CN117873099A - Cargo handling route planning system and method - Google Patents
Cargo handling route planning system and method Download PDFInfo
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Abstract
The invention relates to a cargo handling route planning system and method, wherein the method comprises the following steps: constructing a plurality of bounding boxes based on the obstacle information; constructing a bounding box based on model data and size data of the unmanned forklift; pre-collision is performed on the handling route based on the bounding box and bounding box to determine whether there is a transportation risk. In case of transportation risk, collision checking is performed on the bounding box and the bounding box to plan the carrying route of the unmanned forklift and/or the pose of the carried goods. According to the invention, the change of the overall size of the unmanned forklift after carrying the goods and the simple pre-collision of a plurality of obstacles in the transported virtual scene are adopted, so that whether the unmanned forklift collides with the obstacles on a preset path after carrying the goods is judged by a small amount of calculation. The invention also avoids the section with transportation risk by performing high-precision collision inspection on the section with transportation risk to adjust the position of the unmanned forklift for carrying the goods or the way of the unmanned forklift for carrying the route.
Description
Technical Field
The invention relates to the technical field of intelligent forklifts, in particular to a cargo handling route planning system and method.
Background
A forklift is an industrial transport vehicle, and is a transport vehicle that performs operations of loading and unloading, stacking, and short-distance transportation of cargoes. The technology of forklifts is very different day by day, and especially the intellectualization of forklifts. In the process of driving and forking in workshops or high-risk environments, the placement positions of some cargoes are not accurate enough and the sizes of cargoes are different, so that the size of the cargoes can not pass through a certain height-limiting or other limited passage or obstacle when the unmanned forklift passes through the passage or obstacle. The prior art focuses on the planning of the obstacle avoidance route of the unmanned forklift, and the indexes such as the driving distance, the time and the energy consumption of the unmanned forklift are minimized under the condition of meeting the cargo transportation by intelligent scheduling and path optimization of the unmanned forklift. The prior art lacks planning of unmanned forklift travel routes for cargo sizes. In particular, the collision relation between the goods and the obstacles is judged according to different sizes and positions of the goods so as to adjust the carrying route and the positions of the goods. Simple ranging sensors cannot acquire relevant characteristics of cargo for collision checking.
The patent application with publication number CN110872080A discloses a route planning system based on an unmanned forklift, which comprises the unmanned forklift and a monitoring end for monitoring the unmanned forklift. The unmanned forklift further comprises a motion module and a monitoring module; the motion module further comprises a starting and stopping device for starting and stopping the forklift, a motion object acquisition and capturing module for capturing motion objects on a forklift driving path, and autonomous navigation for path navigation. The unmanned forklift disclosed by the patent can optimize the running route, and captures moving images in real time on the freight path according to the conditions of moving objects on the path so as to avoid collision. The differential navigation device can timely adjust the path so as to ensure the safety of the forklift in operation. The four cameras detect the periphery of the forklift respectively, and after the images are fed back to the main control device, the captured images are analyzed. The speed of the vehicle can be controlled after analysis to ensure the safety of the whole line. The unmanned forklift also has a route planning function. However, the disadvantage of this patent is that if the size and length of the cargo carried by the unmanned forklift exceeds the width of the unmanned forklift, the four-bit radar of this patent cannot obtain the distance between the longest end of the cargo and the obstacle, so that the patent ignores the increase in the volume occupied by the unmanned forklift that may be brought by carrying the cargo when planning a route. The cargo may collide with the obstacle, resulting in that the unmanned forklift cannot transport the cargo through the route, and even resulting in the cargo being dumped or damaged.
CN112978619a discloses a goods transportation shock absorbing forklift with an automatic guiding device, comprising a forklift body, an automatic guiding device, a loading fork interval adjusting device, a forklift lifting frame and a mecanum wheel group, wherein the automatic guiding device is arranged on the forklift body. The forklift truck body can run according to the set route, the route is not deviated, and the accuracy is high. The bottom of the forklift body is provided with the Mecanum wheel group, so that vibration generated in the process of transporting goods can be reduced, displacement of the goods due to vibration and even falling of the goods in the process of transporting the goods are avoided, and the transportation safety of the goods is kept; meanwhile, the width between two loading and unloading forks on the forklift body can be adjusted, so that the width can be adjusted according to the goods to be loaded and unloaded in practice, and the loading and unloading requirements of different types of goods can be met. This patent considers the handling requirements of different types of cargo, but does not also consider the problem of different sizes associated with different types of cargo. If the goods are longer rectangular shape, then probably take place the goods and shift and fall owing to the collision between goods and the barrier in the transportation, reduced unmanned fork truck goods transportation's efficiency.
Furthermore, there are differences in one aspect due to understanding to those skilled in the art; on the other hand, since the applicant has studied a lot of documents and patents while making the present invention, the text is not limited to details and contents of all but it is by no means the present invention does not have these prior art features, but the present invention has all the prior art features, and the applicant remains in the background art to which the right of the related prior art is added.
Disclosure of Invention
In the prior art, the sensor is used for acquiring the environmental data of the freight warehouse so as to avoid the obstacle and smoothly reach the target point in the running process of the unmanned forklift. However, in the case of carrying goods, the prior art does not consider the collision between the unmanned forklift and the obstacle, which may be caused by the incorrect placement of the goods with different sizes or postures. The distance between the unmanned forklift and the obstacle can only be obtained by the traditional distance measuring sensor, and if the goods are long, the goods can collide with the obstacle under the condition that the distance measuring sensor judges that the goods are far away from the obstacle. Especially, how to plan a proper carrying route of the unmanned forklift based on different sizes and placing postures of cargoes in a channel which enters a height limiting or bending mode is a technical problem which needs to be solved urgently in the prior art.
In order to realize the judgment of trafficability in the cargo handling process, the prior art has presented a technical scheme for carrying out simulated transportation evaluation on the trafficability of cargo transportation based on a three-dimensional channel model. For example, patent document with publication number CN114387407a discloses a method for evaluating trafficability of a large cargo based on a three-dimensional channel model, which comprises firstly determining a transportation route, creating a large transport vehicle model, a large cargo model, a special road scene model and an obstacle model, rendering each model on a map, secondly generating a three-dimensional channel model, obtaining a positional relationship between the large transport vehicle model and the large cargo model in the three-dimensional channel model, and judging whether contact collision occurs between the large transport vehicle model and the three-dimensional channel model and between the large transport vehicle model and the obstacle model in the transportation process. According to the technical scheme, a three-dimensional modeling and simulation technology is utilized, the actual transportation process is simulated in software, and the trafficability and safety of the transportation vehicle are judged through data matching and algorithm analysis. However, according to the technical scheme, the visual angle is fixed on the large-piece transportation vehicle model, the large-piece transportation vehicle model is simulated to move according to the planned transportation route, the position relation between the large-piece transportation vehicle model and the large-piece goods model in the three-dimensional channel model is obtained, the large-piece goods have a certain occupied space by default, the occupied space cannot be changed, and therefore the impact analysis cannot be considered on impact of the dimensional change of the goods in the transportation process. The technical scheme is suitable for collision analysis in the large road passing process, and can not realize accurate collision analysis in occasions with various cargo transportation size requirements such as cargo storage warehouses and the like.
