CN112418731A - UWB and big data based manual forklift scheduling method and system - Google Patents
UWB and big data based manual forklift scheduling method and system Download PDFInfo
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Abstract
The invention discloses a manual forklift scheduling method and system based on UWB and big data, which are characterized in that a big database is constructed according to task generation conditions on a previous production line by obtaining the task generation conditions on the previous production line, then a task generation hot spot area in a future period is predicted in real time based on the big database, the position of a forklift is positioned based on UWB, an idle forklift is assigned to move to the hot spot area to wait, the idle forklift can be deployed in advance, and the material handling efficiency is improved; receiving the material transport request, establishing the transport task, then assigning the transport task for the nearest fork truck, the fork truck carries out the goods transport operation, has realized artifical fork truck's automatic dispatch, has strengthened the stability of dispatch work, has improved the handling efficiency of material greatly.
Description
Technical Field
The invention relates to the technical field of industrial automation, in particular to a forklift scheduling method and system based on UWB and big data.
Background
With the increasing development of industrial automation, the automation degree of a factory production line is gradually improved, but at present, a manual forklift driven by a forklift operator is still an important ring for material handling.
The work flow of the traditional manual forklift has certain defects in the industrial automation background, and is mainly characterized in that the dispatching flow of the traditional manual forklift still depends on forms of oral delivery, telephone, talkback and the like in most of times, the dispatching mode enables the forklift to have low efficiency when a logistics carrying task is executed, the dispatching efficiency depends on the operation experience of a forklift driver, and the dispatching efficiency has great randomness and instability. In addition, because the driving selection of workers has certain uncontrollable property, the parking position of the forklift when no carrying task exists also influences the efficiency of material carrying, so that the scheduling problem of the forklift also needs to pay attention to the parking rest area of the forklift, and the influence on the efficiency of material carrying caused by the excessively long path distance between a parking point and a task point is avoided.
Disclosure of Invention
In order to solve the problems, the inventor provides a forklift scheduling method and system based on UWB and big data, the automatic scheduling of a manual forklift can be realized by combining the cargo handling requirements on a production line, and the material handling efficiency is effectively improved.
According to a first aspect, the invention provides a manual forklift scheduling method based on UWB and big data, which comprises the following steps:
step S1: acquiring a task generation condition on a previous production line, constructing a big database according to the task generation condition, and updating data information in the big database in real time;
step S2: predicting a task generation hot spot area in a future period of time in real time based on a large database, positioning a forklift in real time, acquiring forklift position information, and assigning an idle forklift to move to the hot spot area to wait based on the forklift position information;
step S3: receiving a material carrying request and creating a carrying task;
step S4: judging whether the forklift waiting in the hot spot area is closest to a loading place or not based on the forklift position information, and if so, issuing the carrying task to the waiting forklift; if the distance is not the nearest distance, the carrying task is sent to the forklift with the nearest distance;
step S5: and (5) transferring the forklift to complete the carrying task.
Further, the step of assigning an idle forklift to move to the hot spot area for waiting comprises:
step S21: acquiring the operation condition of the forklift and traversing forklift information;
step S22: judging whether the forklift is in an idle state or not according to the forklift operation condition and the forklift information, and if the forklift is in the idle state, assigning the forklift to move to the hot spot area to wait; if the mobile terminal is in the non-idle state, repeating the step S21 until a forklift enters the hot spot area to wait.
Further, the step S4 further includes:
receiving forklift feedback information, and binding the carrying task with the forklift if the feedback information is accepted; if the feedback information is overtime or refused, the task is issued again until the feedback information is accepted.
Further, the step S5 further includes:
step S51: receiving a loading confirmation request after the loading is finished;
step S52: carrying out loading error-proofing verification based on the loading cargo position information and the current forklift position information, and if the verification is passed, carrying away the cargo; if the verification is not passed, the forklift carries out loading again until the verification is passed;
step S53: after the goods are transported to the unloading position, receiving an unloading confirmation request;
step S54: based on the unloading goods position information and the current forklift position information, unloading error-proofing verification is carried out, and if the verification passes, the carrying task is completed; if the verification is not passed, unloading is carried out again until the verification is passed.
