Unmanned fork truck and fork control method and controller thereof

Abstract

An unmanned forklift and its fork control method and controller are disclosed, wherein the unmanned forklift includes forks and a controller, the controller being configured to perform the following steps: receiving a lateral step length, a rotation step length, and a target direction of the forks; controlling the forks to perform lateral movement according to the lateral step length and the target direction; and controlling the forks to perform rotation movement according to the rotation step length and the target direction.

Description

Technical Field

[0001] This application relates to the field of warehousing and logistics technology, specifically to an unmanned forklift and its fork control method and controller. Background Technology

[0002] With the rapid development of the logistics industry, unmanned forklifts are being used more and more widely in warehouse logistics. In warehouse environments, the layout of goods storage is complex and diverse, requiring unmanned forklifts to accurately pick up and place goods.

[0003] In addition to moving up and down and forward and backward during operation, unmanned forklifts sometimes need to rotate and / or move the forks laterally to align the goods to be picked up when picking up or placing goods that are not aligned with the forks.

[0004] Traditional forklift operation relies on manual labor, requiring operators to adjust the fork position based on experience to adapt to different goods and rack layouts. Even in some existing automated forklift technologies, there are issues with insufficient precision, low efficiency, and poor adaptability to complex scenarios in the lateral movement and rotation of the forks. For example, in warehouse environments with narrow aisle racks, where goods are stored at high density and aisles are narrow, the precision requirements for the lateral movement and rotation of the automated forklift forks are extremely high. Furthermore, when dealing with palletized goods of different sizes, the forks need to be able to quickly and accurately adjust their position for picking up and stacking. Current automated forklift algorithms are not yet perfect in these operations, easily leading to goods collisions, failed picking, or inaccurate placement, affecting the efficiency and accuracy of the entire logistics operation. Summary of the Invention

[0005] In view of this, this application provides a fork control method for an unmanned forklift, which realizes the alignment of the forks and goods of the unmanned forklift and the picking and placing of goods. This application also provides an unmanned forklift and controller using this method.

[0006] According to one embodiment of this application, an unmanned forklift is provided, wherein the unmanned forklift includes forks and a controller, the controller being configured to perform the following steps: receiving a lateral step length, a rotation step length, and a target direction of the forks; controlling the forks to perform lateral movement according to the lateral step length and the target direction; and controlling the forks to perform rotation movement according to the rotation step length and the target direction.

[0007] According to one embodiment of this application, the lateral movement is performed before the rotational movement. According to another embodiment, the rotational movement is performed before the lateral movement. According to yet another embodiment, the lateral movement and the rotational movement are performed simultaneously.

[0008] According to one embodiment of this application, the steps further include: determining a target lateral movement position of the forks based on the size of the vehicle and the size of the cargo carried by the vehicle; receiving the lateral movement position of the forks; and if the difference between the lateral movement position and the target lateral movement position is greater than or equal to the lateral movement step, causing the forks to perform the lateral movement.

[0009] According to one embodiment of this application, the step further includes: if the difference between the lateral position and the target lateral position is less than the lateral step length, causing the fork to perform the rotational movement.

[0010] According to one embodiment of this application, the steps further include: determining a target rotation position of the fork based on the size of the vehicle and the size of the cargo carried by the vehicle; receiving the rotation position of the fork; and if the difference between the rotation position and the target rotation position is greater than or equal to the rotation step size, causing the fork to perform the rotational movement.

[0011] According to one embodiment of this application, the step further includes: if the difference between the rotational position and the target rotational position is less than the rotational step size, causing the fork to perform the lateral movement.

[0012] According to one embodiment of this application, the step further includes: determining the projection of the fork onto the cross-section of the passageway traveled by the vehicle based on the lateral position and the rotational position; if the projection of the fork does not fall within the width range of the passageway, then controlling the fork to stop the currently performed rotational movement or lateral movement.

[0013] According to one embodiment of this application, the step further includes: if the projection of the fork does not fall within the width range of the channel, then further controlling the fork to switch between the rotational motion and the lateral motion.

[0014] According to one embodiment of this application, the steps further include: determining the motion mode of the current step of the fork movement; determining one or more possible motion modes for the next step of the fork movement; determining a first coefficient for each of the one or more possible motion modes; determining the motion cost value of each of the one or more possible motion modes based on the first coefficient; and controlling the fork to execute the motion mode with the minimum motion cost value.

[0015] According to one embodiment of this application, the steps further include: determining a second coefficient for each of the one or more possible motion modes; determining the motion cost of each of the one or more possible motion modes based on the first coefficient and the second coefficient; and controlling the fork to execute the motion mode with the minimum motion cost.

[0016] According to an embodiment of this application, the steps further include: determining a third coefficient for each of the one or more possible motion modes; determining the motion cost of each of the one or more possible motion modes based on the first coefficient, the second coefficient, and the third coefficient; and controlling the fork (104) to execute the motion mode with the minimum motion cost.

[0017] According to one embodiment of this application, the step further includes: wherein when the second coefficient of one of the one or more possible motion modes is greater than 1, the third coefficient of the one is set to 1.

[0018] According to one embodiment of this application, the step further includes: wherein the current step motion includes: lateral movement and / or rotational movement of the forks.

[0019] According to an embodiment of this application, the step further includes: wherein the one or more possible motion modes include one or more of the following: positive lateral movement, negative lateral movement, positive rotational movement, and negative rotational movement.

