Robot control method, device and equipment and storage medium

Abstract

The embodiment of the invention provides a robot control method and device, equipment and a storage medium. The method comprises the steps of determining a movement control parameter of the robot from a current actual position to a current expected position based on path information contained in a task to be completed, determining a parameter control strategy of the robot based on a scene type corresponding to the task to be completed, and controlling the robot to move according to the parameter control strategy and the movement control parameter. And controlling the moving state of the robot. According to the technical scheme, the problem that collision cannot be avoided in the action of the robot in the prior art is solved, the accuracy and reliability of robot state control are guaranteed, and therefore the completion rate of corresponding tasks of the robot is increased, and the problems of collision and motor overcurrent are remarkably reduced.

Description

Technical Field

[0001] The present disclosure relates to the field of robot control technology, and in particular to a robot control method, device, equipment and storage medium. Background Art

[0002] In the fields of warehousing, logistics, factory production, etc., there are scenarios where robots are required to move materials between equipment such as shelves, workstations, and production lines. Especially in factories, due to the large number of equipment, higher safety requirements are required. It is necessary to ensure the accuracy of the robot's movement to ensure the accurate handover of materials so that production can proceed safely. Maintenance will be carried out by laying out peripheral mechanisms such as guide rails to limit the robot's movement trajectory.

[0003] In related technologies, the control optimization of robot actions is mainly achieved by optimizing the robot's motion control algorithm. However, conventional control algorithms find it difficult to strike a balance between the robot's movement efficiency and control accuracy, which leads to unavoidable problems such as collisions and motor overcurrent during robot actions. Summary of the invention

[0004] The embodiments of the present disclosure provide a robot control method, device, equipment and storage medium to solve the problem in the related art that the robot cannot avoid collision during movement.

[0005] In a first aspect, an embodiment of the present disclosure provides a robot control method, the robot control method comprising:

[0006] Based on the path information contained in the task to be completed, determine the movement control parameters of the robot from the current actual position to the current expected position;

[0007] Determine the robot's parameter control strategy based on the scenario type corresponding to the task to be completed;

[0008] Based on the parameter control strategy and movement control parameters, the movement state of the robot is controlled.

[0009] Optionally, based on the path information contained in the task to be completed, the movement control parameters of the robot from the current actual position to the current expected position are determined, including: based on the path information contained in the task to be completed, determining the position deviation parameter between the current actual position and the current expected position of the robot; based on the position deviation parameter, determining the movement control parameter.

[0010] Optionally, the position deviation parameters include forward position difference, lateral deviation and angular deviation; the movement control parameters include forward movement speed and rotation parameters, and the rotation parameters include lateral deviation control angular velocity generated based on lateral deviation and angular deviation control angular velocity generated based on angular deviation.

[0011] Optionally, based on the position deviation parameter, the movement control parameter is determined, including: based on the forward position difference, determining the forward movement speed; based on the lateral deviation, determining the lateral deviation control angular velocity; based on the angle deviation, determining the angle deviation control angular velocity.

[0012] Optionally, the scenario types of the task to be completed include at least three types, and the parameter control strategy of the robot is determined based on the scenario types corresponding to the task to be completed, including: if the task to be completed corresponds to the first type of scenario, the parameter control strategy is determined to abandon lateral deviation control; if the task to be completed corresponds to the second type of scenario, the parameter control strategy is determined to abandon angle deviation control; if the task to be completed corresponds to the third type of scenario, the parameter control strategy is determined to abandon angle deviation control and lateral deviation control.

[0013] Optionally, the robot includes a picking mechanism, a backpack and / or a charging mechanism, and the first category of scenarios includes: the robot's picking mechanism is performing the action of taking out a pallet or putting back a pallet, and the picking mechanism is located under the pallet; or, the robot's backpack is in a docking position for receiving a material box; or, the robot's charging mechanism is docked with a charging device; or, the robot's current actual position is on a main road and the lateral deviation is less than a set lateral difference; or, the extension direction of the robot's backpack is perpendicular to the moving direction of the material box to be received.

[0014] Optionally, the robot includes a picking mechanism, and the second type of scenarios includes: the robot's picking mechanism is performing the action of taking out a pallet or putting back a pallet, and the horizontal distance between the picking mechanism and the pallet is greater than a first set distance value; or, the difference between the current actual position and the current expected position is greater than the set position difference.

[0015] Optionally, the robot includes a picking mechanism, a backpack and / or a charging mechanism. The third category of scenarios includes: a scenario in which the robot is located on a guide rail or track; a scenario in which the robot's picking mechanism is taking out or putting back a pallet, the picking mechanism is located under the pallet, and the pallet contains a through hole whose size matches the picking mechanism.

[0016] Optionally, the movement state of the robot is controlled based on the parameter control strategy and the movement control parameters, including: based on the parameter control strategy, the movement control parameters are subjected to dimensionality reduction processing to obtain the target control parameters after dimensionality reduction processing; based on the target parameters, the indication information of the corresponding drive motor of the robot is determined; the indication information is sent to the drive motor, and the drive motor is used to control the movement state of the robot based on the indication information.

[0017] Optionally, based on the parameter control strategy, the mobile control parameters are subjected to dimensionality reduction processing to obtain target control parameters after dimensionality reduction processing, including: setting the values ​​of the mobile control parameters abandoned in the parameter control strategy to zero, and determining the obtained mobile control parameters as the target control parameters.

[0018] In a second aspect, an embodiment of the present disclosure provides a robot control device, the robot control device comprising:

[0019] A judgment module, used to determine the movement control parameters of the robot from the current actual position to the current expected position based on the path information included in the task to be completed;

[0020] A determination module, used to determine a parameter control strategy of the robot based on the scenario type corresponding to the task to be completed;

[0021] A control module is used to control the movement state of the robot based on a parameter control strategy and the movement control parameters.

[0022] Optionally, the judgment module is specifically used to determine, based on the path information included in the task to be completed, a position deviation parameter between the current actual position and the current expected position of the robot; and determine the movement control parameter based on the position deviation parameter.