Further, the step of performing loading error proofing includes:
step S521: acquiring loading goods position information and current forklift position information; the loading location information includes: the current loading position information and the loading position information in the carrying task;
step S522: comparing the current forklift position information with the loading position information in the carrying task, if the current forklift position information is the same as the loading position information in the carrying task, passing the verification, and carrying away the goods; and if the loading cargo space information in the current forklift position information carrying task is different, the verification fails.
Further, the step S522 further includes:
if the current forklift position information is the same as the loading cargo position information in the carrying task, comparing the current forklift position information with the current loading cargo position information, and if the current forklift position information is the same as the current loading cargo position information, passing the verification and carrying away the cargo; and if the current forklift position information is different from the current loading cargo space information, the verification fails.
Further, the step of performing discharge error proofing verification includes:
step S541: acquiring unloading goods position information and current forklift position information, wherein the unloading goods position information comprises: the current unloading cargo position information and the unloading cargo position information in the carrying task;
step S542: comparing the current forklift position information with unloading goods position information in the carrying task, if the current forklift position information is the same as the unloading goods position information in the carrying task, checking to pass, and unloading; and if the unloading goods position information in the current forklift position information carrying task is different, the verification fails.
Further, the step S542 further includes:
if the current forklift position information is the same as the unloading cargo position information in the carrying task, comparing the current forklift position information with the current unloading cargo position information, and if the current forklift position information is the same as the current unloading cargo position information, checking to pass and unloading; and if the current forklift position information is different from the current unloading cargo space information, the verification fails.
According to a second aspect, the invention also provides a manual forklift dispatching system based on UWB and big data, which comprises: the system comprises a UWB positioning system, a dispatching subsystem, a plurality of UWB positioning base stations distributed in a warehouse, UWB positioning tags arranged on a forklift and a vehicle-mounted terminal, wherein the UWB positioning system and the dispatching subsystem run on a server, the vehicle-mounted terminal is connected with the dispatching subsystem, and the UWB positioning tags are connected with the UWB positioning system;
the UWB positioning system, the UWB positioning tag and the plurality of UWB positioning base stations are matched and used for acquiring the position information of the forklift in real time;
the scheduling subsystem is used for constructing a big database according to the task generation condition by acquiring the task generation condition on the conventional production line and updating data information in the big database in real time; the system is also used for predicting a task generation hot spot area in a future period of time in real time based on the big database, and assigning an idle forklift to move to the hot spot area to wait based on the forklift position information; the system is also used for receiving a material carrying request, creating a carrying task, sending the carrying task to a waiting forklift, and transferring the forklift to complete the carrying task;
the vehicle-mounted terminal is used for receiving the carrying task.
Further, the system further comprises: the system comprises a cargo position sensor arranged on a cargo position, wherein the cargo position sensor is used for acquiring current loading cargo position information or current unloading cargo position information;
the scheduling subsystem is also used for receiving the loading request and the unloading request and carrying out loading error-proof verification and unloading error-proof verification.
Compared with the prior art, the invention has the following beneficial effects:
the material handling needs and the big data that will combine to produce the line combine, can predict the production region of future material handling task, simultaneously, carry out real-time location to fork truck based on UWB again, can send idle fork truck to the rest point near the production region of future material handling task waits, has both realized artifical fork truck's automatic dispatch, has strengthened the stability of dispatch work, has improved the handling efficiency of material greatly.
Drawings
FIG. 1 is a flow chart of a manual forklift scheduling method based on UWB and big data provided by the invention;
FIG. 2 is a flowchart of the steps for assigning an idle truck to move to the hot spot area to wait;
fig. 3 is a flowchart of step S5;
FIG. 4 is a system diagram of a UWB and big data based manual forklift dispatching system provided by the invention;
fig. 5 is a schematic view of an application scenario of the manual forklift scheduling system based on UWB and big data provided by the present invention.