[0020] According to an embodiment of this application, the steps further include: if one or more of the plurality of candidates have reached a limit value, then determining the one with the smallest motion cost among the other one or more possible motion modes according to the first coefficient, the second coefficient and the third coefficient; and controlling the fork to execute the motion mode with the smallest motion cost.

[0021] According to one embodiment of this application, the step further includes: determining whether the initial movement of the forks of the vehicle is a lateral movement or a rotational movement based on the lateral step length, the rotation step length, the target lateral position, and the target rotational position.

[0022] According to another embodiment of this application, a fork control method for an unmanned forklift is provided, which includes the step of controlling the forks of the unmanned forklift according to any of the foregoing embodiments to perform lateral movement and / or rotational movement.

[0023] According to another embodiment of this application, a controller is provided for executing program instructions, including controlling the forks of an unmanned forklift as described in any of the foregoing embodiments to perform lateral and / or rotational movements. Attached Figure Description

[0024] The accompanying drawings are provided to further illustrate the present application and form part of the specification. They are used together with the following detailed description to explain the present application, but do not constitute a limitation thereof. In the drawings: Figure 1AA block diagram illustrating an unmanned forklift according to an embodiment of this application.

[0025] Figure 1B A schematic diagram illustrating the application of an unmanned forklift according to an embodiment of this application in a warehouse.

[0026] Figure 2 This is a flowchart illustrating another part of the unmanned forklift fork lateral / rotation method according to an embodiment of this application.

[0027] Figure 3A A top view illustrating the lateral / rotation of the forks to a position according to an embodiment of this application.

[0028] Figure 3B A top view illustrating the lateral / rotation of the forks to a position according to another embodiment of this application.

[0029] Figure 4 A schematic diagram illustrating the displacement and rotation angle of the rotation axis and lateral axis of a fork according to an embodiment of this application.

[0030] Figure 5 This is a flowchart illustrating another part of the unmanned forklift fork lateral / rotation method according to an embodiment of this application.

[0031] Figure 6 A schematic diagram illustrating the displacement and rotation angle of the rotation axis and lateral axis of a fork according to an embodiment of this application. Detailed Implementation

[0032] The following disclosure provides various implementations or examples that can be used to achieve different features of this disclosure. Specific examples of components and configurations described below are for simplification purposes. It is understood that these descriptions are illustrative only and are not intended to limit the scope of this disclosure. For example, in the following description, forming a first feature on or over a second feature may include, in some embodiments, the first and second features being in direct contact with each other; and may also include, in some embodiments, additional components being formed between the first and second features, such that the first and second features may not be in direct contact. Furthermore, component symbols and / or reference numerals may be reused in multiple embodiments of this disclosure. Such reuse is for the purpose of brevity and clarity and does not in itself represent a relationship between the different embodiments and / or configurations discussed.

[0033] Automated forklifts are widely used in intelligent logistics and automated warehousing, enabling the autonomous handling and retrieval of goods without human drivers. Automated forklifts are typically equipped with sensors, navigation systems, and controllers to ensure efficient and safe operation. With the rapid growth of modern logistics demands, automated forklifts have become an important tool for improving operational efficiency and reducing labor costs.

[0034] Path planning for automated forklifts is a core technology that determines the efficiency and accuracy of their goods storage and retrieval. Precise fork path planning enables automated forklifts to achieve path planning, obstacle avoidance, and accurate goods storage and retrieval, ensuring efficient operation in various complex environments. However, in existing technologies, the lateral movement and / or rotation planning of the forks in automated forklifts often relies on manually assigning a fixed speed and visually judging the required space. This lack of planning for the fork's position during lateral movement / rotation not only results in poor stability and low efficiency but also increases the risk of collisions during lateral movement / rotation, potentially leading to hazards.

[0035] In view of this, this application proposes a fork lateral movement / rotation planning method for an unmanned forklift and an unmanned forklift using the method to solve this problem.

[0036] For ease of explanation, the relevant hardware of the unmanned forklift is defined in this invention as follows: Processor: Responsible for performing core functions such as calculation, control, and decision-making. It receives data from sensors, runs control algorithms, and directs actuators to complete tasks. Common processor types include: Central Processing Unit (CPU), Digital Signal Processor (DSP), Microcontroller Unit (MCU), etc. In this article, "processor" can refer to a collection of processors used to perform the same or different tasks.

[0037] Memory: Used to store data or program algorithms, etc. In this document, memory can refer to a collection of memories used to perform the same or different tasks. Optionally, the processor, sensor, and controller in this invention may each include their own memory / storage unit.

[0038] Controller: At the hardware level, a controller typically includes a processor and memory. Optionally, it may also include input / output interfaces, a motherboard, peripheral circuits, and components. At the software level, it typically includes control algorithms, operating systems, and communication protocols. In this article, "controller" can refer to a collection of controllers used to perform the same or different tasks.

[0039] refer to Figure 1A , Figure 1AThis is a block diagram illustrating an unmanned forklift 100 according to an embodiment of this application. In some embodiments, the unmanned forklift 100 may include a controller 102, a sensor 103, and forks 104. The controller 102 includes a processor 1021. In some embodiments, the controller 102 or processor 1021 is operatively coupled to the sensor 103. In some embodiments, the controller 102 or processor 1021 works with the sensor 103 to implement the fork lateral / rotation method proposed in this application. In some embodiments, the controller 102 may be an integrated element. The controller 102 may consist of one or more control units / processing units. The processor 1021 may include a computing unit or a core computing unit. The processor 1021 may accept data from the sensor 103 or other hardware devices. The processor 1021 may process data from the sensor 103 or other hardware devices.

