CN116453366A - Automatic driving forklift traffic planning method based on warehouse bin coordinates - Google Patents
Automatic driving forklift traffic planning method based on warehouse bin coordinates Download PDFInfo
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- 238000011156 evaluation Methods 0.000 claims description 8
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096708—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control
- G08G1/096725—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control where the received information generates an automatic action on the vehicle control
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/096805—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/0969—Systems involving transmission of navigation instructions to the vehicle having a display in the form of a map
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
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Abstract
The invention discloses an automatic driving forklift traffic planning method based on warehouse bin coordinates, which belongs to the technical field of unmanned vehicle traffic planning and comprises the following steps: when no one deploys to a new storage environment, guiding a guide vehicle to advance on a traffic route by an operator, and generating a traffic route map under the current storage environment; the target vehicle runs according to the corresponding traffic route map; after the goods reach the storage shelf, the identification and the positioning of the label content on the storage shelf are completed through the scanning of the camera to each angle, and corresponding goods processing is performed based on the identification and the positioning data; an operator automatically creates and generates a traffic route map in a storage environment through a laser radar installed on a forklift in a manual forklift dragging mode; different from the laser SLAM probability map, the traffic route map constrains the passable range of the forklift, and the forklift path planning range is limited to improve the safety and reliability of automatic forklift path planning in a complex storage environment.
Description
Technical Field
The invention belongs to the technical field of unmanned vehicle traffic planning in storage, and particularly relates to an automatic driving forklift traffic planning method based on storage bin coordinates.
Background
With the maturation and progress of automatic driving technology, unmanned vehicles have more application scenes. At present, the unmanned automatic forklift is widely applied in the field of storage, and replaces manpower in storage to carry and transport goods; although the mature and perfect automatic driving technology can replace manual work by an unmanned vehicle, the prior technical scheme still has certain defects in the application of the unmanned vehicle; in order to perform unmanned vehicle path planning, the current technical scheme often needs to generate a corresponding storage environment map, then perform unmanned vehicle path planning based on the storage environment map, the existing path planning algorithm and the like, and needs a certain professional ability of staff; when the warehouse has variation, corresponding staff is required to plan the route again by using related knowledge; the traffic planning mode is complicated, and particularly, with the wide application of the unmanned vehicle, small-scale users are difficult to independently carry out corresponding traffic planning, and corresponding technicians are required to be used for carrying out traffic planning, so that the unmanned vehicle has a certain restriction on application sinking; therefore, in order to realize the convenient operation of unmanned vehicle traffic planning, the invention provides an automatic driving forklift traffic planning method based on storage bin coordinates.
Disclosure of Invention
In order to solve the problems of the scheme, the invention provides an automatic driving forklift traffic planning method based on warehouse bin coordinates.
The aim of the invention can be achieved by the following technical scheme:
an automatic driving forklift traffic planning method based on warehouse bin coordinates, comprising the following steps:
when the unmanned vehicle is deployed in a new storage environment, guiding the guided vehicle to advance on a traffic route by an operator, and generating a traffic route map in the current storage environment;
when the vehicle has a task, the target vehicle runs according to the corresponding traffic route map; after the goods reach the storage shelf, the identification and the positioning of the label content on the storage shelf are completed through the scanning of the camera to each angle, and corresponding goods processing including inventory and goods taking are performed based on the identification and the positioning data.
Further, when the cameras identify the shelves, the cameras synchronously judge whether the positions of the shelves are empty.
Further, the traffic route map generating method comprises the following steps:
and the operator selects a single-row or double-row mode, the guided vehicle is guided to run on the corresponding route, the passing width of the corresponding target vehicle is generated in real time, and after the guided vehicle is guided, a corresponding traffic route map is generated based on the passing area corresponding to the passing width.
Further, the traffic route map generating method comprises the following steps:
and acquiring safety distances on two sides of the walking route in real time, judging the number of the walking ways according to the safety distances, planning the traffic route based on the obtained number of the walking ways, and generating a traffic route map.
Further, in the actual application process, the number of the basic channels is only the number of the channels corresponding to the single channel and the double channels; for the situation that the number of the roads is one, the traffic route is a route through which a guide vehicle pulls; for the situation that the number of the roads is two, the traffic route is offset to two sides by taking the traction route of the guide vehicle as a reference to form two sections of parallel routes, and when the two sections of parallel routes are generated, a user can prescribe the driving direction of each path; and so on.