Detailed Description
The present invention will be described in further detail with reference to the following detailed description and accompanying drawings. Wherein like elements in different embodiments are numbered with like associated elements. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, those skilled in the art will readily recognize that some of the features may be omitted or replaced with other elements, materials, methods in different instances. In some instances, certain operations related to the present invention have not been shown or described in the specification in order to avoid obscuring the present invention from the excessive description, and it is not necessary for those skilled in the art to describe these operations in detail, so that they can be fully understood from the description in the specification and the general knowledge in the art.
Furthermore, the features, operations, or characteristics described in the specification may be combined in any suitable manner to form various embodiments. Also, the various steps or actions in the method descriptions may be transposed or transposed in order, as will be apparent to one of ordinary skill in the art. Thus, the various sequences in the specification and drawings are for the purpose of describing certain embodiments only and are not intended to imply a required sequence unless otherwise indicated where such sequence must be followed.
The invention improves the existing manual forklift dispatching system, performs positioning through UWB, acquires position information, performs heat setting area prediction through big data, performs error-proofing verification in the loading and unloading process, reduces manual allocation work, reduces subjective errors and greatly improves the carrying efficiency. It should be understood that, like the existing manual forklift dispatching system, an indoor map is drawn through a positioning system, and the manual forklift is dispatched based on the map, and the map drawing method is the same as that of the conventional manual forklift dispatching system, and the specific process is not repeated herein.
The first embodiment is as follows:
as shown in fig. 1, the present invention provides a manual forklift scheduling method based on UWB and big data, which includes the following steps:
step S1: acquiring the task generation condition on the conventional production line, constructing a large database according to the task generation condition, and updating data information in the large database in real time.
Step S2: the method comprises the steps of predicting a hot spot area generated by a task in a future period of time in real time based on a large database, positioning a forklift in real time, obtaining forklift position information, and assigning an idle forklift to move to the hot spot area to wait based on the forklift position information. The real-time positioning of the forklift is mainly realized by UWB, positioning is carried out by measuring the transmission delay differences of different UWB base stations and the vehicle-mounted terminal by using a TDOA positioning algorithm, the positioning technology is the prior art, and details are not repeated herein.
Step S3: and receiving a material conveying request and creating a conveying task.
Step S4: judging whether the forklift waiting in the hot spot area is closest to the loading place or not based on the position information of the forklift, and if so, issuing a carrying task to the waiting forklift; and if the distance is not the nearest distance, the carrying task is assigned to the forklift with the nearest distance.
Step S5: and (5) transferring the forklift to complete the carrying task.
Specifically, as shown in fig. 2, the step of assigning an idle forklift to move to the hot spot area for waiting includes:
step S21: acquiring the operation condition of the forklift, traversing forklift information, and updating the forklift operation condition in real time by a forklift scheduling system; the forklift information is forklift information registered in the system.
Step S22: judging whether the forklift is in an idle state or not according to the operation condition of the forklift and the information of the forklift, and if the forklift is in the idle state, assigning the forklift to move to the hot spot area to wait; if the mobile terminal is in the non-idle state, repeating the step S21 until a forklift enters the hot spot area to wait.
Further, in step S4, after the transportation task reaches the forklift, the forklift driver may choose to accept the transportation task or reject the transportation task, transmit the feedback information to the system through the vehicle-mounted terminal, and the system makes a judgment after receiving the feedback information, and if the feedback information is accepted, the transportation task is bound with the forklift; if the feedback information is overtime or refused, the task is issued again until the feedback information is accepted.
Further, as shown in fig. 3, after the forklift receives the transportation task, the forklift driver performs the loading operation, and after the loading operation is completed, the following steps are performed:
step S51: a shipment confirmation request is received.