[0040] In some embodiments, sensor 103 may be an integrated element. Sensor 103 can be considered as being composed of multiple sensor elements. Sensor 103 includes, for example, but not limited to, lidar, vision sensors, inertial measurement units, etc.

[0041] refer to Figure 1B , Figure 1B This diagram illustrates the application of an unmanned forklift 100 according to an embodiment of this application in a warehouse. In some embodiments, the unmanned forklift 100... Figure 1B The unmanned forklift 100 operates and performs tasks within the warehouse shown. It can retrieve goods from the warehouse area according to instructions and precisely place them in designated locations. Furthermore, with the cooperation of sensors 103 and processor 1021, it plans the path for the forks during lateral movement and rotation, avoiding collisions and improving operational efficiency. It should be noted that... Figure 1B The demonstration of the unmanned forklift 100 is merely illustrative and is not intended to limit the scope of this application.

[0042] Figure 2 This diagram illustrates a method for lateral movement / rotation of the forks of an unmanned forklift according to an embodiment of this application. While the same results can be obtained substantially, this application is not limited to strictly adhering to this method. Figure 2 Follow the steps shown in the diagram. It should be noted that... Figure 2 The illustrated process steps are not entirely limited to unmanned forklifts. In other embodiments, Figure 2 The illustrated process steps can be applied to any smart mobile device. Subsequent embodiments will be accompanied by... Figure 1A and Figure 1B As an example, in some embodiments, the steps of the unmanned forklift fork lateral movement / rotation method 20 may be performed by different control units / processing units in controller 102 or by the same control unit / processing unit.

[0043] The fork lateral movement / rotation method 20 of the unmanned forklift includes: Step 200: Determine whether to pick up or place goods on the left or right side.

[0044] In some embodiments, the unmanned forklift 100 receives instructions from a host computer (not shown) to unload goods on the left or right side of the aisle (e.g., instructions sent to the unmanned forklift 100 via wireless communication). The processor 1021 executes a corresponding algorithm based on the received instructions and controls the forks 104 to rotate / laterally move in the corresponding direction. For example, if the unmanned forklift 100 receives an instruction to unload on the right side of the aisle, the processor 1021 determines that the forks 104 should rotate to the right and laterally move to the left. In subsequent steps, the processor 1021 further determines whether the forks 104 should perform the lateral movement first, the rotation movement first, or both simultaneously.

[0045] In some embodiments, the unmanned forklift 100 receives instructions from a host computer (not shown) to retrieve goods from the left or right side of the aisle (e.g., instructions sent to the unmanned forklift 100 via wireless communication). The processor 1021 controls the forks 104 to rotate / laterally move in the corresponding direction based on the received instructions. For example, if the unmanned forklift 100 receives an instruction to retrieve goods from the right side of the aisle, the processor 1021 determines that the forks 104 should rotate to the right and laterally move to the left. In subsequent steps, the processor 1021 further determines whether the forks 104 should perform the lateral movement first, the rotation movement first, or both simultaneously.

[0046] In some embodiments, upon receiving an instruction to pick up or place goods on the right side of the aisle, the processor 1021 will control the forks 104 to rotate to the right about the rotation axis 301 in subsequent steps (in... Figure 3A and 3B In the illustrated embodiment, this is equivalent to clockwise rotation; conversely, upon receiving an instruction to pick up or place goods on the left side of the aisle, in subsequent steps, the processor 1021 will control the forks 104 to rotate to the left about the rotation axis 301 (in... Figure 3A and 3B The embodiment shown is equivalent to a counterclockwise rotation.

[0047] Step 201: The processor 1021 determines whether the unmanned forklift 100 is operating in mode 201a or mode 201b. If it is mode 201a, proceed to step 202; if it is mode 201b, proceed to step 202. Figure 5The method flow is described below. In some embodiments, modes 201a and 201b correspond to the single-path and multi-path operating modes of the unmanned forklift 100, respectively. In some embodiments, the single-path operating mode means that the processor 1021 can only control the rotation or lateral movement of the forks 104 of the unmanned forklift 100 at any given time. In other embodiments, the multi-path operating mode means that the processor 1021 can simultaneously control the rotation and lateral movement of the forks 104 of the unmanned forklift 100. The method described in this application is applicable to both single-path and multi-path unmanned forklifts. Depending on the hardware support, multi-path operation can save motion control time, provided the unmanned forklift equipment allows it.

[0048] refer to Figure 3A and 3B , Figure 3A The diagram illustrates a top view of a certain position of the forks 104 during the lateral / rotational movement of an unmanned forklift 100 in an unloaded state according to an embodiment of this application. Figure 3A The unmanned forklift 100 shown only includes the forks 104 and the rotating shaft, omitting other parts such as the vehicle body. The forks 104 generally consist of a left fork and a right fork. Both forks are connected to a fork fixing device at their base. The fork fixing device is fixedly connected to a beam at its center. This beam can rotate, laterally move, or rise and fall about the end away from the fork fixing device, thereby causing the forks 104 to rotate, laterally move, or rise and fall.

