computer device may perform human detection based on a pre-trained human detection model, i.e., identify pickers in warehouse real-time surveillance videos using the human detection model. In this example, the human detection model may be a model that is trained on the YOLO V4 model using a first training data set. The first training data set may include a plurality of sets of first training data, and each set of first training data may include a picker image collected in a warehouse in advance, a picker position marking result corresponding to the picker image, and a picker name corresponding to the picker image. Further, considering that a plurality of pickers may exist in the warehouse, when a plurality of human bodies are detected in the warehouse real-time monitoring video, the computer device may determine the unique personnel identifier corresponding to each human body, so as to distinguish each picker according to the unique personnel identifier, and further distinguish the pickpaths and the path guiding texts corresponding to each picker. For example, the computer device may uniquely identify the picker name output by the human detection model as a person.
S206: and determining the sight direction of the picker based on the five-sense organ position information, and determining steering information according to the sight direction and the goods position of the goods to be picked.
In this step, in order to accurately and rapidly guide the picker to the goods position where the goods are to be picked up and pick up the goods, considering that the attention of the picker is focused on the goods in the sight line direction, the computer device may determine the sight line direction of the picker according to the five sense organ position information of the picker to determine the eye gazing direction of the picker. The computer device may determine steering information based on the line of sight direction and the cargo position of the cargo to be picked, the steering information being operable to guide the pickers to steer the line of sight direction to the cargo position of the cargo to be picked.
It will be appreciated that the computer device may determine the direction of the line of sight of the pickers based on any manner, as long as the computer device determines from the facial feature location information. For example, the computer device may label the five sense organs of the pickers in the warehouse real-time monitoring video according to the five sense organ position information, and input the warehouse real-time monitoring video labeled with the five sense organs of the human body into the line-of-sight direction determination model trained in advance to acquire the line-of-sight direction output by the line-of-sight direction determination model.
S208: and acquiring the real-time position of the picker in the warehouse, and calculating the moving distance according to the real-time position and the goods position of the goods to be picked.
In this step, the computer device may locate the real-time position of the picker in the warehouse through an electronic terminal carried by the picker, or may determine the real-time position of the picker based on the human detection result, which is not particularly limited herein. When the computer equipment acquires the real-time position of the picker, the distance between the real-time position and the goods position of the goods to be picked can be calculated to obtain the moving distance.
S210: generating a path guiding text according to the moving distance and the steering information, and sending the path guiding text to an electronic terminal carried by the picker.
In this step, the path guidance text may include the moving distance and the steering information. The picker can receive the path guide text through the electronic terminal carried by the picker and turn and advance according to the turn information and the moving distance included in the path guide text, so that the picker can accurately and quickly reach the goods position of the goods to be picked and finish goods picking.
In the method, the line of sight direction of the pickers is determined according to the warehouse real-time monitoring video, and the steering information and the moving distance of the pickers are respectively determined based on the line of sight direction of the pickers, the real-time position of the pickers in the warehouse and the goods position of the goods to be picked in the warehouse, so that the path guiding text can be generated according to the steering information and the moving distance, and the pickers can receive the path guiding text by adopting a low-cost general electronic terminal. Therefore, on one hand, the method and the device can realize path guidance by using the existing monitoring equipment of the warehouse and the general electronic terminal with lower cost, and the AR equipment is not required to be additionally configured for the pickers, so that the cost of path guidance can be reduced. On the other hand, the method and the device can guide the pickers to move according to the steering information and the moving distance, so that the pickers can accurately and quickly determine the goods positions of the goods to be picked. Therefore, the method and the device can accurately guide the pickers to move through a low-cost scheme, and give consideration to cost and guiding effect.
In one embodiment, the facial feature location information may include left ear location coordinates, right ear location coordinates, and nose tip location coordinates. Herein, "left" and "right" may be left and right sides with respect to the order picker as a directional reference, or left and right sides when looking toward the order picker from the front.