[0023] Optionally, the judgment module specifically includes: the position deviation parameters include forward position difference, lateral deviation and angle deviation; the movement control parameters include forward movement speed and rotation parameters, and the rotation parameters include lateral deviation control angular velocity generated based on lateral deviation and angle deviation control angular velocity generated based on angle deviation.

[0024] Optionally, the judgment module is specifically used to determine the forward moving speed based on the forward position difference; determine the lateral deviation control angular velocity based on the lateral deviation; and determine the angular deviation control angular velocity based on the angular deviation.

[0025] Optionally, the determination module is specifically used to, if the scenario types of the task to be completed include at least three types, if the task to be completed corresponds to the first type of scenario, determine the parameter control strategy to abandon lateral deviation control; if the task to be completed corresponds to the second type of scenario, determine the parameter control strategy to abandon angle deviation control; if the task to be completed corresponds to the third type of scenario, determine the parameter control strategy to abandon angle deviation control and lateral deviation control.

[0026] Optionally, the determination module specifically includes, if the robot includes a picking mechanism, a backpack and / or a charging mechanism, the first type of scenario includes: a scenario in which the robot's picking mechanism is performing the action of taking out a pallet or putting back a pallet, and the picking mechanism is located under the pallet; or a scenario in which the robot's backpack is in a docking position for receiving a material box; or a scenario in which the robot's charging mechanism is docked with a charging device; or a scenario in which the robot's current actual position is on a main road and the lateral deviation is less than a set lateral difference; or a scenario in which the extension direction of the robot's backpack is perpendicular to the moving direction of the material box to be received.

[0027] Optionally, the determination module specifically includes, if the robot includes a picking mechanism, the second type of scenario includes: the robot's picking mechanism is performing the action of taking out a pallet or putting back a pallet, and the horizontal distance between the picking mechanism and the pallet is greater than a first set distance value; or, the difference between the current actual position and the current expected position is greater than the set position difference.

[0028] Optionally, the determination module specifically includes, if the robot includes a picking mechanism, a backpack and / or a charging mechanism, the third category of scenarios includes: a scenario in which the robot is located on a guide rail or track; a scenario in which the robot's picking mechanism is performing an action of taking out a pallet or putting back a pallet, the picking mechanism is located under the pallet, and the pallet contains a through hole whose size matches the picking mechanism.

[0029] Optionally, the control module is specifically used to perform dimensionality reduction processing on the mobile control parameters based on the parameter control strategy to obtain the target control parameters after dimensionality reduction processing; based on the target parameters, determine the instruction information of the robot corresponding to the drive motor; send the instruction information to the drive motor, and the drive motor is used to control the movement state of the robot based on the instruction information.

[0030] Optionally, the control module is specifically configured to set the value of the mobile control parameter abandoned in the parameter control strategy to zero, and determine the obtained mobile control parameter as the target control parameter.

[0031] In a third aspect, an embodiment of the present disclosure further provides a control device, the control device comprising:

[0032] at least one processor;

[0033] and a memory communicatively coupled to the at least one processor;

[0034] The memory stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor to enable the control device to perform the robot control method as described in the first aspect of the present disclosure.

[0035] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, in which computer execution instructions are stored. When the computer execution instructions are executed by a processor, they are used to implement the robot control method as in the first aspect of the present disclosure.

[0036] In a fifth aspect, an embodiment of the present disclosure further provides a computer program product, which includes computer execution instructions, and when the computer execution instructions are executed by a processor, they are used to implement the robot control method as in the first aspect of the present disclosure.

[0037] The robot control method, device, equipment and storage medium provided by the embodiments of the present disclosure determine the movement control parameters of the robot from the current actual position to the current expected position based on the path information contained in the task to be completed, and then determine the parameter control strategy of the robot based on the scene type corresponding to the task to be completed, and finally control the movement state of the robot based on the parameter control strategy and the movement control parameters. In this way, the robot can adjust the control strategy of its movement-related parameters in different business scenarios of path tracking control, ensure the accuracy and reliability of the robot state control, thereby improving the completion rate of the robot's corresponding tasks and significantly reducing the occurrence of collisions and motor overcurrent problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0039] Figure 1 An application scenario diagram of the robot control method provided by the embodiment of the present disclosure;

[0040] Figure 2 A flowchart of a robot control method provided by an embodiment of the present disclosure;

[0041] Figure 3a A flowchart of a robot control method provided by yet another embodiment of the present disclosure;

[0042] Figure 3b for Figure 3a A schematic diagram of the relationship between the relevant parameters of the robot position deviation provided in the illustrated embodiment;

[0043] Figure 3c for Figure 3a A schematic diagram of deviation control in the first case provided in the illustrated embodiment;

[0044] Figure 3d for Figure 3a A schematic diagram of deviation control in the second case provided in the illustrated embodiment;

[0045] Figure 3e for Figure 3a A schematic diagram of deviation control in a third case provided in the illustrated embodiment;

[0046] Figure 3f for Figure 3a A schematic diagram of deviation control in a fourth case provided in the illustrated embodiment;

[0047] Figure 3g for Figure 3a A schematic diagram of the process of a forklift taking away a pallet provided in the illustrated embodiment;

[0048] Figure 3h for Figure 3a A schematic diagram of the process of lowering a pallet by a forklift provided in the illustrated embodiment;

[0049] Figure 3j for Figure 3a A schematic diagram of the process of docking the robot and the guide rail provided in the illustrated embodiment;

[0050] Figure 4 A schematic diagram of the structure of a robot control device provided by yet another embodiment of the present disclosure;

[0051] Figure 5 A schematic diagram of the structure of a control device provided in one embodiment of the present disclosure.

[0052] The above drawings show clear embodiments of the present disclosure, which will be described in more detail below. These drawings and text descriptions are not intended to limit the scope of the present disclosure in any way, but to illustrate the concepts of the present disclosure to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0053] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0054] The technical solution of the present invention and how the technical solution of the present invention solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0055] In the fields of warehousing, logistics, and factory production, there are scenarios where robots are required to move materials between equipment such as shelves, workstations, and production lines. Especially in factories, due to the large number of equipment, high safety requirements are required. It is necessary to ensure the accuracy of robot movement to ensure accurate material transfer and safe production. The robot's trajectory is limited by laying out external mechanisms such as guide rails. In addition, different stages of the task have different movement requirements for robots. For example, when operating on a wide main road, the robot is expected to ensure efficiency and smoothness and appropriately give up control accuracy; when operating near dense storage locations or machines, the robot is expected to prioritize control accuracy, especially angle accuracy, to prevent collisions. For example, when a forklift is unloading a pallet after putting the goods, it is expected that the forklift will prioritize angle accuracy to prevent collisions with the inner wall of the pallet due to rotation.