[0049] In some embodiments, for example, when the forks 104 are in an unloaded state, the processor 1021 calls the length L and width W of the forks 104 of the forklift 100, such as... Figure 3A As shown.

[0050] Figure 3B This diagram illustrates a top view of a specific position during the lateral / rotational movement of the forks 104 of an unmanned forklift 100 in a loaded state, according to an embodiment of this application. In some embodiments, for example, when the forks 104 are in a loaded state, the processor 1021 obtains the length L' and width W' of the cargo on the forks 104 via a sensor 103 (e.g., a laser sensor or a vision sensor), such as... Figure 3B As shown. In some embodiments, L may be greater than, equal to, or less than L'; in other embodiments, W may be greater than, equal to, or less than W'. To avoid collisions between the unmanned forklift 104 and the aisle boundary, the method disclosed in this application shall be used in the calculations of the larger of L and L' and W and W' in the steps detailed below.

[0051] In some embodiments, the length L' and width W' of the goods carried by the forks 104 can be transmitted wirelessly to the unmanned forklift 100 by a host computer (not shown) in the control room. In other embodiments, the length L' and width W' of the goods carried by the forks 104 can be obtained through data exchange between the unmanned forklift 100 and the RF tag on the goods to be picked up.

[0052] In some embodiments, the width m of the passageway traveled by the unmanned forklift 100 is obtained by sensor 103 (e.g., 2D / 3D LiDAR). In another embodiment, the width m of the passageway traveled by the forklift 100 can be matched from a preset list of passageway widths based on the forklift's location in the warehouse. In another embodiment, an RF tag can be placed at the entrance of the passageway. When the unmanned forklift 100 travels to the entrance of a passageway, the forklift 100 senses the RF tag and selects the passageway width m corresponding to the RF tag value from a preset list of passageway widths m. In another embodiment, the value of the passageway width m can also be manually input into the controller 102 of the forklift 100 after the unmanned forklift 100 is started via an input device (e.g., an external device such as a mouse or keyboard connected to the controller of the forklift 100).

[0053] Processor 1021 calculates the distance d from the root of fork 104 to the rotation axis 301 of fork 104. For example... Figure 3A and 3B As shown, the fork 104 can rotate within a range of 0-180° around the rotation axis 301, and the rotation angle of the rotation axis of the fork 104 is defined as 0° when picking up goods on the left and 180° when picking up goods on the right. The fork 104 can also use the intersection of the rotation axis 301 and the lateral axis 302 as an anchor point p, and point p can move laterally left and right along the lateral axis 302. In the exemplary embodiment of this application, the lateral axis is... Figure 3A and 3B The x-axis is shown. The origin O of the coordinate system is defined as the intersection of the center of the channel and the x-axis.

[0054] Step 201 further includes: processor 1021 determining an initial rotation angle θ0 of rotation axis 301 based on data obtained from sensor 103 (e.g., angle sensor), and processor 1021 determining an initial position p0 of transverse axis 302 based on data obtained from another sensor 103 (e.g., distance sensor).

[0055] Step 201 further includes: the processor 1021 calling preset iteration angle ∆θ of the rotation axis 301 and iteration displacement ∆p of the transverse axis 302. ∆θ represents the increment of the rotation angle of the rotation axis 301 in each iteration; ∆p represents the increment of the displacement of the transverse axis 302 in each iteration. ∆θ and ∆p can be selected with appropriate values ​​according to actual operation requirements. In some embodiments, the value of the rotation angle increment ∆θ can be 0.1°, 0.2°, 0.5°, 1°, 1.5°, 2°, 2.5°, 3°, 5°, 8°, 10°, etc. In some embodiments, the value of the displacement increment ∆p can be 0.01m, 0.02m, 0.05m, 0.1m, 0.2m, etc. The iteration frequency of the algorithm can be 0.1s / time, 0.2s / time, 0.5s / time, 1s / time, 1.5s / time, 2s / time, etc.

[0056] Step 201 further includes: the processor 1021 calling a preset algorithm E1 to determine the target angle of the rotation axis 301. and the target displacement of the transverse axis 302 .

[0057] In formula E1, W refers to Figure 3A The width W of the forks 104 in the middle and Figure 3B The larger of the width W' of the goods shown; similarly, L in formula E1 refers to Figure 3A The length L of the fork 104 in the middle and Figure 3B The larger of the lengths L' of the goods shown.

[0058] In mode 201a, step 202 includes: processor 1021 invoking a preset algorithm E2 to determine the initial movement mode of fork 104. For example, in some embodiments, processor 1021 determines according to algorithm E2 that fork 104 first rotates around rotation axis 301. In other embodiments, processor 1021 determines according to algorithm E2 that fork 104 first moves laterally along transverse axis 302.

[0059] Q= E2 Formula E2 determines whether the initial motion is a rotational or lateral movement of the fork 104 based on the ratio of the total iteration step size of the rotational movement to the total iteration step size of the lateral movement. If Q is less than 1, it indicates that the total iteration step size of the lateral movement is larger, and the processor 1021 prioritizes the lateral movement of the fork 104 during iteration. Conversely, if Q is greater than 1, it indicates that the total iteration step size of the rotational movement is larger, and the processor 1021 prioritizes the rotational movement of the fork 104 during iteration. This reduces the number of times different movements are switched during the iteration process (e.g., switching from the rotational movement of the fork 104 to the lateral movement).