It is to be understood that the present application may identify the left ear, the right ear, and the tip of the nose in any manner, as not specifically limited herein. In one embodiment, the human body detection result may be a video frame area where the pickers are located in the warehouse real-time monitoring video through a human body detection frame. The computer equipment can intercept the target video area defined by the human body detection frame from the warehouse real-time monitoring video, and divide the target video area to obtain the skin color area in the target video area. The computer device may determine left ear position coordinates, right ear position coordinates, and nose tip position coordinates, respectively, of the pickers based on the skin tone area. Further, in one example, the computer device may count a gray histogram corresponding to the target video region and obtain a distribution of the skin color region in the target video region based on the gray histogram.
In one embodiment, the computer device may intercept a target video area framed by the human body detection frame from the warehouse real-time monitoring video, and identify the left ear, the right ear and the nose tip from the target video area based on a deep learning algorithm, so as to obtain the position coordinates of the left ear, the position coordinates of the right ear and the position coordinates of the nose tip, respectively.
In one embodiment, the step of determining the gaze direction of the order picker based on the facial feature location information comprises:
respectively taking the left ear position coordinate, the right ear position coordinate and the nose tip position coordinate as three vertexes to construct a triangle;
the barycentric coordinates of the triangle are determined, and a direction from the barycentric coordinates to the nose tip position coordinates is taken as a line-of-sight direction.
Specifically, since the monitoring device is generally installed at a higher position and the hardware configuration of the monitoring device is uneven, in the warehouse real-time monitoring video, the eyes and the mouth of the pickers may have shielding situations or situations of insufficient video definition. For example, when the picker looks at a lower elevation, the eyes may be blocked by the hair and the mouth may be blocked by the nose. Considering that the nose and the ears have a certain bulge height and are easy to capture by the monitoring equipment, the vision direction of the pick person can be determined according to the left ear position coordinate, the right ear position coordinate and the nose tip position coordinate.
Specifically, the computer device may construct a triangle according to the two-ear position coordinates and the nose tip position coordinates of the pick person, where three vertex coordinates of the triangle are the left-ear position coordinate, the right-ear position coordinate, and the nose tip position coordinate, respectively. That is, the first side of the triangle may be a line connecting the left ear position coordinates to the right ear position coordinates, the second side may be a line connecting the right ear position coordinates to the nose tip position coordinates, and the third side may be a line connecting the nose tip position coordinates to the left ear position coordinates. Further, when the warehouse area is smaller, the portrait area of the pickers in the real-time monitoring video of the warehouse is larger, so that the triangle obtained by construction can be an obtuse triangle. When the warehouse area is larger, the portrait area of the pickers in the real-time monitoring video of the warehouse is smaller, and the triangle obtained by construction can be an acute triangle.
After the triangle is constructed, the computer device may determine the barycentric coordinates of the triangle, i.e., the coordinates of the intersection of the three midlines of the triangle. The direction from the barycentric coordinates to the nose tip position coordinates can be determined as the vision direction of the pickers.
In this embodiment, on the one hand, by determining the line of sight direction based on both ears and nose tips, the setting requirements and hardware requirements for the monitoring device can be reduced. On the other hand, the computer equipment takes the left ear position coordinate, the right ear position coordinate and the nose tip position coordinate as three vertexes to construct a triangle, and takes the direction pointing to the nose tip position coordinate from the gravity center coordinate of the triangle as the sight line direction of the pick-up person.
In one embodiment, the steering information may include a steering angle and a steering direction. The steering angle may be an angle that the picker needs to rotate, and the steering direction may be a direction that the picker needs to rotate. For example, when the steering information is rotated 90 ° to the left, the steering angle is 90 °, and the steering direction is rotated to the left.
Determining steering information according to the line of sight direction and the cargo position of the cargo to be picked up, comprising:
taking a direction pointing to a cargo position of the cargo to be picked from the barycentric coordinates as a target direction;
the steering angle and the steering direction are determined based on the line-of-sight direction and the target direction, respectively.