Step S52: carrying out loading error-proofing verification based on the loading cargo position information and the current forklift position information, and if the verification is passed, carrying away the cargo; and if the verification is not passed, the forklift carries out loading again until the verification is passed. The specific checking process comprises the following steps:
step S521: and acquiring the loading cargo space information and the current forklift position information. The loading position information includes: current loading location information and loading location information in the handling task. The current forklift position information is obtained by UWB positioning, the current loading cargo position information is obtained from a position sensor on the cargo position, and the loading cargo position information in the carrying task is the cargo position carried in the material carrying request.
Step S522: comparing the current forklift position information with the loading cargo position information in the carrying task, if the current forklift position information is the same as the loading cargo position information in the carrying task, comparing the current forklift position information with the current loading cargo position information, and if the current forklift position information is the same as the current loading cargo position information, passing the verification and transporting the cargo away; otherwise, the verification fails, and the loading operation is carried out again. And if the loading cargo position information in the current forklift position information carrying task is different, the verification fails, and the loading operation is carried out again.
Step S53: after the goods are transported to the unloading position, the unloading confirmation request is received.
Step S54: based on the unloading goods position information and the current forklift position information, unloading error-proofing verification is carried out, and if the verification passes, the carrying task is completed; if the verification is not passed, unloading is carried out again until the verification is passed. Wherein, the step of carrying out discharge error proofing verification includes:
step S541: acquiring unloading goods position information and current forklift position information, wherein the unloading goods position information comprises: current unload cargo space information and unload cargo space information in the transfer task. The current forklift position information is obtained by UWB positioning, the current unloading goods position information is obtained from a position sensor on the goods position, and the unloading goods position information in the carrying task is the goods position carried in the goods and materials carrying request.
Step S542: comparing the current forklift position information with unloading goods position information in the carrying task, if the current forklift position information is the same as the unloading goods position information in the carrying task, comparing the current forklift position information with the current unloading goods position information, and if the current forklift position information is the same as the current unloading goods position information, checking to pass and unloading; and if the unloading goods position information in the current forklift position information carrying task is different, the verification fails, and the unloading operation is carried out again. And if the current forklift position information is different from the current unloading cargo space information, the verification fails, and the unloading operation is carried out again.
As shown in fig. 3, the present invention further provides a manual forklift dispatching system based on UWB and big data, which comprises: the system comprises a UWB positioning system 1, a dispatching subsystem 2, a plurality of UWB positioning base stations 3 distributed in a warehouse, UWB positioning tags 41 and vehicle-mounted terminals 42 arranged on a forklift 4, a cargo position sensor (not shown) arranged on a cargo position, wherein the UWB positioning system 1 and the dispatching subsystem 2 run on a server, the server is a server carried by a conventional dispatching system, the server is connected with upper systems such as an MES (manufacturing execution system), information of cargos to be carried is managed by the upper systems, it is required to be explained that the server and the upper systems are the prior art and are also the server and the upper systems used in the current forklift dispatching system, and the description is omitted. The vehicle-mounted terminal 42 is connected with the dispatching subsystem 1 through WIFI, the UWB positioning tags are connected with the UWB positioning system, and the UWB positioning system, the UWB positioning tags and the UWB positioning base stations are matched with one another to acquire the position information of the forklift 4 in real time. A cargo position sensor (not shown) is used to obtain current loading cargo position information or current unloading cargo position information.
The in-vehicle terminal 42 is configured to receive a transport task and also configured to transmit a loading request or a unloading request.
The scheduling subsystem 1 is used for establishing a big database according to the task generation condition by acquiring the task generation condition on the previous production line and updating data information in the big database in real time; the system is also used for predicting a task generation hot spot area in a future period of time in real time based on the big database, and assigning an idle forklift 4 to move to the hot spot area to wait based on the forklift position information; the system is also used for receiving a material carrying request, creating a carrying task, sending the carrying task to the waiting forklift 4 and transferring the forklift 4 to complete the carrying task; the dispatching subsystem 1 is also used for receiving loading requests and unloading requests from the vehicle-mounted terminal 42 and carrying out loading error-proof verification and unloading error-proof verification.