[0060] In other embodiments, the start movement mode of the forks of the unmanned forklift 100 is directly issued by a host computer (not shown) via wireless communication, without determining the start movement mode of the forks 104 through the method described in step 202. For example, when picking up goods on the right side, the forklift 100 receives an instruction from the host computer instructing the forks 104 to start rotating first. After receiving the instruction, the processor 1021 controls the forks 104 to change from a stationary state to rotating around the rotation axis 301.

[0061] Step 203: The processor 1021 determines whether the next movement of the fork 104 is a lateral movement or a rotation, and determines the direction of movement, based on the initial movement mode of the fork 104 determined in step 202. In some embodiments, for the fork 104, there are two types of movement: rotation about the rotation axis 301 and lateral movement along the lateral axis 302. In one embodiment, for the fork 104, there are two directions of movement: positive, i.e., towards the target, and negative, i.e. away from the target. For example, when the goods are on the right side of the aisle, the direction of the fork 104 rotating to the right is a positive rotation. At the same time, in order to allow the fork 104 sufficient space to rotate to the right without colliding with the goods or the aisle boundary, the direction of the lateral movement axis 302 moving to the left is a positive lateral movement. The combination of each type of movement and each direction of movement is called a movement mode. Therefore, the fork 104 in this invention has four motion modes: positive rotation around the rotation axis 301, negative rotation around the rotation axis 301, positive lateral movement along the lateral axis 302, and negative lateral movement along the lateral axis 302. As long as the collision boundary condition is not met, the fork 104 will have these four possible motion modes in each motion iteration. To make the entire motion process more energy-efficient and effective, the processor 1021 should select the motion mode with the lowest motion cost from the above four possible motion modes and control the fork 104 to execute that motion mode. This application determines the motion cost of each of the above four possible motion modes using the following three weighting coefficients, as shown in Table 1: Table 1: Weighting coefficients of exercise cost If the current movement of fork 104 is a lateral movement, and the next movement is a rotation; or if the current movement of fork 104 is a rotation, and the next movement is a lateral movement, then the weighting coefficient 3 in Table 1 should be set to 1. This is because rotation and lateral movement are two different movement types of fork 104, and therefore it does not involve whether the direction of the next movement of fork 104 is the same as the direction of the current movement (either positive or negative). Only when the next movement of fork 104 is either a lateral movement or a rotation can we discuss whether the directions of the next and current movements are the same.

[0062] The motion cost of each of the four possible motion modes of the next movement of the fork 104 can be calculated using the following formula based on the three weighting coefficients in Table 1: The motion cost of the next move = the cumulative motion cost of the current move + weighting coefficient 1 Weighting coefficient 2 Weighting coefficient 3 In the formula, "the cumulative motion cost of the current step" refers to the arithmetic sum of the motion cost values ​​of each step performed by the fork 104. The logic behind setting the weight coefficients in Table 1 is that when both the next step and the current step are in the target direction and are either lateral or rotational, the motion cost value of the next step is the lowest, thus ensuring the continuity of motion iteration in the same direction. During the motion iteration process of the fork 104, combined with boundary conditions (see the explanation of step 205), motion patterns that cause collisions between the fork 104 and the boundary of the passage / or the goods being transported will be removed and will not be iterated.

[0063] For example, as mentioned earlier, each movement of the fork 104 includes four possible movement modes: forward rotation, negative rotation, forward lateral movement, and negative lateral movement. If step 202 determines that the current movement mode of the fork 104 is forward rotation, and assuming that the "cumulative motion cost value of the current movement" is 0.48, then the motion cost value of each of the four possible movement modes of the next movement of the fork 104 can be calculated using the above-mentioned motion cost value calculation formula based on the three weighting coefficient values ​​in Table 1. Motion cost of motion mode 1 (forward rotation): 0.48 + 0.6 1.0 0.8 = 0.96; Motion cost of Motion Mode 2 (Negative Rotation): 0.48 + 2.0 1.0 1.3 = 3.08; Motion cost of motion mode 3 (positive lateral traverse): 0.48 + 0.6 1.2 1 = 1.2; Motion cost of Motion Mode 4 (Negative Lateral Movement): 0.48 + 2.0 1.2 1 = 2.88.

[0064] Therefore, when the current movement of the fork 104 is a forward rotation, it can be determined that the next movement of the fork 104 will be a forward rotation, resulting in the lowest motion cost and highest efficiency. Therefore, the processor 1021 controls the next movement iteration of the fork 104 to be a forward rotation. In other words, the motion cost is minimized when the next movement pattern of the fork 104 is the same as the current movement pattern.

[0065] In some embodiments, the movement mode with the lowest motion cost for the fork 104 may be: negative rotation. In other embodiments, the movement mode with the lowest motion cost may be: positive lateral movement. In still other embodiments, the movement mode with the lowest motion cost may be: negative lateral movement. Based on the current movement of the fork 104 (whether it is rotation or lateral movement, positive or negative), the weighting coefficients of the motion cost values ​​in Table 1 are substituted, and the next movement mode with the lowest motion cost for the fork 104 is determined using the above-mentioned motion cost value calculation formula. The processor 1021 controls the fork 104 to execute the movement mode with the lowest motion cost.