[0056] In the related art, the control optimization of robot action is mainly achieved by optimizing the robot's motion control algorithm, but it is difficult for conventional control algorithms to ensure a balance between the robot's movement efficiency and control accuracy, especially for non-complete constraint robots (that is, robots whose movement mode consists of forward and turning, such as forklift robots used to carry material boxes). To eliminate lateral position deviations, it is necessary to rotate the direction, and the rotation direction may increase the angle deviation. Therefore, simply adjusting the control parameters cannot simultaneously ensure the high accuracy of lateral position deviation and angle deviation. At the same time, due to position deviations, objects may block the robot's movement trajectory, which in turn causes the robot's movement speed to fail to reach the expected speed, causing the robot's drive motor to continuously increase the current (in an attempt to speed up), resulting in excessive current and burning of the motor or driver, that is, the motor overcurrent problem. In summary, conventional control algorithms cannot avoid the occurrence of problems such as collisions and motor overcurrent during robot action.

[0057] In order to solve this problem, the embodiment of the present disclosure provides a robot control method, which determines the parameter control strategy for the robot deviation according to the type of scene the robot is in, and generates corresponding instructions accordingly to control the movement of the robot to ensure the accuracy of the robot during movement and minimize the occurrence of problems such as collision and motor overcurrent.

[0058] The application scenarios of the embodiments of the present disclosure are explained below:

[0059] Figure 1 This is an application scenario diagram of the robot control method provided by the embodiment of the present disclosure. Figure 1 As shown, in the intelligent warehousing system, the robot 100 will transport goods 121 between the conveyor line 110 and the shelf 120 according to the received task, and based on the path information in the received task to be completed, the control algorithm is used to ensure the accuracy and safety of the driving, so as to effectively complete the cargo handling task.

[0060] It should be noted that Figure 1 In the scenario shown, only one robot, conveyor line, shelf, and cargo is used as an example for illustration, but the present disclosure is not limited to this, that is, the number of robots, conveyor lines, shelves, and cargo can be arbitrary.

[0061] The robot control method provided by the present disclosure is described in detail below through specific embodiments.

[0062] Figure 2 Flow chart of a robot control method provided by one embodiment of the present disclosure. Figure 2 As shown, the robot control method provided in this embodiment includes the following steps:

[0063] Step S201, based on the path information included in the task to be completed, determine the movement control parameters of the robot from the current actual position to the current expected position.

[0064] Specifically, the robot is a mobile robot that needs to move in environments such as factories and warehouses to complete various tasks, including a forklift robot with a forklift structure, a transport robot with multiple backpacks, etc.

[0065] The task to be completed is usually to move the robot to a specified starting position to receive a material box (or other items to be transported), and then move to a specified end position according to the determined path information and place the material box. Therefore, the task to be completed will include the path information, the starting position and the end position of the robot (the starting position and the end position may also be included in the path information).

[0066] After receiving the task to be completed, the robot will move based on the starting position, path information and end position in the task to be completed, and will determine the current actual position in real time, and compare it with the current expected position determined based on the path information (such as the position point contained in the path information and the current actual position, or if the path information also includes the time requirement for reaching each position point, the current expected position can also be the position point corresponding to the current time point).

[0067] The movement of the robot is usually achieved by moving the robot chassis in a two-dimensional plane (i.e., the area where the robot moves is a two-dimensional plane by default), and its control dimensions include the two-dimensional position (x, y) and the angle θ. The deviation between the current actual position P of the robot and the current expected position in the path information is calculated as the current control deviation ΔP. On this basis, based on the control deviation ΔP, the movement mode that the robot needs to perform can be analyzed, including the movement speed, steering angle, etc., which are the movement control parameters of the robot. Through the movement control parameters, the robot can be driven to move from the current actual position to the current expected position.

[0068] Step S202, determining the parameter control strategy of the robot based on the scenario type corresponding to the task to be completed.

[0069] Specifically, since driving the robot to move directly according to the mobile control parameters is prone to problems such as collision and motor overcurrent, it is necessary to determine the processing strategy for the mobile control parameters (i.e., parameter control strategy) in combination with the scenario type of the task to be completed, such as abandoning the control of some parameters (for example, when the robot moves onto the guide rail, the control of the robot's angle and lateral deviation can be abandoned, and it can move directly based on the forward deviation, because the guide rail will limit the lateral movement of the robot and will not allow the lateral deviation to increase further).

[0070] Each task to be completed can correspond to multiple scene types, such as receiving boxes at the unloader, moving on the main road, and placing boxes on the shelf. Usually, the parameter control strategies under different scenes are different, so it is necessary to predetermine the parameter control strategies corresponding to each scene type. When the robot determines the scene type it is in through the task to be completed and the environment recognition, it can execute the corresponding parameter control strategy.

[0071] Step S203, controlling the movement state of the robot based on the parameter control strategy and the movement control parameters.

[0072] Specifically, by executing the parameter control strategy, the movement control parameters are processed (usually dimensionality reduction processing to reduce the parameters that need to be considered for the robot to move), and then the working state of the robot's drive motor is determined based on the processed parameters. Through the operation of the drive motor, the robot is controlled to move from the current actual position to the current expected position according to the determined movement state.

[0073] The robot control method provided by the disclosed embodiment determines the movement control parameters of the robot from the current actual position to the current expected position based on the path information contained in the task to be completed, and then determines the parameter control strategy of the robot based on the scene type corresponding to the task to be completed, and finally controls the movement state of the robot based on the parameter control strategy and the movement control parameters. In this way, the robot can adjust the control strategy of its movement-related parameters in different business scenarios of path tracking control, ensure the accuracy and reliability of the robot state control, thereby improving the completion rate of the robot's corresponding tasks and significantly reducing the occurrence of collisions and motor overcurrent problems.