In accordance with one aspect of the present invention, in response to the deficiencies of the prior art, a method for planning a cargo handling route is disclosed, the method comprising: constructing a plurality of bounding boxes in the virtual scene transported by the unmanned forklift based on the barrier information; constructing at least one bounding box based on model data of the unmanned forklift and size data of the transported goods; pre-collision is carried out on at least one carrying route based on a plurality of bounding boxes and at least one bounding box to determine whether transportation risks exist, and if so, the bounding boxes and the bounding boxes are subjected to collision check to obtain three-dimensional collision data; and planning the pose of the goods carried by the unmanned forklift and/or the carrying route of the unmanned forklift based on the three-dimensional collision data. Compared with the prior art, the object carrying route planning method can adjust the pose of the goods carried by the unmanned forklift and/or the carrying route of the unmanned forklift according to the collision analysis result. Based on the above distinguishing technical features, the problems to be solved by the present invention may include: how to adjust the corresponding carrying strategy according to different carrying cargoes and reduce the data processing capacity of collision analysis. Specifically, the invention simply pre-collides with a plurality of obstacles in the virtual scene of transportation through the change of the overall size of the unmanned forklift after carrying the goods, thereby judging whether the unmanned forklift collides with the obstacles on a preset path or not after carrying the goods with a small amount of calculation amount, and screening out sections which cannot collide. The invention also acquires three-dimensional collision data of collision by carrying out high-precision collision inspection on the section with transportation risk, and avoids the section with transportation risk by adjusting the position of carrying goods by the unmanned forklift or the way of carrying the goods by the unmanned forklift. Therefore, the pre-calculation amount of the pre-set path collision prediction is reduced, and the safe carrying route of the unmanned forklift can be planned.
In order to ensure smoothness and safety of goods in the transportation process, the prior art has already presented a technical scheme for realizing ordered transportation of goods in places with large circulation of logistics by adjusting the positions of the goods. For example, patent document publication No. CN115818192a discloses a transport apparatus capable of calibrating a position of a cargo, the transport apparatus including a transport device for transporting the cargo from a loading position to a unloading position, a positioning device for adjusting the cargo in a standing posture to the cargo in a lying posture, and a calibration device for adjusting the position of the cargo so as to be movable on the transport device in the same posture; when the transmission path of the transmission device is a straight line, the calibration device is arranged into two groups and is respectively provided with an upstream end and a downstream end of the transmission device; when the transmission path includes at least one turning point, the calibration devices are arranged in a plurality of groups, and the calibration devices are respectively arranged at the upstream end and the downstream end of the turning point. According to the technical scheme, the goods can be adjusted from a standing state to a lying state by using the setting based on the position adjusting device, so that the gravity center of the goods is lowered, the goods can be transported to a destination in a perfect state, and the transportation route in the process is fixed and cannot be adjusted according to the installation state of the goods. That is, the adjustment of the posture of the goods in the technical solution is limited to the adjustment of the installation state thereof, the main control element of the process adjustment is the initial installation state of the goods, and the technical solution is not related to the collision process possibly caused by the overall dimension of the goods in the transportation process, and the posture of the goods installation on the unmanned forklift and/or the transportation route of the unmanned forklift cannot be adjusted under the condition that the collision will occur in the predicted transportation process.
According to a preferred embodiment, the method of constructing several bounding boxes comprises establishing a global coordinate system in a virtual scene based on obstacle information of a freight warehouse that has completed digital twinning; a geometric body corresponding to the obstacle in the global coordinate system is established based on the longest side of the obstacle in the obstacle information, and the geometric body is taken as a bounding box. Compared with the prior art, the method and the device can establish the collision analysis area of the unmanned forklift in the global coordinate system. Based on the above distinguishing technical features, the problems to be solved by the present invention may include: how to reduce the data processing amount of collision analysis in the transportation process of the unmanned forklift. Specifically, because the specific goods stored in the freight warehouse are different, the size or the limiting range of the space area occupied by the goods shelves for placing various goods is also different, meanwhile, the specific appearance structure of the goods shelves is directly influenced by different structures such as access channels arranged on different goods shelves, so that the carrying process of different goods among different goods shelves is realized, the collision analysis process is required to be respectively executed according to different goods shelf structure forms and goods types, and the initial collision analysis data processing amount is larger. In contrast, in the present invention, the bounding box constructed is not a bounding box that fits or conforms completely to the obstacle, but can approximate a regular geometry that characterizes the coverage of the obstacle. Therefore, the problem that the bounding box established in the prior art needs to accurately calculate each change and form of the obstacle is avoided, the calculation amount of subsequent collision detection is simplified, and a plurality of obstacles in a freight warehouse are not missed at the same time.
According to a preferred embodiment, the method of constructing a bounding box comprises: establishing a virtual model for representing the size of the body of the unmanned forklift based on model data of the unmanned forklift; in the case where the unmanned forklift carries the cargo, at least one bounding box containing the unmanned forklift and the cargo is constructed based on the virtual model and the pose and size data of the cargo. Preferably, in the case where the pose of the cargo is changed, the bounding box is updated or reconstructed based on the changed pose of the cargo. In case of a change of the cargo pose, the processing unit updates or reconstructs the bounding box based on the changed cargo pose. The bounding box refers to the smallest cube that contains the unmanned forklift and cargo. Therefore, the invention can realize the planning of the conveying route of the unmanned forklift through the collision inspection of the bounding box and the bounding box.
According to a preferred embodiment, the method further comprises: establishing a virtual channel capable of representing the movement track of the unmanned forklift by moving the bounding box along a preset carrying route; the virtual channel is cut based on the three-dimensional tangential planes of the bounding boxes to form a plurality of bounding boxes to be tested. The shape of the virtual channel is curved and complex, and if the virtual channel is subjected to global collision checking, not only is the calculation amount of the processing unit increased, but most of collision calculations are also meaningless. Therefore, the invention screens the bounding box to be detected corresponding to the unmanned forklift in the area where the bounding box exists based on the bounding box to perform collision detection, thereby improving the efficiency of data calculation.
According to a preferred embodiment, the method of pre-crash comprises: and judging the collision relation between the bounding boxes to be tested and the corresponding bounding boxes to screen out a plurality of bounding boxes to be tested and a plurality of bounding boxes with collision relation. The processing unit determines whether the bounding box to be detected and the bounding box have collision relations or not through space judgment in the global coordinate system, and then screens out a plurality of bounding boxes to be detected and a plurality of bounding boxes which possibly have collision relations. According to the invention, through the pre-collision of the bounding box with a larger range, the obstacle possibly colliding with the unmanned forklift is screened out, and then the bounding box with high precision is divided for collision detection.
According to a preferred embodiment, the method further comprises: under the condition that the bounding box to be detected and the bounding box have collision relation, the irregular bounding box is divided into a plurality of bounding box sub-modules in a segmented and/or split mode, and the bounding box sub-modules which possibly have collision relation are screened out in a mode of pre-collision between the bounding box sub-modules and the bounding box to be detected. Compared with the prior art, the method and the device can divide the area of the part where the bounding box to be detected has the collision relation with the bounding box. Based on the above distinguishing technical features, the problems to be solved by the present invention may include: how to screen the part of the bounding box with collision risk to improve the accuracy of collision analysis. Specifically, the accuracy in the judgment of the collision relationship is too low because the space covered by the bounding box constructed from the longest side of the obstacle exceeds the actual volume of the obstacle. Therefore, after screening out part of the bounding boxes, the method and the device perform secondary screening by dividing the bounding boxes into a plurality of bounding box sub-modules, so that the accuracy of judging the collision relationship is improved on the basis of reducing the calculated amount of the three-dimensional collision data.