[0066] In other embodiments, since the forks 104 have reached the boundary conditions, if the next step still selects the movement mode with the lowest motion cost (i.e., the same movement mode as the previous step), a collision between the forks and the goods or aisle boundary may occur. In this case, the processor 1021 will exclude the movement mode with the lowest motion cost and further consider the movement mode with the second lowest motion cost. If the processor 1021 further determines that the movement mode with the second lowest motion cost may still cause the forks 104 to collide with the goods or aisle, the processor 1021 will further exclude the movement mode with the second lowest motion cost... and so on.

[0067] In other embodiments, similar to the former, although the fork 104 has not reached the boundary condition, if the lateral axis of the fork 104 has moved to its limit position, or the rotation axis of the fork 104 has rotated to its limit angle, it means that the fork 104 cannot continue to execute the same motion mode as the current step. In this case, the processor 1021 will exclude the motion mode with the lowest motion cost and further consider the motion mode with the second lowest motion cost. If the processor 1021 further determines that the motion mode with the second lowest motion cost still belongs to the limit lateral position or limit rotation angle of the fork 104, then the processor 1021 will further exclude the motion mode with the second lowest motion cost... and so on.

[0068] The motion cost weighting coefficients in Table 1 of this application only show preferred weight values ​​and do not represent the exclusion of other weight values ​​or other weighting coefficients.

[0069] Step 204: Processor 1021 calls preset algorithm E3 to determine the next iteration amount of fork 104. Specifically, processor 1021 determines the next angle iteration value of rotation axis 301 according to algorithm E3. and / or the next displacement iteration value of the transverse axis And control the forks 104 to rotate around the rotation axis 301 to Angle and / or control fork 104 to move laterally along transverse axis 302 to At the coordinates.

[0070] Step 205: Processor 1021 calls preset algorithm E4 to calculate whether the unmanned forklift 100 meets the collision boundary conditions. If the collision boundary conditions are met, the unmanned forklift 100 may collide with the aisle, and therefore cannot continue moving in the same direction. At this time, it is necessary to switch the movement mode of the forks 104 and return to step 203 for the next iteration, such as... Figure 2 As shown. In some embodiments, the forks 104 may switch from rotational motion about the rotation axis 301 to lateral motion along the lateral axis 302. In other embodiments, the forks 104 may switch from lateral motion along the lateral axis 302 to rotational motion about the rotation axis 301.

[0071] Wmax<m / 2&Wmin> -m / 2 E4 In this application, to ensure that the unmanned forklift 100 does not collide with the aisle boundary, the maximum value Wmax of the unmanned forklift 100's projection on the x-axis must be less than the coordinate m / 2 of the right boundary of the aisle, and the minimum value Wmin of the unmanned forklift 100's projection on the x-axis must be greater than the coordinate -m / 2 of the left boundary of the aisle. Based on the coordinates of point p and the dimensions of the forks (cargo) of the unmanned forklift, the processor 1021 can calculate the values ​​of Wmax and Wmin and determine whether the unmanned forklift 100 meets the collision boundary conditions.

[0072] If the collision boundary conditions are not met, it means that the unmanned forklift 100 will not collide with the aisle boundary. Then continue to execute step 206 below.

[0073] Step 206: Processor 1021 calls preset algorithm E5 to calculate whether fork 104 has reached the target position. , If not achieved ( , If the iteration has been completed, then return to step 203 for the next iteration. In some embodiments, if the iteration has been completed... However, it was not achieved. Then return to step 203 to proceed. The iteration. In other embodiments, if the goal is not achieved... And has already reached Then return to step 203 to proceed. The iteration. If fork 104 has reached the target position ( , If the iteration stops, then stop.

[0074] According to formula E5, when the lateral displacement p of the fork 104 in the kth iteration... k With the target lateral displacement value p target The difference is less than the iteration step size When p, it can be considered that the fork 104 has reached the target lateral movement position. When the rotation angle θ of the fork 104 in the k-th iteration... k With the target angle value θ target The difference is less than the iteration step size At this point, the forks 104 can be considered to have reached the target rotation position. In some embodiments, a slightly larger [position] can be selected. The lateral displacement of p (e.g., 1.05) p, 1.1 p, 1.2 p, 1.3 p, 1.5 p, etc.) and / or slightly greater than The rotation angle (e.g., 1.05) 1.1 1.2 1.3 1.5 (etc.) can be used as the right-hand side value of inequalities in E5, thus allowing for faster iteration.

[0075] Figure 4 It shows according to Figure 2 The diagram illustrates the rotation angle and lateral displacement of the rotating shaft of the fork 104. According to... Figure 4 The fork 104 operates in a single-path motion mode. The fork 104 starts in the middle of the aisle, and the initial angle of the rotation axis 301 is 90° (the rotation angle of the fork 104 around the rotation axis 301 ranges from 0 to 180°). The motion process of the fork 104 is summarized as follows: - The initial movement of the forks 104 is a rotation in the positive direction around the rotation axis 301 (picking up goods on the right). - The fork 104 rotates to about 110°. At this time, the fork 104 meets the collision boundary condition, thus switching the motion mode to lateral movement along the positive direction of the lateral axis 302. When the p-point of the fork 104 moves laterally to approximately -0.75m, the fork 104 again satisfies the collision boundary condition, thereby switching the motion mode back to rotation around the rotation axis 301. - When the fork 104 rotates to approximately 150°, the fork 104 meets the collision boundary condition, thereby switching the motion mode to lateral movement along the positive direction of the lateral axis 302; When the fork 104 moves laterally at point p to approximately -0.83m, the fork 104 reaches point p. target But still not to reach θ target Stop iterating in the lateral direction and return to the previous step to iterate in the rotation direction until the rotation angle of fork 104 reaches θ. target .