[0074] Figure 3a Flow chart of a robot control method provided by one embodiment of the present disclosure. Figure 3a As shown, the robot control method provided in this embodiment includes the following steps:

[0075] Step S301, based on the path information included in the task to be completed, determine the position deviation parameter between the current actual position and the current expected position of the robot.

[0076] Specifically, the position deviation parameters include forward position difference, lateral deviation and angle deviation.

[0077] After receiving a task to be completed, the robot will determine its current actual position in real time, and based on the path information (the expected path contained therein), find the point on the expected path closest to the robot's current actual position as the reference point (that is, the current expected position).

[0078] Then, take this point as the origin of the reference coordinate system, and the forward direction of the path tangent as the positive direction of the x-axis to establish a reference coordinate system. Then, define the horizontal axis coordinate value of the robot's current actual position expressed in the reference coordinate system as the lateral deviation Δy, and the angle as the angular deviation Δθ. The forward position difference Δx is the distance from the current expected position to the end point of the expected path.

[0079] Therefore, the goal of controlling the robot's moving state is to control the position deviation parameter ΔP = (Δx, Δy, Δθ) to 0, that is, to control the robot to move strictly along the desired path to the end of the path.

[0080] like Figure 3b As shown in the figure, it is a schematic diagram of the relationship between the relevant parameters of the robot position deviation. Among them, point O is the center of the robot, the hollow arrow is the forward movement direction of the robot, O1 is the fulcrum on the nearest expected path (starting position A, end position B), forward X, lateral Y, and angle θ are the three dimensions representing the robot's posture, and Δx, Δy, and Δθ are the three position deviation parameters.

[0081] Step S302: determining movement control parameters based on the position deviation parameters.

[0082] Specifically, in order to control the position deviation parameter to 0, it is necessary to control the movement state of the robot. The control of the robot movement involves movement control parameters, which include forward movement speed and rotation parameters. The rotation parameters include lateral deviation control angular velocity based on lateral deviation and angular deviation control angular velocity based on angular deviation. These movement control parameters are described in detail below.

[0083] When the robot is moving, its position includes three dimensions: forward x, lateral y and angle θ. That is, the robot's motion control can be decoupled into forward moving speed and rotation parameters, where the forward moving speed corresponds to the desired speed v. sp , the corresponding position deviation parameter is Δx; the corresponding control quantity of the rotation parameter is the desired angular velocity ω sp, the corresponding position deviation parameters are Δy and Δθ. The movement control amount v is obtained by controlling the forward position difference Δx sp , thereby controlling the robot to move to the end of the path; by controlling the lateral deviation Δy and the angular deviation Δθ, the rotation control amount ω is obtained sp , thereby controlling the robot to be on the desired path, and the angle is consistent with the direction of the desired path.

[0084] Among them, the forward moving speed can be determined based on the forward position difference; the lateral deviation control angular velocity can be determined based on the lateral deviation; and the angular deviation control angular velocity can be determined based on the angular deviation.

[0085] It can be specifically expressed as:

[0086] Forward moving speed: v sp = CTR(Δx);

[0087] Rotation parameters:

[0088] Where CTR(·) represents the robot’s built-in controller algorithm function, including but not limited to PID controller. sp_Δy is the rotation control amount generated based on the lateral deviation, that is, the lateral deviation control angular velocity; ω sp_Δθ is the rotation control quantity generated based on the angle deviation, that is, the angle deviation controls the angular velocity. Define ω sp Counterclockwise rotation is positive and clockwise rotation is negative.

[0089] The forward position difference can be controlled by controller algorithm function or speed planning. If the forward movement control is abandoned, the robot can only rotate in place (only the rotation control amount ω remains sp ), it is impossible to reach the end point, so the forward movement control cannot be abandoned. Therefore, in practical applications, the control of the lateral deviation Δy and the angle deviation Δθ is mainly abandoned (i.e., different parameter control strategies), thereby reducing the control dimension.

[0090] For example, Figure 3c As shown, it is a schematic diagram of deviation control in the first case. Figure 3c In the figure, Δy>0 (Δy is the distance from O to O1 in the figure), that is, the robot is on the left side of the path (looking along the path direction, that is, the direction indicated by the vertical solid arrow in the figure), then the control amount generated by the lateral deviation is ω sp_Δy <0, that is, in order to eliminate Δy, the robot is expected to rotate clockwise. At the same time, Δθ>0, that is, in order to keep the robot's driving direction straight, the robot needs to rotate clockwise, that is, ω sp_Δθ <0, therefore, we can directly control the robot to rotate clockwise and move in the direction to eliminate Δy.

[0091] Another example Figure 3d As shown in Figure 2, it is a schematic diagram of the deviation control in the second case. Figure 3d In the case of Δy>0, Δθ<0, since ω sp_Δy <0, then the robot needs to be controlled to rotate clockwise. At the same time, the control amount ω generated by the angle deviation sp_Δθ >0, that is, in order to make the robot direction consistent with the path direction, the robot is expected to rotate counterclockwise. Therefore, the actual rotation direction is based on ω sp_Δy and ω sp_Δθ The size of is relatively certain, if |ω sp_Δy |>|ω sp_Δθ |, you need to rotate clockwise, otherwise, you need to rotate counterclockwise.

[0092] For example Figure 3e As shown in Figure 2, it is a schematic diagram of deviation control in the third case. Figure 3e In the case of Δy<0, Δθ<0, Figure 3d The situation is similar to that in , while rotating clockwise, that is, ω sp_Δy >0, the car needs to rotate counterclockwise, and ω sp_Δθ <0, the car needs to rotate clockwise, so it is also necessary to determine the direction of rotation by comparing the two values.

[0093] For example Figure 3f As shown, it is a schematic diagram of deviation control in the fourth case. Figure 3f In the equation, Δy<0, Δθ>0, that is, ω sp_Δy >0 and ω sp_Δθ >0, therefore, counterclockwise rotation is required to ensure vehicle control.

[0094] In summary, during the path tracking process, the robot may encounter various situations. Therefore, it is necessary to select the corresponding parameter control strategy according to the type of scene.

[0095] Step S303: If the task to be completed corresponds to the first type of scenario, the parameter control strategy is determined to abandon the lateral deviation control.