Specifically, the computer device takes as a target direction a direction pointing from the barycentric coordinates of the triangle to the cargo position of the cargo to be picked, and the target direction may be a direction in which the picker is to be oriented after steering adjustment. During the path guidance, the computer device needs to guide the picker to adjust the sight direction of the picker to the target direction so that the picker can accurately and quickly position the goods to be picked.
In the case of determining the target direction, the computer device may determine a steering angle based on the target direction and the line-of-sight direction of the pick person, and determine a steering direction based on the target direction and the line-of-sight direction. Further, in one example, the computer device may calculate an angle between the unit vector of the target direction and the unit vector of the line of sight direction to obtain the steering angle and the steering direction, respectively.
In this way, the computer device can quickly determine the steering angle and steering direction, and can reduce the consumption of computing resources, thereby improving the guidance efficiency and further reducing the cost.
In one embodiment, the step of obtaining the real-time location of the pickers in the warehouse includes: and determining the real-time position based on the human body detection result and preset warehouse pattern information. Because the human body detection result can indicate the position of the pickers in the video picture of the warehouse real-time monitoring video, the computer equipment can determine the real-time position of the pickers in the warehouse according to the position of the pickers in the warehouse real-time monitoring video and preset warehouse pattern information. Therefore, the real-time position of the pickers can be determined in an image recognition mode, so that the pickers can carry the electronic terminals without positioning functions as guiding equipment, the requirements on the electronic terminals can be further reduced, and the cost is further reduced.
In one embodiment, the step of determining the location of the pick-up items in the warehouse comprises:
determining a warehouse picking path corresponding to the picker; the warehouse picking path is pre-generated and is used for indicating the picking sequence of various target cargos and the cargo position of each target cargos; the target goods are goods related to a picking task corresponding to a picker;
Determining the position of the goods to be picked in the warehouse according to the goods picking path and the goods picking progress information of the warehouse; wherein the pick progress information includes a goods identifier for each picked good.
In particular, given that there may be multiple pickers simultaneously in the warehouse, the computer device may determine a warehouse pick path for each picker, respectively, so as to direct each picker to move in the warehouse, respectively, according to the warehouse pick path for each picker. The warehouse picking path corresponding to each picker can be pre-planned by the computer equipment according to the cargoes involved in the picking task corresponding to the picker, and can be used for indicating the picking sequence of various cargoes involved in the picking task and the cargo position of each kind of cargoes.
In the picking process, when the same picking task involves multiple kinds of cargoes, the picker typically picks the cargoes according to a certain order. In the case where the picking task is not completed, there may be a part of the target goods already picked and another part of the target goods not already picked, so that the goods identification of each picked goods may be recorded by the picking schedule information so as to distinguish the picked target goods from the non-picked target goods according to the picking schedule information.
The computer device may determine the next item to be picked by the picker, i.e., determine the item to be picked, according to the warehouse picking path and the picking schedule information, and obtain the location of the item to be picked in the warehouse accordingly. For example, the warehouse picking path may include at least one node, each node corresponds to various target cargos one by one, the computer device may determine the current node according to the picking progress information, determine the next node of the current node in the warehouse picking path, and take the cargos corresponding to the next node as cargos to be picked.
Therefore, the picker can be guided to pick according to the pre-planned warehouse picking path, the goods to be picked do not need to be manually determined and selected, and the picking efficiency can be improved.
In one embodiment, the generating step of the warehouse picking path includes:
acquiring the goods identification of various target goods;
acquiring cargo information of each target cargo according to each cargo identifier; wherein the cargo information of each target cargo includes a cargo position, a cargo weight, and a cargo volume of the target cargo;
and inputting the goods identifications and the goods information of the various target goods into a path planning model obtained by training in advance so as to obtain a warehouse picking path output by the path planning model.