[0076] Please continue to refer to the following. Figure 5 , Figure 5 Continued Figure 2 The method flowchart is shown, and the demonstration is presented. Figure 2 The 201b mode. In some embodiments, the fork lateral / rotation method 20 of the unmanned forklift further includes: Step 501: The processor 1021 adopts and Figure 2-3B Similar methods are used to obtain the necessary parameters L / L', W / W', d, m, p0, θ0, and p by calling system preset data, obtaining data from sensor 103, receiving data from the host computer, or calculating by calling preset algorithms. target p target The meanings and ranges of the above parameters and Figure 2-3B It is completely consistent with what is shown.

[0077] Step 502: The processor 1021 determines the direction and pattern of the next movement of the fork 104 based on the cost values ​​as shown in Table 1. In some embodiments, the processor 1021 of the multi-way unmanned forklift can simultaneously control the rotation and lateral movement of the fork 104. Therefore, the processor 1021 calculates the next movement direction and pattern with the minimum cost value based on the previous rotational movement of the fork 104, and the processor 1021 also calculates the next movement direction and pattern with the minimum cost value based on the previous lateral movement of the fork 104.

[0078] Step 503: Processor 1021 calls preset algorithm E3 to determine the next iteration amount of fork 104.

[0079] Step 504: Processor 1021 calls preset algorithm E4 to calculate whether the unmanned forklift 100 meets the collision boundary conditions. If the collision boundary conditions are met, the unmanned forklift 100 may collide with the aisle and therefore cannot continue moving in the same direction. At this time, it is necessary to switch the movement mode of the forks 104 and return to step 203 for the next iteration. In some embodiments, the forks 104 may stop rotating around the rotation axis 301 but continue lateral movement along the transverse axis 302. In other embodiments, the forks 104 may stop lateral movement along the transverse axis 302 but continue rotating around the rotation axis 301.

[0080] If the collision boundary conditions are not met, it means that the unmanned forklift 100 will not collide with the aisle boundary. Then continue to execute step 505 below.

[0081] Step 505: Processor 1021 calls preset algorithm E5 to calculate whether fork 104 has reached the target position. , In some embodiments, the description of step 505 can be referred to the embodiment of step 206 above, and specific details are omitted here to save space.

[0082] Figure 6 It shows according to Figure 5 The diagram illustrates the rotation angle and lateral displacement of the rotating shaft of the fork 104. According to... Figure 6 The fork 104 operates in a multi-path motion mode. The fork 104 starts in the middle of the aisle, and the initial angle of the rotation axis 301 is 90° (the rotation angle of the fork 104 around the rotation axis 301 ranges from 0 to 180°). The motion process of the fork 104 is summarized as follows: - The initial movement of the forks 104 is a simultaneous rotation around the rotation axis 301 in the positive direction and a lateral movement along the lateral axis 302 (picking up goods on the right). - When the fork 104 rotates to about 120° and the fork point p moves laterally to about 0.3m, the fork 104 meets the collision boundary condition, thus switching the motion mode to lateral movement only along the positive direction of the lateral axis 302. When the p-point of the fork 104 moves laterally to approximately -0.5m, the fork 104 no longer meets the collision boundary conditions, thus switching the motion mode back to simultaneously rotating around the positive direction of the rotation axis 301 and moving laterally along the lateral axis 302. - When fork 104 rotates to approximately 155° and point p of the fork has moved laterally to approximately -0.83m, fork 104 reaches point p. target But still not to reach θ target Stop iterating in the lateral direction and return to the previous step to iterate in the rotation direction until the rotation angle of fork 104 reaches θ. target .

[0083] In one embodiment, after the forks 104 of the unmanned forklift complete the lateral movement / rotation described above and face the goods or shelves, the sensor 103 (e.g., a laser sensor or a vision sensor) further determines whether the height of the forks 104 is consistent with that of the shelves or goods. If the sensor 103 detects that the height of the forks 104 is inconsistent with that of the goods or shelves, the processor 1021 further controls the forks 104 to rise or fall by a certain height, so that the height of the forks 104 is consistent with that of the goods or shelves, thereby safely picking up goods from the shelves or unloading goods onto the shelves.

[0084] As used herein, the terms “approximately,” “substantially,” “essentially,” and “about” are used to describe and account for small variations. When used in conjunction with an event or situation, the terms may refer to examples where the event or situation occurs precisely or very approximately. As used herein with respect to a given value or range, the term “about” generally means within ±10%, ±5%, ±1%, or ±0.5% of the given value or range. A range may be expressed herein as from one endpoint to another or between two endpoints. Unless otherwise specified, all ranges disclosed herein include endpoints. The term “substantially coplanar” may refer to two surfaces located along the same plane within a few micrometers (µm), for example, within 10µm, 5µm, 1µm, or 0.5µm along the same plane. When referring to “substantially” identical numerical values ​​or characteristics, the term may refer to values ​​within ±10%, ±5%, ±1%, or ±0.5% of the average of said values.

[0085] As used herein, unless the context clearly indicates otherwise, the singular terms “a / an” and “the” may include plural indicators. In the description of some embodiments, a component provided “on” or “above” another component may cover the case where the preceding component is directly on the following component (e.g., in physical contact with the following component), and the case where one or more intermediate components are located between the preceding and following components.