According to a preferred embodiment, the method of acquiring three-dimensional collision data comprises: under the condition that a plurality of boundary boxes and a plurality of boundary box sub-modules are screened, the boundary boxes and the boundary box sub-modules are divided into a plurality of boundary elements, and three-dimensional collision data are acquired in a mode of performing at least one collision check with the bounding box. The invention performs point-by-point collision check on each boundary element and the bounding box to acquire three-dimensional collision data of a plurality of boundary boxes and a plurality of boundary box sub-modules colliding with the bounding box. Therefore, the collision range of the bounding box and the bounding box can be accurately acquired through calculation, partial circuits without collision relation are reserved, and the partial circuits with collision relation are adjusted based on three-dimensional collision data.
According to a preferred embodiment, the method further comprises: controlling the unmanned forklift to change the pose of the goods in a translational or rotational mode based on the three-dimensional collision data, so that the bounding box and the bounding box do not collide; after the pose of the goods is changed, under the condition that the bounding box and the bounding box still have collision relations, a carrying route which can safely pass through the unmanned forklift is planned based on a plurality of bounding box combinations without collision relations. Compared with the prior art, the invention can avoid collision by adjusting the pose of the goods, and can adjust the carrying route according to the change of the pose of the goods. Based on the above distinguishing technical features, the problems to be solved by the present invention may include: how to carry out combination planning on the carrying route according to the type and state information of the goods carried by the unmanned forklift. In particular, during large-scale transportation, it is not necessary to re-plan the transportation route upon encountering an obstacle. In some cases, the goods can be made to pass through a certain passage or obstacle by changing the pose of the goods. For example by tilting the cargo through a certain height-limited passage. According to the invention, the unmanned forklift can pass through the passage or the obstacle which cannot pass through before by changing the position and the posture of the goods. When encountering the passageway of limit for height, it can be through the mode of adjusting the vertical of goods to slope or transversely put, makes the goods height reduce to pass through this limit for height passageway. In the judging process, intervention of staff is not needed, intelligent control of the unmanned forklift is achieved through less calculated amount, and transportation efficiency of the unmanned forklift is not affected.
Another aspect of the invention relates to a cargo handling route planning system including an unmanned forklift and a processing unit. The processing unit is configured to: constructing a plurality of bounding boxes in the virtual scene transported by the unmanned forklift based on the barrier information; constructing at least one bounding box based on model data of the unmanned forklift and size data of the transported goods; pre-collision is carried out on at least one carrying route based on a plurality of bounding boxes and at least one bounding box to determine whether transportation risks exist, and if so, the bounding boxes and the bounding boxes are subjected to collision check to obtain three-dimensional collision data; and planning the pose of the goods carried by the unmanned forklift and/or the carrying route of the unmanned forklift based on the three-dimensional collision data. According to the invention, the corresponding bounding box is established through the change of the collision volume of the unmanned forklift after carrying the goods, so that the unmanned forklift can avoid the carried goods from collision while avoiding the obstacle. The processing unit can plan the carrying route of the unmanned forklift under the condition of carrying the goods based on the formed bounding box, effectively avoids the situation that the unmanned forklift cannot safely reach the target position along the preset carrying route under the condition of carrying due to the change of the size or the pose of the goods, and prevents the possible collision between the goods and the obstacles on the premise of ensuring the transportation efficiency of the unmanned forklift.
According to a preferred embodiment, the processing unit is further configured to: controlling the unmanned forklift to change the pose of the goods in a translational or rotational mode based on the three-dimensional collision data, so that the bounding box and the bounding box do not collide; after the pose of the goods is changed, under the condition that the bounding box and the bounding box still have collision relations, a carrying route which can safely pass through the unmanned forklift is planned based on a plurality of bounding box combinations without collision relations. The processing unit adjusts the pose of the goods by controlling the unmanned forklift to clamp and rotate the goods, so that the unmanned forklift can pass through a certain height-limited, width-limited or bent channel and an obstacle. According to the method, a processing unit is not required to re-plan a carrying route, and the adjustment of the position and the posture of the goods can be realized through the relevant three-dimensional collision data obtained through collision inspection, so that the collision between the goods and a channel or an obstacle is avoided under the condition of along the preset carrying route, and the efficiency of transporting the goods by the unmanned forklift is improved.
Drawings
FIG. 1 is a simplified block diagram of a preferred embodiment of a cargo handling routing system according to the present invention;
FIG. 2 is a simplified flow diagram of a method of cargo handling route planning according to a preferred embodiment of the present invention;
FIG. 3 is a simplified application scenario schematic of a cargo handling routing system according to a preferred embodiment of the present invention;
FIG. 4 is a simplified application scenario diagram of an unmanned forklift of a cargo handling path planning system according to a preferred embodiment of the present invention colliding with an obstacle;
FIG. 5 is a schematic view of another simplified application scenario of an unmanned forklift of a cargo handling path planning system according to a preferred embodiment of the present invention colliding with an obstacle;
FIG. 6 is a simplified application scenario diagram of an unmanned forklift of a cargo handling route planning system according to a preferred embodiment of the present invention after adjusting the cargo pose without colliding with an obstacle;
fig. 7 is a schematic diagram of another simplified application scenario in which an unmanned forklift of a cargo handling route planning system according to a preferred embodiment of the present invention does not collide with an obstacle after adjusting the cargo pose.
List of reference numerals
100: a processing unit; 200: unmanned forklifts; 201: a bounding box; 300: an obstacle; 301: a bounding box; 302: a boundary frame sub-module; 303: a height limiting channel; 304: a goods shelf; 400: goods; 500: and (5) a carrying route.
Detailed Description
The following detailed description refers to the accompanying drawings.
Unmanned forklift 200: the unmanned forklift 200 is an intelligent industrial vehicle robot that can automatically accomplish various handling and transportation tasks through various navigation techniques without manual driving. In the present invention, the unmanned forklift 200 can be a clamp-on rotary intelligent forklift, thereby being capable of controlling the translation and rotation of the cargo 400.
Bounding box 301: refers to a geometric body that is capable of completely containing an object or group of objects. The bounding box 301 may be two-dimensional or three-dimensional, and may be axis aligned or rotated. In the present invention, the bounding box 301 refers to a cube constructed with the longest side of the obstacle 300, which includes not only the obstacle 300 but also additional space.
Bounding box 201: refers to a smallest cube that can completely contain an object or group of objects. The bounding box 201 is generally axis aligned, that is, its sides are parallel to the coordinate axes.
Collision checking: and judging whether at least two virtual models have a spatial overlapping relationship in the virtual space.
Virtual channel: the bounding box 201 encloses a volume formed during movement. For example, in mathematics and geometry, a face movement forms a volume, i.e., a planar pattern moves along a path to form a solid pattern. In the present invention, the virtual passage refers to a stereoscopic pattern formed by the bounding box 201 during movement along the carrying route 500.
Pose: in the present invention, the pose represents the position and posture of the cargo 400. Any one rigid body (e.g., cargo 400) may accurately and uniquely represent its position state in a global coordinate system with position and pose.
Global coordinate system: refers to a coordinate system in which an object is located in a three-dimensional space of a virtual scene. In the present invention, the vertex coordinates of each object (e.g., obstacle 300, unmanned forklift 200, cargo 400, etc.) can be expressed based on the coordinate system. The global coordinate system is the coordinate system of the whole virtual scene and is a fixed coordinate system. Each object is displaced, rotated and scaled relative to the coordinate system.