Further, when the target vehicle works, the target vehicle needs to operate according to a preset passing rule.
Further, the rules for the intersection preferential traffic in the traffic rules are:
marking the target vehicles with priority judgment at the same intersection as evaluation vehicles; and identifying the priority of each evaluation vehicle, and sequentially passing according to the obtained priority order.
The priority evaluation method for evaluating the vehicle is as follows:
single machine priority scheme: the method comprises the steps that a single automatic driving forklift passes through a preset priority, an RFID tag or a QR two-dimensional code identification system is used for binding a priority ID with the forklift, when two forklifts meet, the forklift can identify the RFID or the two-dimensional code on the opposite forklift through an RFID card reader or a camera fixed on the body of the forklift, the opposite priority ID is obtained and compared, if the opposite priority is higher than the priority, the parking waits for the opposite to pass, and if the opposite priority is higher than the opposite priority, the vehicle continues to perform navigation;
multi-machine priority scheme: and by adopting data communication protocols such as DDS, MQTT and the like, each forklift distributes information such as current position, execution path, task priority and the like. Each forklift unit determines the position of the adjacent forklift and the collision path which collide with the current execution path by subscribing the sharing information of other forklifts. Based on the priority of the fork truck tasks of the two conflicting parties as a main judgment basis, when the priorities are the same, auxiliary judgment based on the fork truck ID or information conditions such as whether goods are carried or not can be introduced, namely, judgment is carried out according to the priority of the carried goods. The specific avoidance negotiation rule is that the low-priority forklift firstly proposes an avoidance path scheme. If the avoidance scheme does not conflict with other running paths of the adjacent running forklift, the avoidance scheme is established. And starting to avoid after broadcasting the avoidance path. And after the high-priority forklift receives the low-priority forklift avoidance scheme, the original route is continuously executed. If the low-priority forklift collision avoidance scheme collides with other adjacent forklift paths and no other feasible collision avoidance paths, the broadcasting collision avoidance scheme fails, the collision avoidance cost value is waited and issued in situ, and particularly the length of the other forklift collision paths is the metered collision avoidance cost value, and the corresponding metering conversion relation is preset. Under the condition, the high-priority forklift carries out avoidance planning, and broadcasts an avoidance success message, or the avoidance causes the avoidance cost value which conflicts with other forklifts. At the moment, the two collision sides judge that the forklift with lower avoidance cost performs avoidance action, and the task priority value of the avoidance forklift is adjusted upwards, so that the avoidance action is guaranteed to be matched with the adjacent forklift in priority.
Specifically, under the condition that the avoidance scheme of the low-priority target vehicle collides with paths of other adjacent target vehicles, a corresponding collision analysis model is established based on the CNN network or the DNN network, a corresponding training set is established in a manual mode for training, analysis is carried out through the collision analysis model after the training is successful, and output of avoidance cost value and adjustment of task priority number values are carried out.
The avoidance path planning described by the present rule includes, but is not limited to, the following strategies: 1. the travel is suspended before the collision path is reached, and the travel is continued after the high priority is waited for to pass. 2. Other paths adjacent to the conflicting path are explored, and the conflicting road segments are bypassed without violating a single-row double-row rule. 3. Whether other branches exist on the conflict path or not is explored, the high-priority forklift can be avoided, and temporary stop points of the original path can be returned after the high-priority forklift passes through the branches.
When the electric quantity of the automatic driving forklift is lower than the set lowest working electric quantity, the forklift automatically goes to the charging pile for autonomous charging. If the charging pile is in use, the forklift to be charged recognizes the state of the charging pile and waits in a waiting area in a queue.
Another evaluation method for evaluating the priority of a vehicle is:
task data of each assessment vehicle is obtained in real time, the task data are all task data related to the assessment vehicle, such as progress requirements, cargo types, non-carried quantity and the like, data acquisition items corresponding to the task data can be preset in the actual application process, data acquisition is carried out according to the corresponding data acquisition items, and the task data are obtained in a summarizing mode; establishing a corresponding task analysis model based on a CNN network or a DNN network, setting a corresponding training set based on historical task data in a manual mode, wherein the training set comprises task data, a task fixed value and a duration correction curve which are correspondingly set, and the task fixed value is the goods priority value determined according to the carrying task and is a fixed value, so that the goods priority value is represented by the task fixed value; the time length correction curve is a correction coefficient curve established based on the carried time length of the estimated vehicle, and the time length correction curve is corrected in real time along with the change of task data, such as the acceleration of the required progress, etc.; generally, as the duration increases, the corresponding correction coefficient is larger; because neural networks are prior art in the art, the specific setup and training process is not described in detail in this disclosure;
real-time analysis is carried out on task data through a task analysis model after training is successful, task fixed values and duration correction curves corresponding to all the estimated vehicles are obtained, and corresponding correction coefficients are matched from the duration correction curves according to the carried duration corresponding to the estimated vehicles; marking the obtained task fixed value and the correction coefficient as RW and c respectively; and calculating corresponding priority values according to a priority value formula QG=c×RW, and determining the priority of each evaluation vehicle according to the order of the priority values.