[0096] Specifically, the classification of scenes can be determined based on the task to be completed, the perception of the surrounding or specified equipment, the robot's own positioning, etc. Different parameter control strategies are selected according to different scenes (i.e., determining whether to abandon lateral deviation or angle deviation control, i.e., forcing ω sp_Δy or sp_Δθ Assign 0).

[0097] Among them, the first type of scenario is that it is necessary to give up the control of lateral deviation in order to ensure angle accuracy (that is, the scenario where angle accuracy is obviously more important).

[0098] For example, if the angle deviation is large, collision is prone to occur (if the robot chassis is rectangular, the larger the angle deviation within a certain range, the larger the space occupied by the robot). If the angle deviation is Δθ, the robot or shelf edge at a distance L from the robot center will produce a position deviation of Δθ*L due to the angle deviation, that is, the position deviation caused by the angle deviation will be magnified by the distance L. When L is large (i.e. the size of the robot or the goods is large), the position deviation is more obvious. However, the lateral deviation Δy will not be magnified, that is, the lateral deviation of the robot center is Δy, then the deviation of all points on the entire robot or shelf due to the lateral deviation of the robot center is Δy.

[0099] For example, a large angle deviation (relative to a large lateral deviation) has a greater impact on the operating effect, because a large angle deviation will give people an intuitive feeling of "twisting", affecting the customer experience.

[0100] Furthermore, the first type of scenarios may include:

[0101] Scenario 1: The robot's picking mechanism is taking out or putting back a pallet, and the picking mechanism is located under the pallet.

[0102] Specifically, if the robot is a forklift robot, its picking mechanism includes fork teeth (if it is a handling robot, the corresponding structure is a mechanical arm or a receiving rod, etc., and the forklift robot is used as an example for explanation here). Because the fork teeth are long, when the angle deviation is large, it will cause a large fork tip position deviation. Compared with the lateral deviation, the angle deviation is obviously more likely to cause a collision risk.

[0103] When taking out a pallet, the forklift robot inserts the fork tines into the pallet hole below the pallet and then lifts the fork tines to take out the pallet. Conversely, when putting the pallet back, the forklift lowers the fork tines to the bottom and then moves the pallet out to put the pallet in. Since the space inside the pallet hole is limited, the navigation control accuracy of the forklift is relatively high, especially the angle accuracy. If the forklift has a large angular movement during the process of taking goods into the pallet, it will cause the fork tines to collide with the inside of the pallet hole.

[0104] However, if the pickup mechanism is already under the pallet, that is, the fork is about to enter the pallet or has entered the pallet, it is necessary to ensure that the angle is correct, that is, abandon the lateral deviation control, and control the forklift angle deviation to 0 as soon as possible. After the fork enters the pallet hole, it is hoped that the forklift angle is parallel to the pallet, and the lateral deviation control is completely abandoned, that is, forced ω sp_Δy Assign 0 until the forklift picks up the pallet.

[0105] Therefore, lateral deviation control needs to be abandoned in this scenario.

[0106] Scenario 2: The robot’s backpack is in the docking position for receiving material boxes.

[0107] Specifically, similar to scenario one, angle deviation will cause large position deviation at the corners of the backpack, and the space near the docking position is cramped (usually there is a discharger), so it is easy for the backpack to collide with the discharger. Therefore, compared with lateral deviation, angle accuracy is obviously more important at this time.

[0108] Scenario three: The robot’s charging mechanism is docked with the charging equipment.

[0109] Specifically, the docking of the charging mechanism and the charging device is usually the docking of the charging plug and the charging port. At this time, the angle deviation will cause a large position deviation between the charging port and the charging plug, affecting the success rate of charging docking. Therefore, it is also necessary to give priority to ensuring the angle accuracy.

[0110] Scenario 4: The robot's current actual position is on the main road and the lateral deviation is less than the set lateral difference.

[0111] Specifically, when the robot is driving on the main road, if the lateral deviation is not large (i.e., the lateral deviation is less than the set lateral difference), the angle deviation is obviously more important than the small lateral deviation. Because the main road is wide, a small lateral deviation does not matter, but the robot is expected to go "straight" (i.e., ensure the accuracy of the direction).

[0112] Scene 5: The extension direction of the robot's backpack is perpendicular to the moving direction of the material box to be received.

[0113] Specifically, in addition to the robot backpack directly docking with the unloader, the robot can also face the unloader sideways to achieve sideways pickup. In this case, the backpack of this type of unloader usually includes a receiving mechanism with a telescopic function, and the receiving mechanism has a large margin (and the goods to be received also have a certain size), so lateral deviation does not affect the pickup task. However, if the angle is not correct, it is easy for the robot to collide with the goods or the unloader (because the receiving mechanism may extend a long distance), and the angle accuracy is obviously more important than the lateral deviation.

[0114] The above only lists some common scenarios where lateral deviation needs to be abandoned, but the present solution is not limited by the above list. That is, technical personnel in this field can configure various scenarios as the first category of scenarios where lateral deviation needs to be abandoned according to the needs of actual applications, which are all within the protection scope of this solution.

[0115] Step S304: If the task to be completed corresponds to the second type of scenario, the parameter control strategy is determined to abandon the angle deviation control.

[0116] Specifically, in contrast to the first type of scenario, the second type of scenario is a scenario where angle deviation control needs to be abandoned to ensure lateral position accuracy (or in other words, lateral accuracy is more important in this type of scenario).

[0117] Furthermore, the second category of scenarios includes:

[0118] Scenario 6: The robot's picking mechanism is taking out a pallet or putting back a pallet, and the horizontal distance between the picking mechanism and the pallet is greater than a first set distance value.

[0119] Specifically, in the same task as scenario 1 (but the scenarios are different), if the horizontal distance between the pickup mechanism and the pallet is far (i.e. the horizontal distance is greater than the first set distance value), the front end of the fork tine will not collide with the pallet due to rotation. In order to eliminate the lateral deviation as soon as possible and enable the fork tine to align with the pallet hole, the angle deviation can be abandoned first and the lateral deviation can be converged as soon as possible. Therefore, at this time, the angle deviation control is given priority.