Example 1
In the prior art, the working process of the intelligent forklift does not need manual operation. However, in the cargo transportation process, the intelligent forklift inevitably encounters a part of unpredictable obstacles 300, and the intelligent forklift cannot travel along the originally planned path under the influence of the obstacles 300. Particularly, in the case where the sizes of the cargoes 400 carried by the smart forklift are different, it is difficult for the smart forklift to determine whether the pre-planned path is affected by the dimensional change of the cargoes 400, resulting in collision with the obstacle 300 on the path. For example, if the cargo 400 carried by the smart forklift is large in size, it may not be suitable for pre-planned routes, requiring the cargo 400 to be transported through other routes or aisles. Currently, in the prior art, an artificial potential field method, a bubble band technology and the like are mostly adopted to perform obstacle avoidance planning on an intelligent forklift, and the intelligent forklift performs obstacle avoidance by planning an obstacle 300 on a path into a larger bounding box 201. However, due to the problem of calculation accuracy, the bounding boxes 201 on the path are too many or too large, so that the intelligent forklift has the false image of not being suitable for moving the path, and the path planned by the method does not consider not only the size of the goods 400 and the corresponding placement pose, but also the problems of excessive redundant data and too large calculation amount caused by calculating the bounding boxes 201 for each obstacle 300 on the path, so that the intelligent forklift is insensitive and has lower transportation efficiency. Therefore, how to plan a suitable forklift moving path based on the size and the pose of the cargo 400 and how to reduce the calculation amount of the obstacle 300 and the calculation amount of path planning are technical problems to be solved by the present invention.
As shown in fig. 1, the present invention discloses a planning system for realizing rapid scheduling of goods 400 in a freight warehouse by changing the pose of the transported goods 400 when the unmanned forklift 200 is used for transporting the goods 400 or planning the transportation route 500 of the goods 400 when the unmanned forklift 200 is used for transporting the goods 400 in the situation that the unmanned forklift 200 is required to complete digital twinning.
To this end, the cargo handling route 500 planning system of the present invention includes at least one unmanned forklift 200 for carrying the cargo 400 in a clasping and rotating manner, and a processing unit 100 for planning the handling route 500 of the unmanned forklift 200 and corresponding to the pose of the cargo 400.
In case the processing unit 100 simulates in a virtual scenario several bounding boxes 301 characterizing the obstacle 300, or in case a digital twin freight warehouse has been completed requiring the transportation of goods 400, several unmanned forklifts 200 docked at the charging station are communicatively connected in a wired or wireless manner with the processing unit 100 in a dispatch or monitoring room of a remote server or freight warehouse. The plurality of unmanned forklifts 200 are parked in the charging station in a wired connection manner to supplement energy, and the plurality of unmanned forklifts 200 are simultaneously connected with the processing unit 100 in the charging station in a wired connection manner to transmit a planning of the handling route 500 simulated by the processing unit 100 in the virtual scene and/or the pose of the unmanned forklifts 200 to handle the goods 400 corresponding to the handling route 500.
In the present invention, the processing unit 100 may be located in a dispatch room of a freight warehouse or in a monitoring room or in a charging station where the unmanned forklift 200 is parked. When the processing unit 100 is disposed in the charging station, the processing unit 100 establishes a communication connection with the plurality of unmanned forklifts 200 in a wired manner. The charging station is provided with a communication interface connected with the processing unit 100. The processing unit 100 transmits the transport route 500 simulated in the virtual scene and the pose of the cargo 400 to the unmanned forklift 200 in a wired manner according to the cargo to be transported by the unmanned forklift 200. When the unmanned forklift 200 is required to carry the goods, the data is difficult to be transmitted quickly in a wireless mode due to the large data volume of the carrying route 500 and the corresponding goods 400 pose, and meanwhile, a large bandwidth support is required. Therefore, the wired transmission method is more suitable for the transmission of the handling route 500 obtained by the processing unit 100 after the pre-simulation than the wireless transmission method. In this case, the processing unit 100 pre-simulates and derives the carrying route 500 of the unmanned forklift 200 and the pose of the corresponding cargo 400 in the virtual scene, and transmits several data in a wired manner during the charging of the unmanned forklift 200.
Fig. 3 to 7 are three-dimensional simulated virtual scenes of a freight warehouse. In the case where the processing unit 100 constructs a number of bounding boxes 301 in a virtual scene in which the unmanned forklift 200 is transported based on the obstacle information, and the processing unit 100 constructs bounding boxes 201 based on model data of the unmanned forklift 200 and size data of the transported goods 400, the unmanned forklift 200 carrying the goods 400 moves along a carrying route 500 received from the processing unit 100. Since the carrying route 500 transmitted by the processing unit 100 is accompanied by the pose of the cargo 400 to be carried when passing through the carrying route 500. Accordingly, the unmanned forklift 200 passes through a certain obstacle 300 in such a manner as to adjust the pose of the carried goods 400 in the case of approaching the obstacle 300.
As shown in fig. 3, the unmanned forklift 200 needs to pass through a certain height-limiting aisle 303 or through a fire door curtain of a certain lowering height. As shown in fig. 4, the height of the cargo 400 carried by the unmanned forklift 200 is high due to the gravity center requirement of the cargo 400 carried by the unmanned forklift 200, so that the cargo 400 cannot pass through the height limiting tunnel 303 in the current position of the cargo 400. The unmanned forklift 200 can pass through the height limiting tunnel 303 in a detour manner, but this affects the transport efficiency of the unmanned forklift 200. In the present invention, due to the pre-planning of the processing unit 100 in the virtual scenario, the unmanned forklift 200 is able to pass through the height-limiting tunnel 303 in a manner that changes the cargo pose, in the event that it approaches the height-limiting tunnel 303. The processing unit 100 performs a pre-crash on at least one of the transportation routes 500 based on several bounding boxes 301 and bounding boxes 201 to determine if there is a transportation risk.
As shown in fig. 5, in the case where there is a transportation risk, the processing unit 100 performs a collision check on the bounding box 301 and the bounding box 201 to acquire three-dimensional collision data. The processing unit 100 plans the pose of the cargo 400 carried by the unmanned forklift 200 and/or the carrying route 500 of the unmanned forklift 200 based on the three-dimensional collision data. The above calculations are all derived from simulations in the virtual scenario performed by the processing unit 100, and in particular, the processing unit 100 can send the handling route 500 and the corresponding cargo pose to the unmanned forklift 200 in a wired transmission manner. As shown in fig. 6 and 7, the unmanned forklift 200 passes through the height limiting tunnel 303 in such a manner as to lower the pose of the cargo 400 in the case of approaching the height limiting tunnel 303.
The unmanned forklift 200 of the present invention can perform intelligent transportation of the cargo 400 at a cargo storage point or a cargo storage warehouse. The point of deposit or warehouse has completed digital twinning to facilitate the processing unit 100 to obtain information about obstructions within the point of deposit or warehouse. The processing unit 100 of the present invention may be one or more of a processor, a server, a cloud platform, a computer, a smart device, for executing a software program of the method of planning a cargo handling route 500 of the present invention.
The invention provides a method for planning a cargo carrying route 500, as shown in fig. 2, the method comprises the following steps:
s1: the processing unit 100 builds several bounding boxes 301 in the virtual scene transported by the unmanned forklift 200 based on the obstacle information.
The bounding box 301 refers to a rectangle or cube that can completely contain an object or group of objects. In the present invention, the bounding box 301 refers to a cube that can completely contain the obstacle 300 on the transport path of the unmanned forklift 200.