Wherein the cargo identification can be used to uniquely identify each cargo. For example, a brand B commodity of A1 may correspond to different cargo identifications than a brand B commodity of A2, a brand C1 commodity of A1 and a brand C2 commodity of A1 may correspond to different cargo identifications, and each brand C1 commodity of A1 may correspond to the same cargo identification.
Specifically, in planning a warehouse picking path, the computer device may obtain various target cargoes involved in the picking task, and determine a cargo identifier of each target cargo separately. The computer device can determine the goods position, the goods weight and the goods volume of each target goods according to the goods identifier of the target goods, and input the goods identifier, the goods position, the goods weight and the goods volume into the path planning model so that the path planning model plans a reasonable warehouse goods picking path according to the goods position, the goods weight and the goods volume and outputs the path planning model. Thus, a warehouse picking path which is more convenient for carrying goods can be obtained.
Further, in one example, the path planning model may determine an optimal path from the path distance or path complexity as a handling path based on the cargo volume and the cargo weight. When the cargo volume of each target cargo is smaller than the preset volume threshold value and the cargo weight of each target cargo is smaller than the preset weight threshold value, the path planning model can generate and output a warehouse picking path with the shortest path distance. The path planning model may generate and output a warehouse pick path having a path complexity less than a preset complexity threshold when a cargo volume of the at least one target cargo is greater than or equal to a preset volume threshold, or a cargo weight of the at least one target cargo is greater than or equal to a preset weight threshold. Thus, various factors such as path distance and carrying difficulty can be balanced.
In one embodiment, the step of separately acquiring cargo information of each target cargo according to each cargo identification includes:
extracting a target video image from a real-time monitoring video of a warehouse;
inputting each cargo identification and target video image into a cargo identification model obtained by training in advance so as to obtain cargo positions of various target cargos output by the cargo identification model;
and inquiring a pre-constructed cargo information database according to each cargo identifier, and obtaining the cargo weight and the cargo volume of each target cargo.
Specifically, considering that the distribution condition of the cargos in the warehouse may change and the distribution condition of the cargos in different warehouses may be different, the computer device may extract at least one frame of video image from the warehouse real-time monitoring video as the target video image, and input the target video image and each cargo identification into the cargo identification model, so as to respectively identify the corresponding position of each cargo identification in the target video image through the cargo identification model, and output the cargo position of each target cargo according to the positions.
Further, in one example, the cargo identification model may be a model that is trained on the YOLO V4 model using a second training data set. The second training data set may include a plurality of sets of second training data, where each set of second training data may include a pre-collected cargo image, a cargo position labeling result corresponding to the cargo image, and a cargo name corresponding to the cargo image.
Since the cargo weight and cargo volume of each cargo are less changed, the cargo information database may be previously constructed according to the cargo identification, cargo weight and cargo volume of each cargo stored in the warehouse. When acquiring the cargo information of the target cargos, the computer equipment can query the cargo information database according to the cargo identification of each target cargos so as to obtain the cargo weight and the cargo volume of each target cargos respectively.
In this embodiment, the computer device may determine the cargo position based on the cargo identification model and obtain the cargo volume and the cargo weight based on a pre-constructed cargo information database. On the one hand, when the distribution condition of the cargoes in the warehouse is changed, the computer equipment can accurately determine the positions of the cargoes, and further can accurately guide the pickers so as to further improve the guiding effect. On the other hand, by querying the database to obtain the cargo weight and cargo volume, the consumption of computing resources can be reduced to further reduce costs.
The following describes a pick-up path guiding device provided in an embodiment of the present application, and the pick-up path guiding device described below and the pick-up path guiding method described above may be referred to correspondingly with each other.