[0120] Scenario 7: The difference between the current actual position and the current expected position is greater than the set position difference.

[0121] Specifically, when the robot deviates far from the expected path (i.e., the lateral deviation is large) and the lateral deviation continues to expand, if it does not return to the expected path as soon as possible, it is likely to cause a collision risk. Therefore, the angle deviation can be abandoned to allow the robot to return to the expected path as soon as possible.

[0122] The above only lists some common scenarios where angle deviation needs to be abandoned, but the present solution is not limited by the above list. That is, technical personnel in this field can configure various scenarios as the second type of scenarios where angle deviation needs to be abandoned according to the needs of actual applications, which are all within the protection scope of this solution.

[0123] Step S305: If the task to be completed corresponds to the third type of scenario, the parameter control strategy is determined to abandon the angle deviation control and the lateral deviation control.

[0124] Specifically, in addition to the first two scenarios, there are also scenarios where both lateral deviation and angular deviation control need to be abandoned. In such scenarios, the robot's expected angular velocity ω sp It must be 0, that is, the robot will not have the expectation of rotation control, and the control of rotation parameters can be abandoned, and only the expectation of movement control parameters exists v sp For example, if the robot's motion mechanism is a differential car, the left and right wheel speeds are expected to be the same. For example, if the forklift robot is an example, the steering wheel angle and chassis angular velocity are expected to be 0. This reduces the robot's motion from two-dimensional planar motion to one-dimensional forward and backward motion. This type of scenario usually occurs when the robot is constrained by an external mechanism to only move forward and backward.

[0125] Furthermore, the third category of scenarios includes:

[0126] Scenario 8: The robot is on a rail or track.

[0127] Specifically, in some warehouses or factories, rails are set up near shelves, unloading equipment or workstations to accurately define the robot's position. In such scenarios, the robot is in a free two-dimensional motion state when it is outside the rails, and it is necessary to control the deviations in three dimensions (i.e., three position deviation parameters) at the same time.

[0128] Once the robot passes through the guide rail opening and enters the guide rail, the guide rail completely restricts the robot's lateral movement. However, due to reasons such as sensor positioning fluctuations, lateral deviation and angular deviation cannot be absolutely zero. At this time, if the rotation parameters are controlled to generate rotation and lateral movement components, the motor will be in a stalled or wheel slipping state due to the guide rail restriction. In severe stalling conditions, there is a risk of motor overcurrent. Therefore, when the robot recognizes that it has entered the guide rail, it needs to give up lateral deviation and angular deviation control at the same time, so that the chassis control amount only exists in v sp , that is, the expected speeds of the left and right wheels are always equal, reducing the robot's two-dimensional planar motion to one-dimensional forward and backward motion.

[0129] In addition, in order to improve efficiency and safety, there is currently a new business model: the robot operates in a normal two-dimensional motion mode on the main road, but a ground track will be laid in the aisle for picking up and placing goods (to limit the movement of the robot and the robot speed can be increased without worry). When picking up and placing goods, the robot will drive into the track, thus changing from two-dimensional plane motion to one-dimensional forward and backward motion. At this time, it is also necessary to give up lateral deviation and angular deviation control at the same time.

[0130] Scenario 9: The robot's picking mechanism is taking out or putting back a pallet. The picking mechanism is located under the pallet, and the pallet contains a through hole with a size that matches the picking mechanism.

[0131] Specifically, in contrast to scenarios one and six, when the picking mechanism is in contact with the pallet hole (that is, the through hole under the pallet), it is equivalent to restricting the lateral movement of the forklift. If the pallet hole is very small (equivalent to the width of the fork tine), the picking mechanism and the robot only need to move forward and backward to drive the pallet to take out and put back. At this time, there is no need to adjust its own lateral deviation and angular deviation, so it is also necessary to give up the lateral deviation and angular deviation control at the same time.

[0132] The above only lists some common scenarios where lateral deviation and angular deviation need to be abandoned at the same time, but the present solution is not limited by the above list. That is, technical personnel in this field can configure various scenarios into the third category of scenarios where lateral deviation and angular deviation need to be abandoned according to the needs of actual applications, which are all within the protection scope of this solution.

[0133] In actual applications, in addition to the above three scenarios, there are also scenarios where the movement control parameters do not need to be abandoned, that is, scenarios where the robot can move normally according to the position deviation parameters, such as scenarios where the robot is driving normally on the main road. In this scenario, the robot is in a normal driving state relative to the path information. Since it does not involve parameter control strategies, it will not be described in detail here.

[0134] For example, Figure 3g and Figure 3h As shown, they are respectively a schematic diagram of the process of forklift taking away the pallet and a schematic diagram of the process of forklift putting down the pallet. Figure 3g In the figure, taking the upper left part as an example, the white figure between points AB corresponds to the forklift robot (referred to as forklift), and the white and gray image between points BC corresponds to the pallet, where the white color represents the pallet hole under the pallet.

[0135] The forklift's path from moving to the vicinity of the pallet to taking the pallet away includes two sections, AB and BC. In the AB section, the distance between the forklift and the pallet needs to be reduced as quickly as possible. Therefore, the angle deviation control can be abandoned (corresponding to the above scenario six). In the BC section, the forklift's fork tine needs to be aligned with the hole under the pallet. Therefore, the lateral deviation control can be abandoned (corresponding to the above scenario one). After the forklift's fork tine enters the hole under the pallet, the forklift only needs to move forward and backward (corresponding to the above scenario nine). When it reaches point C, the fork tine rises and connects with the pallet, which can drive the pallet to move.

[0136] exist Figure 3h In the process of lowering the pallet by the forklift, when the forklift's fork tines are disconnected from the pallet at point C, the only way to do it is to move to point B in the way described in scenario nine, so that the pallet is out of contact with the fork tines. After point B, normal control can be restored, and the forklift can move in the direction of BA and leave the vicinity of the pallet.

[0137] Another example Figure 3j As shown, it is a schematic diagram of the process of docking the robot with the guide rail. The robot on the left carries a shelf (i.e., a rectangular frame containing four gray rectangles in the figure), and drives the shelf to move to the guide rail (i.e., the structure corresponding to the gray strip in the figure) until it docks with the machine (or storage location, i.e., the gray rectangle on the right side of the figure). This process corresponds to scene eight.