Compared with the prior art, the invention has the beneficial effects that:
an operator automatically creates and generates a traffic route map in a storage environment through a laser radar installed on a forklift in a manual forklift dragging mode; the method is different from a laser SLAM probability map, the traffic range of the forklift is restricted in a traffic route map, and the path planning range of the forklift is limited to improve the safety and reliability of automatic forklift path planning in a complex storage environment; the path planning of the unmanned vehicle is carried out by utilizing modes such as manual traction, and the like, so that when the path is changed and adjusted, the path of the unmanned vehicle can be re-planned only after simple parameter input of the unmanned vehicle, the use of a user is greatly facilitated, and the path planning of the unmanned vehicle is simple and easy to understand; the path planning and adjustment of the unmanned vehicle can be realized without complex expert knowledge; the application popularization of corresponding unmanned vehicles is facilitated.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
FIG. 1 is a schematic view of a double roadway of the present invention;
FIG. 2 is a schematic view of the intersection area of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1 to 2, an automatic driving forklift traffic planning method based on warehouse bin coordinates includes:
according to the function requirement of the unmanned vehicle, corresponding hardware supplementation, such as laser radar and IMU, is carried out on the unmanned vehicle, and is used for building a map, navigation positioning and obstacle avoidance; the ultrasonic radar is used for pedestrian obstacle avoidance; the RGB/depth camera can simultaneously obtain environment optical image information and high-precision three-dimensional space distance information, is used for storage map creation, tray positioning, inserting and placing control, and can be lifted and deflected by a certain angle under the control of a motor; the navigation system, the unmanned vehicle central control system, the wireless communication module and the like, particularly, the unmanned vehicle central control system, the wireless communication module and the like are used for carrying out corresponding software and hardware configuration according to corresponding functions of the unmanned vehicle, and the corresponding software and hardware configuration based on the required functions can be realized by utilizing the existing related technology.
And carrying out traffic route planning of the unmanned vehicle:
when the unmanned vehicle is deployed in a new storage environment, an operator guides the unmanned vehicle to walk on a passable route to build a map in a manual control mode or a remote control mode; this operation will simultaneously complete the automatic generation of the navigation environment setup map and the unmanned vehicle traffic pattern. And automatically creating and generating a traffic route map in the warehouse environment through a laser radar installed on the forklift. Different from the laser SLAM probability map, the traffic route map constrains the passable range of the forklift, and the forklift path planning range is limited to improve the safety and reliability of automatic forklift path planning in a complex storage environment.
The method comprises the steps that an initial guided or remote-controlled unmanned vehicle is marked as a guided vehicle, the guided vehicle is not necessarily a vehicle which runs on the traffic route in the future, and the unmanned vehicle which runs on the corresponding traffic route in the future is marked as a target vehicle; if the guided vehicle is not a target vehicle running on the traffic route in the future, acquiring vehicle information, width, length, height, safety protection distance and other data of the target vehicle, wherein the safety protection distance is set based on the actual condition of the corresponding target vehicle, and a distance is extended outwards to be the safety protection distance by taking the boundaries of two sides of the unmanned vehicle as the reference; and debugging the corresponding boundary range on the guide vehicle based on the vehicle information, namely debugging the safety boundary range position of the target vehicle taking the guide vehicle as a reference on the guide vehicle by utilizing the distance information of various sizes of the target vehicle.
By way of example, depth cameras are adopted to collect distance information around the forklift, and the passable range of the traffic route map along the line is automatically expanded through the extracted distance information.
Several traffic roadmap creation modes are now provided:
a single row double-lane manual selection mode.