In one embodiment, the present application provides a pick path guidance device 300. As shown in fig. 3, the apparatus 300 may include:
a cargo position determining module 310 for determining a cargo position of the pick-up cargo in the warehouse;
the five sense organ position information determining module 320 is configured to perform human body detection on the warehouse real-time monitoring video, and determine five sense organ position information of the picker based on a human body detection result;
a steering information determining module 330, configured to determine a line of sight direction of the picker based on the location information of the five sense organs, and determine steering information according to the line of sight direction and the location of the goods to be picked;
a moving distance calculating module 340, configured to obtain a real-time position of the picker in the warehouse, and calculate a moving distance according to the real-time position and a cargo position of the cargo to be picked;
and the guiding module 350 is used for generating a path guiding text according to the moving distance and the steering information and sending the path guiding text to an electronic terminal carried by the picker.
In one embodiment, the five sense organ position information includes left ear position coordinates, right ear position coordinates, and nose tip position coordinates. The steering information determination module 330 of the present application may include a triangle construction unit and a line-of-sight direction determination unit. The triangle construction unit is used for constructing a triangle by taking the left ear position coordinate, the right ear position coordinate and the nose tip position coordinate as three vertexes respectively. The line-of-sight direction determining unit is configured to determine barycentric coordinates of the triangle, and to take, as the line-of-sight direction, a direction from the barycentric coordinates to the nose tip position coordinates.
In one embodiment, the steering information includes a steering angle and a steering direction. The steering information determination module 330 of the present application may further include a target direction determination unit and a steering information determination unit. The target direction determining unit is used for taking a direction pointing to the goods position of the goods to be picked from the barycentric coordinates as a target direction. The steering information determining unit is used for determining the steering angle and the steering direction according to the sight line direction and the target direction.
In one embodiment, the moving distance calculating module 340 of the present application includes a real-time position determining unit for determining the real-time position based on the human body detection result and preset warehouse pattern information.
In one embodiment, the cargo position determination module 310 of the present application includes a path determination unit and a cargo position determination unit. The path determining unit is used for determining a warehouse picking path corresponding to the picker; the warehouse picking path is pre-generated and is used for indicating the picking sequence of various target cargos and the cargo position of each target cargos; the target goods are goods related to the picking task corresponding to the picker. The goods position determining unit is used for determining the goods position of the goods to be picked in the warehouse according to the warehouse goods picking path and the goods picking progress information; wherein the pick progress information includes a goods identifier for each picked good.
In one embodiment, the pick path guidance of the present application may further include a goods identification acquisition module, a goods information acquisition module, and a path acquisition module. The goods identifier acquisition module is used for acquiring the goods identifiers of various target goods. The goods information acquisition module is used for acquiring the goods information of each target goods according to each goods identifier; wherein the cargo information of each of the target cargo includes a cargo position, a cargo weight, and a cargo volume of the target cargo. And the path acquisition module is used for inputting the goods identifications and the goods information of the target goods into a path planning model which is trained in advance so as to acquire the warehouse picking path which is output by the path planning model.
In one embodiment, the cargo information acquisition module of the present application includes a target video image extraction unit, a cargo position identification unit, and a query unit. The target video image extraction unit is used for extracting target video images from the warehouse real-time monitoring video. The goods position identification unit is used for inputting the goods identifications and the target video images into a pre-trained goods identification model so as to acquire the goods positions of the various target goods output by the goods identification model. And the inquiring unit is used for inquiring a pre-constructed goods information database according to the goods identifications and obtaining the goods weight and the goods volume of each target goods.
In one embodiment, the present application also provides a storage medium having stored therein computer readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the pick path guidance method as in any embodiment.
In one embodiment, the present application also provides a computer device having stored therein computer readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the pick path guidance method as in any embodiment.
Schematically, fig. 4 is a schematic internal structure of a computer device provided in an embodiment of the present application, where in an example, the computer device may be a server. Referring to FIG. 4, computer device 900 includes a processing component 902 that further includes one or more processors, and memory resources represented by memory 901, for storing instructions, such as applications, executable by processing component 902. The application program stored in the memory 901 may include one or more modules each corresponding to a set of instructions. In addition, the processing component 902 is configured to execute instructions to perform the steps of the pick path guidance method of any of the embodiments described above.