[0138] Step S306: Based on the parameter control strategy, the movement control parameters are subjected to dimensionality reduction processing to obtain target control parameters after dimensionality reduction processing.

[0139] Specifically, according to the selected parameter control strategy, the lateral deviation and angle deviation control are judged whether to abandon processing. Since the value of the mobile control parameter abandoned in the parameter control strategy is set to zero at this time, the obtained mobile control parameter is determined as the target control parameter. This process is the process of dimensionality reduction.

[0140] Furthermore, after dimensionality reduction, the comprehensive mobile control parameter v sp ,ω sp_Δy ,ω sp_Δθ The control amount required for the robot to move can be obtained: the expected speed v sp , desired angular velocity ω sp =ω sp_Δy +ω sp_Δθ .

[0141] Step S307: determining instruction information of the robot corresponding to the driving motor based on the target parameters.

[0142] Specifically, by performing kinematic inverse solution on the control amount in the above steps, the desired control amount corresponding to each motor drive (i.e., the desired motor speed) can be obtained. By sending the desired control amount as instruction information to each drive motor, the drive motor can be driven to work according to the set state (i.e., the state corresponding to the desired control amount).

[0143] Step S308, sending the instruction information to the driving motor, and the driving motor is used to control the movement state of the robot based on the instruction information.

[0144] Specifically, the movement state of the robot is controlled by sending instruction information to the drive motor for execution.

[0145] Furthermore, according to the indication information below, the robot will determine whether the task to be completed is completed. If the task to be completed is still in an unfinished state, it will return to step S301 and enter the next cycle.

[0146] The robot control method provided by the disclosed embodiment determines the position deviation parameter between the current actual position and the current expected position of the robot based on the path information contained in the task to be completed, determines the mobile control parameter based on the position deviation parameter, and then determines the corresponding parameter control strategy according to the scene type corresponding to the task to be completed, and then performs dimensionality reduction processing on the mobile control parameter based on the parameter control strategy to obtain the target control parameter after dimensionality reduction processing, and determines the indication information of the corresponding driving motor of the robot based on the target parameter, and finally sends the indication information to the driving motor, and the driving motor is used to control the movement state of the robot based on the indication information. In this way, the robot can choose whether to give up the lateral deviation or angle deviation control according to different business scenarios, and always ensure the safety and reliability of the robot's movement process, thereby improving the task completion rate and reducing the occurrence of collision and motor overcurrent problems.

[0147] Figure 4 This is a schematic diagram of the structure of a robot control device provided by an embodiment of the present disclosure. Figure 4As shown, the robot control device 400 includes: a judgment module 410, a determination module 420 and a control module 430. Among them:

[0148] A judgment module 410 is used to determine the movement control parameters of the robot from the current actual position to the current expected position based on the path information included in the task to be completed;

[0149] A determination module 420, configured to determine a parameter control strategy of the robot based on the type of scenario corresponding to the task to be completed;

[0150] The control module 430 is used to control the movement state of the robot based on the parameter control strategy and the movement control parameters.

[0151] Optionally, the judgment module 410 is specifically used to determine a position deviation parameter between a current actual position and a current expected position of the robot based on the path information included in the task to be completed; and determine a movement control parameter based on the position deviation parameter.

[0152] Optionally, the judgment module 410 specifically includes: the position deviation parameters include forward position difference, lateral deviation and angle deviation; the movement control parameters include forward movement speed and rotation parameters, and the rotation parameter package includes a lateral deviation control angular velocity generated based on the lateral deviation and an angle deviation control angular velocity generated based on the angle deviation.

[0153] Optionally, the judgment module 410 is specifically used to determine the forward moving speed based on the forward position difference; determine the lateral deviation control angular velocity based on the lateral deviation; and determine the angular deviation control angular velocity based on the angular deviation.

[0154] Optionally, the determination module 420 is specifically used to, if the scenario types of the task to be completed include at least three types, if the task to be completed corresponds to the first type of scenario, determine the parameter control strategy to abandon lateral deviation control; if the task to be completed corresponds to the second type of scenario, determine the parameter control strategy to abandon angle deviation control; if the task to be completed corresponds to the third type of scenario, determine the parameter control strategy to abandon angle deviation control and lateral deviation control.

[0155] Optionally, the determination module 420 specifically includes, if the robot includes a picking mechanism, a backpack and / or a charging mechanism, the first type of scenario includes: a scenario in which the robot's picking mechanism is performing the action of taking out a pallet or putting back a pallet, and the picking mechanism is located under the pallet; or a scenario in which the robot's backpack is in a docking position for receiving a material box; or a scenario in which the robot's charging mechanism is docked with a charging device; or a scenario in which the robot's current actual position is on a main road and the lateral deviation is less than a set lateral difference; or a scenario in which the extension direction of the robot's backpack is perpendicular to the moving direction of the material box to be received.

[0156] Optionally, the determination module 420 specifically includes, if the robot includes a picking mechanism, the second type of scenario includes: a scenario in which the robot's picking mechanism is performing an action of taking out a pallet or putting back a pallet, and the horizontal distance between the picking mechanism and the pallet is greater than a first set distance value; or a scenario in which the difference between the current actual position and the current expected position is greater than the set position difference.

[0157] Optionally, the determination module 420 specifically includes, if the robot includes a picking mechanism, a backpack and / or a charging mechanism, the third category of scenarios includes: a scenario in which the robot is located on a guide rail or track; a scenario in which the robot's picking mechanism is performing an action of taking out a pallet or putting back a pallet, the picking mechanism is located under the pallet, and the pallet contains a through hole whose size matches the picking mechanism.

[0158] Optionally, the control module 430 is specifically used to perform dimensionality reduction processing on the mobile control parameters based on the parameter control strategy to obtain the target control parameters after dimensionality reduction processing; based on the target parameters, determine the instruction information of the robot corresponding to the drive motor; send the instruction information to the drive motor, and the drive motor is used to control the movement state of the robot based on the instruction information.

[0159] Optionally, the control module 430 is specifically configured to set the value of the abandoned mobility control parameter in the parameter control strategy to zero, and determine the obtained mobility control parameter as the target control parameter.