S2: the processing unit 100 constructs at least one bounding box 201 based on model data of the unmanned forklift 200 and size data of the transported goods 400.
S3: the processing unit 100 performs pre-collision on at least one carrying route 500 based on a plurality of bounding boxes 301 and at least one bounding box 201 to determine whether there is a transportation risk, and performs collision check on the bounding boxes 301 and the bounding boxes 201 to acquire three-dimensional collision data of the bounding boxes 301 colliding with the bounding boxes 201 in case of the transportation risk.
S4: the processing unit 100 plans the pose of the cargo 400 carried by the unmanned forklift 200 and/or the carrying route 500 of the unmanned forklift 200 based on the three-dimensional collision data.
According to the invention, through simple pre-collision of the unmanned forklift 200 after carrying the goods 400 and a plurality of obstacles 300 in a virtual scene of transportation, whether the unmanned forklift 200 collides with the obstacles 300 on a preset path or not after carrying the goods 400 is judged by a small amount of calculation amount, and the section which cannot collide is screened. The processing unit 100 of the present invention also acquires three-dimensional collision data of a collision by performing high-precision collision inspection on a section with transportation risk, and avoids the section with transportation risk by adjusting the position of the unmanned forklift 200 carrying the cargo 400 or the way of the unmanned forklift 200 carrying the route 500. Thus, not only the amount of previous calculation of the preset path collision prediction is reduced, but also the safe transportation route 500 of the unmanned forklift 200 can be planned.
S11: the processing unit 100 establishes a global coordinate system in the virtual scene based on the obstacle information of the freight warehouse that has completed the digital twinning.
A number of digital twinning sensors are arranged in the freight warehouse which completes digital twinning. The digital twin sensors can be laser scanning sensors whereby global obstacle information of the current freight warehouse and relative coordinates of the obstacle with respect to the respective digital twin sensor are obtained. The processing unit 100 converts the relative coordinates of the several obstacles 300 into global coordinates in a global coordinate system based on the obstacle information and global coordinates of the current location points of the respective digital twin sensors, thereby establishing the several obstacles 300 in the virtual scene.
S12: the processing unit 100 establishes a number of bounding boxes 301 corresponding to the obstacle 300 based on the global coordinate system and the size of the number of obstacles 300.
Preferably, step S12: the processing unit 100 establishes a geometric body corresponding to the obstacle 300 based on the longest side in the size of the obstacle 300, and takes the geometric body as the bounding box 301. The processing unit 100 takes the longest side length of the obstacle 300 as the boundary of the bounding box 301, thereby constructing the bounding box 301 that completely contains the obstacle 300 in the virtual scene.
As shown in fig. 1, the above-described obstacle 300 can refer to a number of shelves 304 in a freight warehouse, a parked unmanned forklift 200, or other stationary obstacle 300. In the present invention, the bounding box 301 constructed by the processing unit 100 is not a bounding box 201 that completely conforms or conforms to the obstacle 300, but is capable of approximating a regular geometry that characterizes the coverage of the obstacle 300. Thus, the problem of the prior art that the bounding box 201 needs to accurately calculate every change and morphology of the obstacle 300 is avoided, the calculation of subsequent collision checks is simplified, and at the same time, a number of obstacles 300 in the freight warehouse are not missed.
S21: the processing unit 100 builds a virtual model for characterizing the body dimensions of the unmanned forklift 200 based on model data of the unmanned forklift 200.
Model data of the unmanned forklift 200 can be pre-stored in a database according to different models of the unmanned forklift 200, the processing unit 100 in wireless connection with the unmanned forklift 200 can identify the current model of the unmanned forklift 200, and model data corresponding to the model is called from the database to construct a virtual model representing the size of the body of the unmanned forklift 200. The processing unit 100 may also construct a virtual model corresponding to the unmanned forklift 200 in advance to directly call the virtual model to plan the carrying route 500. In the invention, the unmanned forklift 200 can be a clamp rotary forklift or other intelligent forklift capable of realizing the rotary placement of the goods 400, so that the goods 400 on the goods shelf 304 can be taken, and the pose of the goods 400 can be adjusted in the process of transporting the goods 400.
S22: the processing unit 100 builds at least one bounding box 201 based on the dimensional data, pose, and virtual model of the cargo 400 carried by the unmanned forklift 200.
The cargo 400 may be formed into bounding boxes 201 of different sizes and shapes depending on the manner of placement on the unmanned forklift 200. For example, the unmanned forklift 200 can place the cargo 400 on a boom or fork in a horizontal or vertical manner. Preferably, the unmanned forklift 200 is provided with a detection mechanism for monitoring the size of the carried goods 400. The cantilever or fork of the unmanned forklift 200 is provided with a detection mechanism, which can be a photoelectric or distance sensor, so as to obtain the pose and size of the cargo 400 carried by the unmanned forklift 200, and transmit the pose and size data to the processing unit 100. Because the unmanned forklift 200 in the present invention is an intelligent forklift, it can adjust the pose of the cargo 400. Preferably, in the case that the goods 400 on the pallet 304 are not aligned with the forks, the unmanned forklift 200 can adjust the angle of the forks to take the goods 400 on the pallet 304, and the unmanned forklift 200 adjusts the pose of the goods 400 on the forks by means of the rotating gripper of the unmanned forklift 200, so as to reduce the overall occupied space of the unmanned forklift 200 and the goods 400.
Preferably, in case the processing unit 100 obtains the pose and the size of the cargo 400 carried by the unmanned forklift 200, the processing unit 100 establishes at least one bounding box 201 of the unmanned forklift 200 carrying the cargo 400 in combination with the virtual model of the unmanned forklift 200. In the case where the pose of the cargo 400 is changed, the processing unit 100 updates or reconstructs the bounding box 201 based on the changed pose of the cargo 400. The bounding box 201 refers to the smallest cube that contains the unmanned forklift 200 and the cargo 400. In this way, the present invention can realize planning of the conveyance route 500 of the unmanned forklift 200 by collision checking of the bounding box 201 and the bounding box 301.
S31: the processing unit 100 establishes a virtual channel capable of characterizing the movement track of the unmanned forklift 200 in a manner that the bounding box 201 moves along the preset carrying route 500.
The virtual aisle refers to a three-dimensional aisle formed by the unmanned forklift 200 and the bounding box 201 of the transported goods 400 after moving on the preset carrying route 500. The processing unit 100 records each smear in the moving process of the bounding box 201 in a time delay manner, so that a stereoscopic virtual channel is formed. For example, when the bounding box 201 is spherical, the bounding box 201 moves along the straight preset conveyance path 500 to form a cylinder-like virtual channel. The virtual aisle of the present invention is capable of characterizing the trajectory of movement and the space contacted by bounding box 201 (cargo 400 and unmanned forklift 200 carrying it) during movement along the carryway 500. The present invention determines whether the unmanned forklift 200 collides with the obstacle 300 under the transportation route 500 through the pre-collision between the virtual aisle and the bounding box 301, thereby planning the transportation route 500 suitable for the size of the cargo 400 and the movement of the unmanned forklift 200. Since the carrying route 500 is not a single straight line in many cases, the virtual channel formed by the present invention is a channel that extends in a curved manner in a virtual scene.
S32: the processing unit 100 cuts the virtual channel based on the three-dimensional cut surfaces of the bounding boxes 301 to form bounding boxes to be tested.