The computer device 900 may also include a power component 903 configured to perform power management of the computer device 900, a wired or wireless network interface 904 configured to connect the computer device 900 to a network, and an input output (I/O) interface 905. The computer device 900 may operate based on an operating system stored in memory 901, such as Windows Server TM, mac OS XTM, unix, linux, free BSDTM, or the like.
It will be appreciated by those skilled in the art that the internal structure of the computer device shown in the present application is merely a block diagram of some of the structures related to the aspects of the present application and does not constitute a limitation of the computer device to which the aspects of the present application apply, and that a particular computer device may include more or less components than those shown in the figures, or may combine some of the components, or have a different arrangement of the components.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. Herein, "a," "an," "the," and "the" may also include plural forms, unless the context clearly indicates otherwise. Plural means at least two cases such as 2, 3, 5 or 8, etc. "and/or" includes any and all combinations of the associated listed items.
In the present specification, each embodiment is described in a progressive manner, and each embodiment focuses on the difference from other embodiments, and may be combined according to needs, and the same similar parts may be referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (7)
1. A method of routing a pick path, the method comprising:
determining a warehouse picking path corresponding to the picker; the warehouse picking path is pre-generated and is used for indicating the picking sequence of various target cargos and the cargo position of each target cargos; the target goods are goods related to a picking task corresponding to the picker;
Determining the goods position of the goods to be picked in the warehouse according to the goods picking path and the goods picking progress information of the warehouse; wherein the picking schedule information comprises a goods identifier of each picked goods;
human body detection is carried out on the warehouse real-time monitoring video, and the five sense organ position information of the pickers is determined based on the human body detection result; the five sense organs position information comprises a left ear position coordinate, a right ear position coordinate and a nose tip position coordinate;
respectively taking the left ear position coordinate, the right ear position coordinate and the nose tip position coordinate as three vertexes to construct a triangle;
determining barycentric coordinates of the triangle, and taking a direction pointing from the barycentric coordinates to the nose tip position coordinates as a sight line direction;
determining steering information according to the sight line direction and the goods position of the goods to be picked;
acquiring a real-time position of the picker in the warehouse, and calculating a moving distance according to the real-time position and the goods position of the goods to be picked;
generating a path guiding text according to the moving distance and the steering information, and sending the path guiding text to an electronic terminal carried by the picker;
the step of generating the warehouse picking path comprises the following steps:
Acquiring the goods identification of various target goods;
acquiring cargo information of each target cargo according to each cargo identifier; wherein the cargo information of each target cargo comprises the cargo position, the cargo weight and the cargo volume of the target cargo;
and inputting the goods identifications and the goods information of the target goods into a path planning model which is trained in advance to obtain the warehouse picking path which is output by the path planning model.
2. The method of claim 1, wherein the steering information includes a steering angle and a steering direction;
the step of determining steering information according to the sight line direction and the goods position of the goods to be picked comprises the following steps:
taking a direction pointing to the goods position of the goods to be picked from the barycentric coordinates as a target direction;
and respectively determining the steering angle and the steering direction according to the sight line direction and the target direction.
3. The method of claim 1, wherein the step of obtaining the real-time location of the picker in the warehouse comprises:
and determining the real-time position based on the human body detection result and preset warehouse pattern information.
4. The method of claim 1, wherein the step of separately acquiring cargo information for each of the target cargo based on each of the cargo identifications comprises:
extracting a target video image from the warehouse real-time monitoring video;
inputting each cargo identifier and each target video image into a cargo identification model obtained through training in advance so as to obtain cargo positions of various target cargos output by the cargo identification model;
and inquiring a pre-constructed cargo information database according to each cargo identifier, and obtaining the cargo weight and the cargo volume of each target cargo.