For example, as shown in fig. 5, after the large database is built in the dispatching subsystem 1, the large database is updated in real time, a hot spot area generated by a task in a future period is predicted, and meanwhile, the UWB system 2 sends the position information of the forklift to the dispatching subsystem 1 in real time. The dispatching subsystem 1 judges whether the forklift is in an idle state, and if the forklift is in the idle state, the forklift is assigned to move to a rest area 6 near a hot spot area to wait; and if the forklift is in the non-idle state, reselecting the forklift for judgment until the selected forklift is idle, and then waiting for a rest area 6 near a hot spot area where the idle forklift moves. After the upper system 5 sends the material transport request to the scheduling subsystem 1, the scheduling subsystem 1 establishes a transport task, then judges whether the distance to the forklift in the hot spot area 6 is nearest, if so, the transport task is issued to the forklift, if not, the nearest forklift is searched for and the task is issued, after the task is issued, a forklift driver operates through the vehicle-mounted terminal 42, the transport task is accepted or rejected, if so, the forklift is moved to the loading area 7 for loading, and if the transport task is rejected or overtime, the scheduling subsystem 1 reselects the forklift to issue the task until the task is accepted. After the forklift is loaded, a loading error-proofing verification request is sent to the dispatching subsystem 1, the dispatching subsystem 1 conducts loading error-proofing verification according to the current forklift position information, the loading cargo position information in the carrying task and the current loading cargo position information, if the verification is passed, the cargo is carried away, and if the verification is not passed, the loading is conducted again until the verification is passed. Fork truck transports the goods to unloading district 8 afterwards, when unloading, also need carry out the mistake proofing check-up equally, pass through until the mistake proofing check-up, and whole dispatch process is accomplished to fork truck, and fork truck returns to idle state again this moment.
The present invention has been described in terms of specific examples, which are provided to aid understanding of the invention and are not intended to be limiting. For a person skilled in the art to which the invention pertains, several simple deductions, modifications or substitutions may be made according to the idea of the invention.
Claims (10)
1. A manual forklift scheduling method based on UWB and big data is characterized by comprising the following steps:
step S1: acquiring a task generation condition on a previous production line, constructing a big database according to the task generation condition, and updating data information in the big database in real time;
step S2: predicting a task generation hot spot area in a future period of time in real time based on a large database, positioning a forklift in real time, acquiring forklift position information, and assigning an idle forklift to move to the hot spot area to wait based on the forklift position information;
step S3: receiving a material carrying request and creating a carrying task;
step S4: judging whether the forklift waiting in the hot spot area is closest to a loading place or not based on the forklift position information, and if so, issuing the carrying task to the waiting forklift; if the distance is not the nearest distance, the carrying task is sent to the forklift with the nearest distance;
step S5: and (5) transferring the forklift to complete the carrying task.
2. The UWB and big data based manual forklift scheduling method of claim 1, wherein said step of assigning an idle forklift to move to said hot spot area to wait comprises:
step S21: acquiring the operation condition of the forklift and traversing forklift information;
step S22: judging whether the forklift is in an idle state or not according to the forklift operation condition and the forklift information, and if the forklift is in the idle state, assigning the forklift to move to the hot spot area to wait; if the mobile terminal is in the non-idle state, repeating the step S21 until a forklift enters the hot spot area to wait.
3. The UWB and big data based manual forklift scheduling method of claim 1, wherein said step S4 further comprises:
receiving forklift feedback information, and binding the carrying task with the forklift if the feedback information is accepted; if the feedback information is overtime or refused, the task is issued again until the feedback information is accepted.