In particular, since the obstacles 300 within the freight warehouse are mostly regular geometric bodies (e.g. shelves 304), the processing unit 100 creates respective cut planes tangential to the bounding box 301 in at least three mutually perpendicular directions of the global coordinate system based on the established global coordinate system. In the case where an extended virtual channel is formed, the processing unit 100 divides the virtual channel into bounding boxes to be measured based on several bounding boxes 301 and remains within the bounding box 301 area. The shape of the virtual channel is curved and complex, and if the global collision check is performed on the virtual channel, not only the calculation amount of the processing unit 100 is increased, but also most of the collision calculations are meaningless. Therefore, the invention screens out the bounding box to be tested corresponding to the unmanned forklift 200 based on the bounding box 301 in the area where the bounding box 301 exists to perform collision detection, thereby improving the efficiency of data calculation.
S33: the processing unit 100 determines the collision relationship between the bounding box to be measured and the bounding box 301 based on the pre-collision between the bounding box to be measured and the corresponding bounding box 301 to screen out a plurality of bounding boxes to be measured and a plurality of bounding boxes 301 having the collision relationship.
The collision relationship includes intersection or inclusion. The collision relationship refers to that the bounding box to be measured and the bounding box 301 have overlap in three-dimensional space, and the two may have collision risks. The processing unit 100 determines whether the bounding box to be detected and the bounding box 301 have a collision relationship through space judgment in the global coordinate system, and then screens out a plurality of bounding boxes to be detected and a plurality of bounding boxes 301 which may have a collision relationship.
Since the bounding box 301 constructed by the present invention is formed according to the longest side of the obstacle 300. If the obstacle 300 is a regular geometric body, the pre-collision of the bounding box 301 with the virtual channel is accurate. If the obstacle 300 is irregularly solid, the bounding box 301 contains a range of true positions other than the obstacle 300. At this time, there is necessarily a large error in judging whether the unmanned forklift 200 carrying the cargo 400 collides with the obstacle 300. In the present invention, acquisition of three-dimensional collision data is cumbersome, and the required calculation amount is large. Therefore, it should be further determined whether the bounding box 301 has a collision relationship with the bounding box 201. The bounding box 301 simplifies the calculation amount of the acquisition of the virtual model of the earlier obstacle 300, but also enlarges the volume of the acquired virtual model, resulting in an error in the judgment of the subsequent collision relationship.
It should be noted that, the construction of the bounding box 301 is not performed based on each of the actual outlines of the obstacle 300, because the bounding box 301 of the obstacle 300 constructed by the actual outlines requires a large amount of computing resources, and the amount of data computation required for constructing the bounding box 301 of each of the actual outlines is not negligible. The obstacle 300 that may collide with the unmanned forklift 200 is not a majority. Therefore, the present invention screens out obstacles 300 that may collide with the unmanned forklift 200 by pre-collision of the wide range bounding box 301, and further performs high-precision bounding box 301 division for collision checking.
S34: in the case that the bounding box to be measured has a collision relationship with the bounding box 301, the processing unit 100 divides the irregular bounding box 301 into a plurality of bounding box sub-modules 302 in a segmented and/or split manner, so as to screen out the bounding box sub-modules 302 which may have a collision relationship in a manner of pre-colliding the bounding box with the bounding box to be measured through the bounding box sub-modules 302.
Since the space covered by the bounding box 301 constructed from the longest side of the obstacle 300 exceeds the actual volume of the obstacle 300, the accuracy in determining the collision relationship is too low. Therefore, after screening out a part of the bounding box 301, the invention performs secondary screening by dividing the bounding box 301 into a plurality of bounding box sub-modules 302, thereby increasing the accuracy of collision relation judgment on the basis of reducing the calculation amount of three-dimensional collision data.
Specifically, the processing unit 100 connects vertices at both ends of the irregular obstacle 300 to construct a virtual boundary capable of locally characterizing the minimum containing the obstacle 300. The processing unit 100 pre-collides the virtual boundary with the bounding box to be measured to screen out the bounding box 301 having the collision relationship. Preferably, the processing unit 100 segments the secondarily filtered bounding box 301 based on the irregular characteristics as a bounding box sub-module 302. The irregular characteristic described above refers to a bending or deformation of the obstacle 300. The above-mentioned judgment of the virtual boundary and the bounding box to be measured can obtain the relative positions of the bounding box to be measured and the bounding box 301, and exclude the bounding box to be measured far from the actual obstacle 300. The simple division manner can reduce the calculation amount in the construction of the boundary box sub-module 302, and the division and judgment process can be completed through simple global coordinate judgment.
Specifically, for example, if the obstacle 300 is a shelf having a bend. In the case where it is constructed as a bounding box 301, this bounding box 301 contains a large number of ranges of non-obstacles 300. In contrast, the present invention constructs a virtual boundary that can include the obstacle 300 with a smaller volume by connecting diagonal vertices of the obstacle 300. The processing unit 100 pre-collides the virtual boundary with the bounding box to be detected, thereby further judging the collision relationship between the bounding box to be detected and the obstacle 300, and screening out the bounding box 301 having the collision relationship. The processing unit 100 segments the secondarily filtered bounding box 301 based on the irregular characteristics of the obstacle 300, thereby obtaining a number of bounding box sub-modules 302. The processing unit 100 is based on pre-collision of several bounding box sub-modules 302 with the bounding box to be tested, thereby excluding again bounding box sub-modules 302 that do not have a collision relationship. The bounding box sub-module 302 thus obtained has a high probability of collision with the bounding box to be tested. The invention monitors the collision relation between the boundary frame 301 and the boundary frame sub-module 302 and the bounding box to be detected by adopting a pre-collision mode, only needs to acquire whether the collision relation exists or not, and does not need to acquire an actual collision intersection, thereby saving a great amount of calculation resources, and greatly improving the judgment and planning rate of the carrying route 500 by combining the simple construction mode and the simple division mode of the boundary frame 301 and increasing the working efficiency of the unmanned forklift 200.
S35: in the case of screening out the bounding boxes 301 and the bounding box sub-modules 302, the processing unit 100 divides the bounding boxes 301 and the bounding box sub-modules 302 into bounding elements to perform at least one collision check with the bounding box 201 to acquire three-dimensional collision data.
The processing unit 100 divides the number of bounding boxes 301 and the number of bounding box sub-modules 302 into a number of bounding elements in a preset interval unit. The interval units are, for example, units such as centimeters and millimeters. The invention performs point-by-point collision check on each boundary element and the bounding box 201 to acquire three-dimensional collision data of a plurality of bounding boxes 301 and a plurality of bounding box sub-modules 302 colliding with the bounding box 201. Specifically, the processing unit 100 calculates global coordinates of intersections of each boundary element with the bounding box 201, thereby storing the global coordinates of each intersection in a collective manner. Several intersection points characterize where the bounding box 201 collides with the boundary element (i.e., the unmanned forklift 200 carrying the cargo 400 and the obstacle 300). The collision range of the bounding box 301 and the bounding box 201 can be accurately acquired through calculation, a part of lines without collision relation are reserved, and the part of lines with collision relation are adjusted based on three-dimensional collision data.