In this mode, the operator guides the guided vehicle to travel in the middle area of the passable route, such as the dashed track in fig. 1, and the guided vehicle expands the passable area with a certain width to both sides of the walking track by selecting options such as one-row and two-row provided in the system. The width can define a default value in the system, and can also be used for planning a traffic area by measuring distance of obstacles on two sides of the walking direction in a mode of deflecting a depth camera and an ultrasonic radar on the basis of the default value, and particularly debugging according to differences between a guide vehicle and a target vehicle.
Single-row double-lane automatic planning mode.
In the mode, the system automatically judges the safety distance at two sides of the walking route through the depth camera. The traffic path is automatically designated as a single-way or a double-way according to the length of the safety distance. The traffic route map respectively plans traffic routes according to the single-way and double-way roads. The specific principle is that a single-way road section is adopted, and a traffic route is a route through which a guide vehicle is towed; the traffic route is offset to two sides by taking the traction route of the guide vehicle as a reference to form two parallel routes.
The traffic rules for the case with route intersections, etc. are:
in the area where the multiple roads intersect, as shown in fig. 2, when multiple unmanned vehicles meet, the unmanned vehicle can judge which unmanned vehicle has the highest priority through the priority identification (such as two-dimensional code, RFID, etc.) of each trolley or the priority specified by the background dispatching system. The unmanned vehicles with the highest priority have the priority passing authority, and other unmanned vehicles need to wait for the unmanned vehicles with high priority to pass in situ and then pass through the traffic junction in sequence according to the priority.
Other traffic rules:
maintaining a safe vehicle distance. If a plurality of automatic driving forklifts advance in sequence, the safe vehicle distance between the forklifts should be kept so that enough reaction time exists when braking or avoiding is needed.
Pedestrians and obstacles are detected. And when the logistics vehicle is automatically driven, detecting the pedestrians and the obstacles in the advancing direction, stopping in time, avoiding the obstacles, and continuing to advance when the pedestrians leave.
If the vehicle-mounted camera detects the front stop sign, the vehicle-mounted camera can automatically stop, wait for the sign to be removed and then continue to advance.
In certain areas, such as narrow aisles or heavy areas, the truck needs to reduce the speed of travel to maintain safe passage.
After the traffic route planning is completed, the operation can be performed according to the tasks of each unmanned vehicle; the vehicle is operated according to the corresponding traffic route and work task of each target vehicle, and the vehicle can be applied by referring to the existing mature related technology of the unmanned vehicle to ensure the safe operation of the unmanned vehicle for the problems of obstacle avoidance, safety and the like in the operation process.
The storage shelf can carry out position marking information for storing goods by a pre-specified label. The RGB and depth cameras can finish identification and positioning of tag content through scanning of the cameras on all angles in the process of traffic route establishment. Meanwhile, the depth camera can further identify whether the position of the goods shelf is empty, and corresponding information is uploaded to a background server through a network and used for assisting an automatic information management system of unmanned warehouse storage, such as an MES, a WMS and the like.
The wireless communication module is connected with the forklift navigation system and can upload related information to the server. After the traffic route map is established, the established traffic route map can be shared with a local server, and an operator can edit the traffic route map through a webpage program or other application terminal App programs. After confirming that the operator is correct, the local server can send out the traffic line diagram to other forklifts located in the unified warehouse system. In the running process of the multi-fork truck, the fork truck dispatching system can realize the functions of obstacle avoidance and traffic regulation by sharing the information such as coordinates and execution paths among the fork trucks.
The path planning of the unmanned vehicle is carried out by utilizing modes such as manual traction, and the like, so that when the path is changed and adjusted, the path of the unmanned vehicle can be re-planned only after simple parameter input of the unmanned vehicle, the use of a user is greatly facilitated, and the path planning of the unmanned vehicle is simple and easy to understand; the path planning and adjustment of the unmanned vehicle can be realized without complex expert knowledge; the application popularization of corresponding unmanned vehicles is facilitated.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas which are obtained by acquiring a large amount of data and performing software simulation to obtain the closest actual situation, and preset parameters and preset thresholds in the formulas are set by a person skilled in the art according to the actual situation or are obtained by simulating a large amount of data.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (9)
1. An automatic driving forklift traffic planning method based on warehouse bin coordinates is characterized by comprising the following steps:
when the unmanned vehicle is deployed in a new storage environment, guiding the guided vehicle to advance on a traffic route by an operator, and generating a traffic route map in the current storage environment;
when the vehicle has a task, the target vehicle runs according to the corresponding traffic route map; after the goods reach the storage shelf, the identification and the positioning of the label content on the storage shelf are completed through the scanning of the camera to each angle, and corresponding goods processing is performed based on the identification and the positioning data.