5. A pick path guidance device, the device comprising:
the goods position determining module is used for determining a warehouse goods picking path corresponding to the goods picker and determining the goods position of the goods to be picked in the warehouse according to the warehouse goods picking path and the goods picking progress information; the warehouse picking path is pre-generated and is used for indicating the picking sequence of various target cargos and the cargo position of each target cargos; the target goods are goods related to a picking task corresponding to the picker; the picking schedule information comprises a goods identifier of each picked goods;
The five sense organ position information determining module is used for detecting human bodies of warehouse real-time monitoring videos and determining the five sense organ position information of the pickers based on human body detection results; the five sense organs position information comprises a left ear position coordinate, a right ear position coordinate and a nose tip position coordinate;
the steering information determining module is used for respectively constructing a triangle by taking the left ear position coordinate, the right ear position coordinate and the nose tip position coordinate as three vertexes, determining the gravity center coordinate of the triangle, and taking the direction pointing to the nose tip position coordinate from the gravity center coordinate as the sight line direction; the system is also used for determining steering information according to the sight line direction and the goods position of the goods to be picked;
the moving distance calculating module is used for acquiring the real-time position of the picker in the warehouse and calculating the moving distance according to the real-time position and the goods position of the goods to be picked;
the guiding module is used for generating a path guiding text according to the moving distance and the steering information and sending the path guiding text to an electronic terminal carried by the picker;
the device further comprises a goods identifier acquisition module, a goods information acquisition module and a path acquisition module;
The goods identifier acquisition module is used for acquiring the goods identifiers of various target goods;
the goods information acquisition module is used for acquiring the goods information of each target goods according to each goods identifier; wherein the cargo information of each target cargo comprises the cargo position, the cargo weight and the cargo volume of the target cargo;
and the path acquisition module is used for inputting the goods identifications and the goods information of the target goods into a path planning model obtained by training in advance so as to acquire the warehouse picking path output by the path planning model.
6. A storage medium having stored therein computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of the pick path guidance method of any one of claims 1 to 5.
7. A computer device, comprising: one or more processors, and memory;
stored in the memory are computer readable instructions which, when executed by the one or more processors, perform the steps of the pick path guidance method of any one of claims 1 to 5.
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| CN116320273A (en) * | 2021-12-06 | 2023-06-23 | 汉海信息技术(上海)有限公司 | Video data processing method and device |
| CN114627542A (en) * | 2022-03-31 | 2022-06-14 | 中国工商银行股份有限公司 | Eye movement position determination method and device, storage medium and electronic equipment |
| CN115480511A (en) * | 2022-09-16 | 2022-12-16 | 科大讯飞股份有限公司 | Robot interaction method, device, storage medium and equipment |
| CN116229469A (en) * | 2022-11-28 | 2023-06-06 | 北京亮亮视野科技有限公司 | Multi-target goods picking system and method based on AR technology |
| CN116309873A (en) * | 2023-03-20 | 2023-06-23 | 惠州市德赛西威智能交通技术研究院有限公司 | Acquisition system, method, computing device and storage medium for line-of-sight data samples |
| CN116477262A (en) * | 2023-04-14 | 2023-07-25 | 珠海格力智能装备有限公司 | Robot pickup method, robot pickup device, computer readable storage medium and warehouse system |
| CN116415794A (en) * | 2023-04-18 | 2023-07-11 | 北京休恩博得科技股份有限公司 | AR (augmented reality) glasses-based warehouse-in and warehouse-out method and intelligent warehouse system |
| CN116803549A (en) * | 2023-06-29 | 2023-09-26 | 漳州立达信光电子科技有限公司 | Goods sorting method, goods sorting device, electronic equipment and storage medium |
| CN116883977A (en) * | 2023-07-17 | 2023-10-13 | 阿维塔科技(重庆)有限公司 | Passenger state monitoring method and device, terminal equipment and vehicle |
| CN116823123A (en) * | 2023-08-30 | 2023-09-29 | 青岛宇方机器人工业股份有限公司 | Warehouse management method and device based on AR positioning, electronic equipment and medium |
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