In the present invention, the above-mentioned remaining part of the lines without collision relationship include not only the part of the lines without collision relationship of the unmanned forklift 200 carrying the cargo 400 on the preset carrying route 500, but also the part of the lines calculated by the processing unit 100 without collision relationship between the freight warehouse and the unmanned forklift 200 carrying the cargo 400 in the case that there is a surplus calculation force. The processing unit 100 selectively reserves a part of the route where no collision relationship exists in the following when the unmanned forklift 200 moves forward to a certain area, so that after the pose of the unmanned forklift 200 for carrying the goods 400 is changed, the unmanned forklift 200 can be controlled to change the pose of the goods 400 again to return to the preset carrying route 500. In the case where the pose of the cargo 400 on the unmanned forklift 200 is changed, the processing unit 100 calculates a partial route having no collision relationship with the unmanned forklift 400 based on the changed pose of the cargo 400. The processing unit 100 plans at least one carrying route 500 based on the continuity of the remaining partial routes without collision relationship, and is accompanied by the pose of the cargo 400 required for the unmanned forklift 200 to carry the cargo 400 through the partial routes. The continuity refers to the fact that the carrying route 500 planned by the processing unit 100 is based on continuity, not based on the pose of the cargo 400 changed by the unmanned forklift 200. When the unmanned forklift 200 reaches a certain route, the processing unit 100 controls the unmanned forklift 200 to adjust the pose of the cargo 400 to pass through the route.
Therefore, the invention avoids the situation that the changed pose of the goods 400 or the transportation route 500 collides with other places after the adjustment of the transportation route 500 with collision, and avoids the multiple adjustment of the transportation route 500 of the unmanned forklift 200. In the invention, the pose of the goods 400 carried by the unmanned forklift 200 is preferentially adjusted, and the processing unit 100 adjusts the carrying route 500 again under the condition that the unmanned forklift 200 cannot pass through the current route even after the pose of the goods 400 is adjusted, so that the plurality of times of adjustment of the carrying route 500 of the unmanned forklift 200 is prevented.
Preferably, the processing unit 100 represents the bounding box 201 as a parametric equation and the boundary element as a standard equation, so that the intersection point is calculated based on the parametric equation and the standard equation. The parametric equation can be an equation that delineates bounding box 201 with parameters of the beginning of bounding box 201 and the end of bounding box 201. The standard equation can be an equation for representing a face in global coordinates. For example, the parametric equation can be: f (n) =f1+n (f 2-f 1), where f1 is the start of bounding box 201 and f2 is the end of bounding box 201. The standard equation can be: ax+by+cz+d=0, wherein a, b, c, d is the coefficient of the boundary element in the global coordinates, respectively. Preferably, the processing unit 100 substitutes the parameter equation of the bounding box 201 into the standard equation of the boundary element to calculate the n value. If n is equal to or greater than 0 and equal to or less than 1, the bounding box 201 is judged to intersect with the boundary element. At this time, the specific intersection point coordinates can be obtained by substituting the n value into the parameter equation. If n <0 or n >1, then bounding box 201 is determined to be disjoint from the boundary element. The processing unit 100 stores the coordinates of the intersections in a collective manner as three-dimensional collision data.
S41: the processing unit 100 adjusts the pose of the cargo 400 carried by the unmanned forklift 200 based on the three-dimensional collision data.
The unmanned forklift 200 of the present invention is capable of carrying cargo 400 by way of a clasping rotation. Thereby, the pose of the cargo 400 carried by the unmanned forklift 200 can be adjusted. The sizes of the several cargoes 400 are different and the manner in which the unmanned forklift 200 is carried is also different. If the unmanned forklift 200 carries the cargo 400 in a horizontal or vertical manner, the size and shape of the bounding box 201 formed by the unmanned forklift may be different, so that the different positions of the cargo 400 may determine whether the unmanned forklift 200 can pass the obstacle 300 under the predetermined carrying route 500.
Preferably, the processing unit 100 controls the unmanned forklift 200 to change the pose of the cargo 400 in a translational or rotational manner based on the three-dimensional collision data so that the bounding box 201 does not collide with the bounding box 301. The processing unit 100 determines whether the unmanned forklift 200 can be prevented from colliding with the obstacle 300 after the goods 400 are translated or rotated based on the intersection point between the bounding box 201 and the bounding box 301 in the three-dimensional collision data. The present invention enables the unmanned forklift 200 to pass through a previously non-passing aisle or obstacle 300 by changing the pose of the cargo 400. For large-scale transportation, it is not necessary to re-plan the route 500 upon encountering an obstacle 300. In some cases, the cargo 400 can be passed through a certain passage or obstacle 300 by changing the pose of the cargo 400. For example, by tilting the cargo 400 through a certain height-limited passage. The lack of consideration of the pose of the cargo 400 during obstacle avoidance transportation in the prior art results in the need for the unmanned forklift 200 to re-plan its travel route 500 when encountering an "impenetrable" aisle or obstacle 300. However, the "no pass" is not completely no pass. According to the invention, through the acquisition of the three-dimensional collision data, the unmanned forklift 200 is controlled to adjust the position and the posture of the goods 400 in the clamping rotation mode on the basis of the acquisition, so that the unmanned forklift 200 can avoid the obstacle in a targeted manner in a passage or an obstacle 300. Particularly when encountering a height-limited passage, the height of the cargo 400 can be reduced by adjusting the vertical placement of the cargo 400 to be inclined or horizontal to pass through the height-limited passage 303. In the above judging process, no intervention of staff is needed, intelligent control of the unmanned forklift 200 is realized through less calculation amount, and transportation efficiency of the unmanned forklift 200 is not affected.
S42: the processing unit 100 plans the handling route 500 of the unmanned forklift 200 based on the three-dimensional collision data.
In the case where collision of the unmanned forklift 200 with the obstacle 300 cannot be avoided even if the pose of the cargo 400 is changed, the processing unit 100 re-plans the carrying route 500 of the unmanned forklift 200. The processing unit 100 constructs a transport route 500 through which the unmanned forklift 200 can safely pass based on a combination of a plurality of bounding boxes 301 through which the unmanned forklift can safely pass. After the above-mentioned filtering calculation of the several bounding boxes 301, the processing unit 100 can obtain the several bounding boxes 301 through which the unmanned forklift 200 can pass. The processing unit 100 re-plans the handling route 500 based on the screened several bounding boxes 301. Preferably, the processing unit 100 is able to store several bounding boxes 301 that are screened out to enable the unmanned forklift 200 to safely pass through, to be invoked during transportation by another unmanned forklift 200.
According to the invention, through the screening of the plurality of bounding boxes 301, the calculation amount of collision relation determination and collision inspection can be effectively reduced, the calculation amount can be used as the data storage for planning the subsequent carrying route 500, whether the carrying route 500 is matched with the size of the goods 400 or not can be rapidly judged in the goods transportation process of the unmanned forklift 200, the carrying route 500 which can be moved by the unmanned forklift 200 can be rapidly planned under the condition that the carrying route is not matched with the size of the goods 400, and the goods transportation efficiency of the unmanned forklift 200 is improved.
Throughout this document, the word "preferably" is used in a generic sense to mean only one alternative, and not to be construed as necessarily required, so that the applicant reserves the right to forego or delete the relevant preferred feature at any time.
It should be noted that the above-described embodiments are exemplary, and that a person skilled in the art, in light of the present disclosure, may devise various solutions that fall within the scope of the present disclosure and fall within the scope of the present disclosure. It should be understood by those skilled in the art that the present description and drawings are illustrative and not limiting to the claims. The scope of the invention is defined by the claims and their equivalents. The description of the invention includes various inventive concepts such as "preferably," "according to a preferred embodiment," or "optionally," which each mean that the corresponding paragraph discloses a separate concept, applicant reserves the right to filed a divisional application according to each inventive concept.