4. The UWB and big data based manual forklift scheduling method of any one of claims 1 to 3, wherein the step S5 further comprises:
step S51: dispatching the forklift to load, and receiving a loading confirmation request after the loading is finished;
step S52: carrying out loading error-proofing verification based on the loading cargo position information and the current forklift position information, and if the verification is passed, carrying away the cargo; if the verification is not passed, the forklift carries out loading again until the verification is passed;
step S53: after the goods are transported to the unloading position, receiving an unloading confirmation request;
step S54: based on the unloading goods position information and the current forklift position information, unloading error-proofing verification is carried out, and if the verification passes, the carrying task is completed; if the verification is not passed, unloading is carried out again until the verification is passed.
5. The UWB and big data based manual forklift scheduling method of claim 4, wherein the step of performing loading error-proofing verification comprises:
step S521: acquiring loading goods position information and current forklift position information; the loading location information includes: the current loading position information and the loading position information in the carrying task;
step S522: comparing the current forklift position information with the loading position information in the carrying task, if the current forklift position information is the same as the loading position information in the carrying task, passing the verification, and carrying away the goods; and if the loading cargo space information in the current forklift position information carrying task is different, the verification fails.
6. The UWB and big data based manual forklift scheduling method according to claim 5, wherein said step S522 further comprises:
if the current forklift position information is the same as the loading cargo position information in the carrying task, comparing the current forklift position information with the current loading cargo position information, and if the current forklift position information is the same as the current loading cargo position information, passing the verification and carrying away the cargo; and if the current forklift position information is different from the current loading cargo space information, the verification fails.
7. The UWB and big data based manual forklift scheduling method of claim 4, wherein the step of performing unloading error proofing verification comprises:
step S541: acquiring unloading goods position information and current forklift position information, wherein the unloading goods position information comprises: the current unloading cargo position information and the unloading cargo position information in the carrying task;
step S542: comparing the current forklift position information with unloading goods position information in the carrying task, if the current forklift position information is the same as the unloading goods position information in the carrying task, checking to pass, and unloading; and if the unloading goods position information in the current forklift position information carrying task is different, the verification fails.
8. The UWB and big data based manual forklift scheduling method of claim 7, wherein said step S542 further comprises:
if the current forklift position information is the same as the unloading cargo position information in the carrying task, comparing the current forklift position information with the current unloading cargo position information, and if the current forklift position information is the same as the current unloading cargo position information, checking to pass and unloading; and if the current forklift position information is different from the current unloading cargo space information, the verification fails.
9. An artificial forklift dispatching system based on UWB and big data is characterized by comprising: the system comprises a UWB positioning system, a dispatching subsystem, a plurality of UWB positioning base stations distributed in a warehouse, UWB positioning tags arranged on a forklift and a vehicle-mounted terminal, wherein the UWB positioning system and the dispatching subsystem run on a server, the vehicle-mounted terminal is connected with the dispatching subsystem, and the UWB positioning tags are connected with the UWB positioning system;
the UWB positioning system, the UWB positioning tag and the plurality of UWB positioning base stations are matched and used for acquiring the position information of the forklift in real time;
the scheduling subsystem is used for constructing a big database according to the task generation condition by acquiring the task generation condition on the conventional production line and updating data information in the big database in real time; the system is also used for predicting a task generation hot spot area in a future period of time in real time based on the big database, and assigning an idle forklift to move to the hot spot area to wait based on the forklift position information; the system is also used for receiving a material carrying request, creating a carrying task, sending the carrying task to a waiting forklift, and transferring the forklift to complete the carrying task;
the vehicle-mounted terminal is used for receiving the carrying task.
10. The UWB and big data based manual forklift dispatch system of claim 9, further comprising: the system comprises a cargo position sensor arranged on a cargo position, wherein the cargo position sensor is used for acquiring current loading cargo position information or current unloading cargo position information;
the scheduling subsystem is also used for receiving the loading request and the unloading request and carrying out loading error-proof verification and unloading error-proof verification.
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