[0086] The foregoing outlines several embodiments and detailed features of this disclosure. The embodiments described in this disclosure can readily serve as the basis for designing or modifying other processes and structures for performing the same or similar purposes and / or obtaining the same or similar advantages of the embodiments introduced herein. These equivalent constructions do not depart from the spirit and scope of this disclosure and various changes, substitutions, and modifications can be made without departing from the spirit and scope of this disclosure.

Claims

1. An unmanned forklift (100), characterized in that, The unmanned forklift (100) includes forks (104) and a controller (102) configured to perform the following steps: Receive the lateral step length, rotation step length, and target direction of the forks (104); The forks (104) are controlled to perform lateral movement according to the lateral step size and the target direction; and The forks (104) are controlled to perform rotational motion according to the rotational step and the target direction.

2. The unmanned forklift (100) according to claim 1, characterized in that, The lateral movement is performed before the rotational movement.

3. The unmanned forklift (100) according to claim 1, characterized in that, The rotational motion is performed before the lateral motion.

4. The unmanned forklift (100) according to claim 1, characterized in that, The lateral movement and the rotational movement are performed simultaneously.

5. The unmanned forklift (100) according to claim 1, characterized in that, The steps further include: The target lateral movement position of the forks (104) is determined based on the size of the vehicle (100) and the size of the cargo carried by the vehicle (100); Receive the lateral position of the forks (104); and If the difference between the lateral position and the target lateral position is greater than or equal to the lateral step size, the fork (104) performs the lateral movement.

6. The unmanned forklift (100) according to claim 5, characterized in that, The steps further include: If the difference between the lateral position and the target lateral position is less than the lateral step, the fork (104) performs the rotational motion.

7. The unmanned forklift (100) according to claim 5, characterized in that, The steps further include: The target rotation position of the forks (104) is determined based on the size of the vehicle (100) and the size of the cargo carried by the vehicle (100); Receive the rotational position of the forks (104); and If the difference between the rotation position and the target rotation position is greater than or equal to the rotation step, the fork (104) performs the rotation movement.

8. The unmanned forklift (100) according to claim 7, characterized in that, The steps further include: If the difference between the rotation position and the target rotation position is less than the rotation step, the fork (104) performs the lateral movement.

9. The unmanned forklift (100) according to claim 7, characterized in that, The steps further include: The projection of the fork (104) onto the cross section of the passage traveled by the vehicle (100) is determined based on the lateral position and the rotational position. If the projection of the fork (104) does not fall within the width range of the channel, then control the fork (104) to stop the currently performing rotational motion or lateral motion.

10. The unmanned forklift (100) according to claim 9, characterized in that, The steps further include: If the projection of the fork (104) does not fall within the width range of the channel, then the fork (104) is further controlled to switch between the rotational motion and the lateral motion.

11. The unmanned forklift (100) according to claim 1, characterized in that, The steps further include: Determine the motion pattern of the current step of the fork (104); Determine one or more possible motion patterns for the next movement of the forks (104); Determine the first coefficient for each of the one or more possible motion patterns; The motion cost of each of the one or more possible motion patterns is determined based on the first coefficient; and Control the forks (104) to execute the motion mode with the minimum motion cost.

12. The unmanned forklift (100) according to claim 11, characterized in that, The steps further include: Determine a second coefficient for each of the one or more possible motion patterns; The motion cost of each of the one or more possible motion patterns is determined based on the first coefficient and the second coefficient; and Control the forks (104) to execute the motion mode with the minimum motion cost.

13. The unmanned forklift (100) according to claim 12, characterized in that, The steps further include: Determine the third coefficient for each of the one or more possible motion patterns; The motion cost of each of the one or more possible motion patterns is determined based on the first coefficient, the second coefficient, and the third coefficient; and Control the forks (104) to execute the motion mode with the minimum motion cost.

14. The unmanned forklift (100) according to claim 13, characterized in that, When the second coefficient of one of the one or more possible motion patterns is greater than 1, the third coefficient of that one is set to 1.

15. The unmanned forklift (100) according to claim 11, characterized in that, The current step motion includes: the lateral movement and / or rotational movement of the forks (104).

16. The unmanned forklift (100) according to claim 15, characterized in that, The one or more possible motion modes include one or more of the following: positive lateral movement, negative lateral movement, positive rotational movement, and negative rotational movement.

17. The unmanned forklift (100) according to claim 16, characterized in that, The steps further include: If one or more of the possible motion patterns have reached their limit, then the motion pattern with the lowest motion cost among the remaining one or more possible motion patterns is determined based on the first coefficient, the second coefficient, and the third coefficient; and Control the forks (104) to execute the motion mode with the minimum motion cost.

18. The unmanned forklift (100) according to claim 16, characterized in that, The steps further include: The initial movement of the forks (104) of the vehicle (100) is determined to be a lateral movement or a rotational movement based on the lateral step length, the rotational step length, the target lateral position, and the target rotational position.

19. A method for controlling the forks of an unmanned forklift (100), characterized in that, The fork control method of the unmanned forklift (100) includes the step of controlling the forks (104) of the unmanned forklift (100) according to claim 1 to perform lateral movement and / or rotational movement.

20. A controller, characterized in that, The controller is used to execute program instructions, including controlling the forks (104) of the unmanned forklift (100) according to claim 1 to perform lateral and / or rotational movements.

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