Claims (10)
1. A method of cargo handling path planning, the method comprising:
constructing a plurality of bounding boxes (301) in a virtual scene transported by the unmanned forklift (200) based on the obstacle information;
Constructing at least one bounding box (201) based on model data of the unmanned forklift (200) and size data of the transported goods (400);
pre-crash on at least one handling route (500) based on a number of said bounding boxes (301) and at least one said bounding box (201) to determine if there is a risk of transportation, and in case of a risk of transportation, crash-checking said bounding boxes (301) with said bounding boxes (201) to obtain three-dimensional crash data;
-planning the pose of the cargo (400) carried by the unmanned forklift (200) and/or the handling route (500) of the unmanned forklift (200) based on the three-dimensional collision data.
2. The method of cargo handling route planning according to claim 1, wherein the method of constructing a number of said bounding boxes (301) comprises:
establishing a global coordinate system under a virtual scene based on the obstacle information of the freight warehouse with the completed digital twinning;
-establishing a geometry corresponding to the obstacle (300) in the global coordinate system based on the longest edge of the obstacle (300) in the obstacle information, and taking the geometry as the bounding box (301).
3. The method of cargo handling route planning according to claim 1 or 2, characterized in that the method of constructing the bounding box (201) comprises:
Establishing a virtual model for characterizing the body size of the unmanned forklift (200) based on model data of the unmanned forklift (200);
constructing at least one bounding box (201) containing the unmanned forklift (200) and the goods (400) based on the virtual model and the pose and the size data of the goods (400) when the goods (400) are carried by the unmanned forklift (200); wherein,
in case the pose of the cargo (400) is changed, the bounding box (201) is updated or reconstructed based on the changed pose of the cargo (400).
4. A method of planning a cargo handling route according to any of claims 1 to 3, wherein the method further comprises:
establishing a virtual channel capable of representing the movement track of the unmanned forklift (200) in a mode that the bounding box (201) moves along a preset carrying route (500);
-cutting the virtual channel based on three-dimensional cut planes of several of the bounding boxes (301) to form several bounding boxes to be tested.
5. The method of cargo handling path planning according to any one of claims 1 to 4, wherein the method of pre-crash comprises:
and judging the collision relation between the bounding box to be tested and the corresponding bounding box (301) so as to screen out a plurality of bounding boxes to be tested and a plurality of bounding boxes (301) with the collision relation.
6. The method of cargo handling route planning according to any one of claims 1 to 5, further comprising:
under the condition that the bounding box to be detected and the bounding box (301) have the collision relation, dividing the irregular bounding box (301) into a plurality of bounding box sub-modules (302) in a segmented and/or split mode, and screening out the bounding box sub-modules (302) possibly having the collision relation in a mode of pre-collision between the bounding box sub-modules (302) and the bounding box to be detected.
7. The method of cargo handling path planning according to any one of claims 1 to 6, wherein the method of acquiring the three-dimensional collision data comprises:
under the condition that a plurality of boundary boxes (301) and a plurality of boundary box sub-modules (302) are screened, dividing the boundary boxes (301) and the boundary box sub-modules (302) into a plurality of boundary elements to acquire the three-dimensional collision data in a mode of performing at least one collision check with the bounding box (201).
8. The method of cargo handling route planning according to any of claims 1-7, further comprising:
controlling the unmanned forklift (200) to change the pose of the goods (400) in a translational or rotational manner based on the three-dimensional collision data so that the bounding box (201) does not collide with the bounding box (301);
After changing the pose of the goods (400), when the bounding box (201) and the bounding box (301) still have the collision relation, a carrying route (500) through which the unmanned forklift (200) can safely pass is planned based on a plurality of bounding boxes (301) which do not have the collision relation.
9. A cargo handling path planning system comprising an unmanned fork lift truck (200) carrying cargo (400) in the form of clasping rotating cargo and a processing unit (1O 0) arranged in a dispatch room of a freight warehouse, characterized in that the processing unit (100) is configured to:
constructing a plurality of bounding boxes (301) in a virtual scene transported by the unmanned forklift (200) based on obstacle information;
constructing at least one bounding box (201) based on model data of the unmanned forklift (200) and size data of the transported goods (400);
pre-crash on at least one handling route (500) based on a number of said bounding boxes (301) and at least one said bounding box (201) to determine if there is a risk of transportation, and in case of a risk of transportation, crash-checking said bounding boxes (301) with said bounding boxes (201) to obtain three-dimensional crash data;
-planning the pose of the cargo (400) carried by the unmanned forklift (200) and/or the handling route (500) of the unmanned forklift (200) based on the three-dimensional collision data.
10. The cargo handling route planning system according to claim 9, wherein the processing unit (100) is further configured to:
controlling the unmanned forklift (200) to change the pose of the goods (400) in a translational or rotational manner based on the three-dimensional collision data so that the bounding box (201) does not collide with the bounding box (301);
after changing the pose of the goods (400), when the bounding box (201) and the bounding box (301) still have collision relation, a transportation route (500) which can safely pass through by the unmanned forklift (200) is planned based on a plurality of bounding boxes (301) which do not have collision relation.
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Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN118569682A (en) * | 2024-07-29 | 2024-08-30 | 北京达美盛软件股份有限公司 | Planning system and method for industrial transportation assembly line |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CA3224047A1 (en) * | 2016-08-26 | 2018-03-01 | Crown Equipment Corporation | Materials handling vehicle path validation and dynamic path modification |
CN210527662U (en) * | 2019-08-23 | 2020-05-15 | 成都航发机器人有限公司 | L-shaped transport vehicle |
CN111880525A (en) * | 2020-06-15 | 2020-11-03 | 北京旷视机器人技术有限公司 | Robot obstacle avoidance method and device, electronic equipment and readable storage medium |
CN114387407A (en) * | 2021-11-18 | 2022-04-22 | 桂林电子科技大学 | Large cargo transportation trafficability assessment method based on three-dimensional channel model |
CN115027464A (en) * | 2022-07-29 | 2022-09-09 | 西安电子科技大学芜湖研究院 | Automatic driving collision detection method based on direction bounding box |
CN115407778A (en) * | 2022-08-31 | 2022-11-29 | 广州蓝胖子移动科技有限公司 | Collision detection area updating method and device and computer-readable storage medium |
-
2024
- 2024-01-15 CN CN202410059352.8A patent/CN117873099A/en active Pending
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CA3224047A1 (en) * | 2016-08-26 | 2018-03-01 | Crown Equipment Corporation | Materials handling vehicle path validation and dynamic path modification |
CN210527662U (en) * | 2019-08-23 | 2020-05-15 | 成都航发机器人有限公司 | L-shaped transport vehicle |
CN111880525A (en) * | 2020-06-15 | 2020-11-03 | 北京旷视机器人技术有限公司 | Robot obstacle avoidance method and device, electronic equipment and readable storage medium |
CN114387407A (en) * | 2021-11-18 | 2022-04-22 | 桂林电子科技大学 | Large cargo transportation trafficability assessment method based on three-dimensional channel model |
CN115027464A (en) * | 2022-07-29 | 2022-09-09 | 西安电子科技大学芜湖研究院 | Automatic driving collision detection method based on direction bounding box |
CN115407778A (en) * | 2022-08-31 | 2022-11-29 | 广州蓝胖子移动科技有限公司 | Collision detection area updating method and device and computer-readable storage medium |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN118569682A (en) * | 2024-07-29 | 2024-08-30 | 北京达美盛软件股份有限公司 | Planning system and method for industrial transportation assembly line |
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