[0160] In this embodiment, the robot control device solves the problem in related technologies that robots cannot avoid collisions during action through the combination of various modules, ensures the accuracy and reliability of robot state control, thereby improving the completion rate of corresponding tasks of the robot and significantly reducing the occurrence of collisions and motor overcurrent problems.

[0161] Figure 5 A schematic diagram of the structure of a control device provided by an embodiment of the present disclosure, such as Figure 5 As shown, the control device 500 includes: a memory 510 and a processor 520 .

[0162] The memory 510 stores a computer program that can be executed by at least one processor 520. The computer program is executed by at least one processor 520 to enable the control device to implement the material removal method provided in any of the above embodiments or the robot control method provided in any of the above embodiments.

[0163] The memory 510 and the processor 520 may be connected via a bus 530 .

[0164] The relevant instructions can be understood by referring to the relevant descriptions and effects corresponding to the method embodiments, which will not be repeated here.

[0165] The relevant instructions can be understood by referring to the relevant descriptions and effects corresponding to the method embodiments, which will not be repeated here.

[0166] An embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, and the computer program is executed by a processor to implement the material removal method provided in any of the above method embodiments or the robot control method provided in any of the above embodiments.

[0167] Among them, the computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0168] An embodiment of the present disclosure provides a computer program product, which includes computer-executable instructions. When the computer-executable instructions are executed by a processor, they are used to implement the material removal method in the above method embodiment or the robot control method provided in any of the above embodiments.

[0169] In the several embodiments provided in the present disclosure, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0170] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the disclosure disclosed herein. The present disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0171] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A robot control method, characterized in that: The robot control method comprises: Determining movement control parameters of the robot from a current actual position to a current desired position based on path information included in the task to be completed; Determining a parameter control strategy for the robot based on the scenario type corresponding to the task to be completed; Based on the parameter control strategy and the movement control parameters, the movement state of the robot is controlled.

2. The method according to claim 1, characterized in that The step of determining the movement control parameters of the robot from the current actual position to the current expected position based on the path information included in the task to be completed includes: Determining a position deviation parameter between a current actual position and a current expected position of the robot based on path information included in the task to be completed; Based on the position deviation parameter, the movement control parameter is determined.

3. The method according to claim 2, characterized in that The position deviation parameters include forward position difference, lateral deviation and angular deviation; The movement control parameters include a forward movement speed and a rotation parameter, and the rotation parameter includes a lateral deviation control angular velocity generated based on the lateral deviation and an angular deviation control angular velocity generated based on the angular deviation.

4. The method according to claim 3, characterized in that The determining the movement control parameter based on the position deviation parameter comprises: determining the forward moving speed based on the forward position difference; Based on the lateral deviation, determining the lateral deviation control angular velocity; Based on the angular deviation, the angular deviation control angular velocity is determined.

5. The method according to claim 1, characterized in that The types of scenarios for the tasks to be completed include at least three types: The determining of the parameter control strategy of the robot based on the scenario type corresponding to the task to be completed includes: If the task to be completed corresponds to the first type of scenario, the parameter control strategy is determined to abandon lateral deviation control; If the task to be completed corresponds to the second type of scenario, the parameter control strategy is determined to abandon the angle deviation control; If the task to be completed corresponds to the third type of scenario, the parameter control strategy is determined to abandon the angle deviation control and the lateral deviation control.

6. The method according to claim 5, characterized in that The robot comprises a picking mechanism, a backpack and / or a charging mechanism. The first type of scenarios include: A scene in which the robot's picking mechanism is taking out a pallet or putting back a pallet, and the picking mechanism is located under the pallet; Alternatively, a scenario in which the backpack of the robot is in a docking position for receiving a material box; Or, a scenario where the charging mechanism of the robot is docked with a charging device; Alternatively, the current actual position of the robot is located on a main road and the lateral deviation is less than a set lateral difference; Alternatively, a scenario in which the extending direction of the backpack of the robot is perpendicular to the moving direction of the to-be-received material box.

7. The method according to claim 5, characterized in that The robot includes a picking mechanism, and the second type of scenario includes: A scenario in which the picking mechanism of the robot is performing an action of taking out a pallet or putting back a pallet, and the horizontal distance between the picking mechanism and the pallet is greater than a first set distance value; Alternatively, a scenario in which the difference between the current actual position and the current expected position is greater than a set position difference.

8. The method according to claim 5, characterized in that The robot comprises a picking mechanism, a backpack and / or a charging mechanism. The third category of scenarios includes: A scenario where the robot is located on a rail or track; The picking mechanism of the robot is performing the action of taking out a pallet or putting back a pallet. The picking mechanism is located below the pallet, and the pallet below includes a scene with a through hole whose size matches that of the picking mechanism.

9. The method according to any one of claims 1 to 8, characterized in that The controlling the movement state of the robot based on the parameter control strategy and the movement control parameter comprises: Based on the parameter control strategy, the mobile control parameter is subjected to dimensionality reduction processing to obtain the target control parameter after dimensionality reduction processing; Based on the target parameter, determining instruction information of a driving motor corresponding to the robot; The instruction information is sent to the driving motor, and the driving motor is used to control the movement state of the robot based on the instruction information.

10. The method according to claim 9, characterized in that The parameter control strategy is based on which the mobile control parameters are subjected to dimensionality reduction processing to obtain target control parameters after dimensionality reduction processing, including: The value of the mobile control parameter abandoned in the parameter control strategy is set to zero, and the obtained mobile control parameter is determined as the target control parameter.

11. A robot control device, characterized in that: The robot control device comprises: A judgment module, used to determine the movement control parameters of the robot from the current actual position to the current expected position based on the path information included in the task to be completed; A determination module, used to determine a parameter control strategy of the robot based on the scenario type corresponding to the task to be completed; A control module is used to control the movement state of the robot based on a parameter control strategy and the movement control parameters.

12. A control device, characterized in that: include: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the control device executes the robot control method according to any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the robot control method according to any one of claims 1 to 10 when executed by a processor.

14. A computer program product, characterized in that The computer program product comprises computer-executable instructions, which are used to implement the robot control method according to any one of claims 1 to 10 when executed by a processor.

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