2. The automatic driving forklift traffic planning method based on warehouse bin coordinates according to claim 1, wherein when a camera identifies the racks, whether the positions of the racks are empty is synchronously judged.
3. The method for planning the traffic of the automatic driving forklift based on the storage bin coordinates of claim 1, the traffic route map generation method is characterized by comprising the following steps of:
and the operator selects a single-row or double-row mode, the guided vehicle is guided to run on the corresponding route, the passing width of the corresponding target vehicle is generated in real time, and after the guided vehicle is guided, a corresponding traffic route map is generated based on the passing area corresponding to the passing width.
4. The automatic driving forklift traffic planning method based on warehouse bin coordinates according to claim 1, wherein the traffic route map generating method comprises the following steps:
and acquiring safety distances on two sides of the walking route in real time, judging the number of the walking ways according to the safety distances, planning the traffic route based on the obtained number of the walking ways, and generating a traffic route map.
5. The method for planning traffic of an automatic driving forklift based on storage bin coordinates according to claim 4, wherein when the number of roads is one, the traffic route is a route through which a guided vehicle pulls;
when the number of the roads is two, the traffic route is offset to two sides by taking the traction route of the guide vehicle as a reference to form two sections of parallel routes, and the user specifies the driving direction of each path.
6. The method for planning traffic of an automatic driving forklift based on storage bin coordinates according to claim 1, wherein the target vehicle operates according to a preset passing rule when operating.
7. The method for planning traffic of an automatic driving forklift based on warehouse bin coordinates according to claim 6, wherein the rules for the preferential traffic of intersections in the traffic rules are:
determining an evaluation vehicle; identifying the priority of each evaluation vehicle, and sequentially passing according to the obtained priority order;
priority assessment is classified as: a single machine priority scheme and a multiple machine priority scheme;
when the electric quantity of the target vehicle is lower than the set minimum working electric quantity, the forklift automatically goes to the charging pile to perform autonomous charging; when the charging stake is in use, the target vehicle to be charged will recognize the charging stake state and wait in line in the waiting area.
8. The method for planning traffic of an automatic driving forklift based on warehouse bin coordinates according to claim 7, wherein the single machine priority scheme is as follows:
presetting the priority of each evaluation vehicle and carrying out corresponding binding;
when two estimated vehicles meet, identification recognition is carried out, the priority ID of the opposite party is obtained and compared, and when the priority of the opposite party is higher than the priority of the opposite party, the vehicle is stopped and the opposite party is waited to pass; when the present priority is higher than the opponent priority, the present vehicle continues to perform navigation.
9. The method for planning traffic of an automatic driving forklift based on warehouse bin coordinates as claimed in claim 7, wherein the multi-machine priority scheme is as follows:
each target vehicle analyzes the current position, the execution path and the task priority information based on a preset communication protocol, and marks the current position, the execution path and the task priority information as sharing information; sharing information of other target vehicles is obtained in real time, and the position of an adjacent forklift and a collision path which collide with the current execution path are determined; judging based on the corresponding priority; when the priorities are the same, judging based on the transported information;
the method comprises the steps that an avoidance path scheme is firstly provided for a low-priority target vehicle, when the avoidance scheme does not conflict with the running paths of other nearby running target vehicles, the avoidance scheme is established, and avoidance is started after the avoidance path is broadcasted; after the high-priority forklift receives the low-priority forklift avoidance scheme, the original route is continuously executed;
when the avoidance scheme of the low-priority target vehicle collides with paths of other adjacent target vehicles and other feasible avoidance paths are not available, the broadcast avoidance scheme fails and the avoidance cost value based on the length measurement of the paths colliding with other target vehicles is distributed; the high-priority target vehicles carry out avoidance planning, and broadcast an avoidance success message, or avoid the avoidance cost value causing conflict with other target vehicles; and the conflicting target vehicles judge that the forklift with lower avoidance cost value executes the avoidance action at the moment, and the task priority value of the avoidance target vehicles is adjusted upwards.
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| CN116934206A (en) * | 2023-09-18 | 2023-10-24 | 浙江菜鸟供应链管理有限公司 | Scheduling method and system |
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