Robot control method, device and equipment and robot

Abstract

The embodiment of the invention provides a robot control method, device and equipment and a robot, and relates to the technical field of intelligent storage. The method comprises the steps of determining first quality data of a robot at a current moment in a variable-speed driving process of the robot, and predicting a predicted speed of the robot at a next moment; according to the first quality data and the prediction speed, the advancing speed of the robot at the next moment is determined; and according to the advancing speed, the robot is controlled to run at the next moment. The method is used for achieving the effects that the movement parameters such as the advancing speed of the robot in the variable-speed driving process can adapt to the load of the robot, and the operation stability of the robot is improved.

Description

Technical Field

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

[0002] Robots have gradually been applied to various scenarios of human life, such as controlling warehouse robots to climb shelves to pick up and place goods.

[0003] In the prior art, based on the trapezoidal speed planning algorithm, in a preset acceleration section, for example, when climbing a shelf from the ground, the robot is controlled to accelerate at a constant acceleration.

[0004] However, in the above method, since the acceleration of the robot in the acceleration section is constant, the acceleration cannot be adjusted in time to adapt to the robot load that changes due to picking and placing goods, resulting in unbalanced operation of the robot or even rushing out of the climbing track. Summary of the invention

[0005] The disclosed embodiments provide a robot control method, device, equipment and robot to solve the technical problem that the robot cannot adjust the acceleration to adapt to the changing robot load, resulting in unbalanced operation of the robot or even rushing out of the climbing track.

[0006] In a first aspect, an embodiment of the present disclosure provides a robot control method, comprising:

[0007] During the robot's speed-changing driving process, determining the first mass data of the robot at the current moment, and predicting the predicted speed of the robot at the next moment; wherein the first mass data represents the mass of the robot itself and the transported goods;

[0008] Determining the travel speed of the robot at the next moment according to the first mass data and the predicted speed;

[0009] According to the travel speed, the operation of the robot at the next moment is controlled.

[0010] In a possible implementation, determining the travel speed of the robot at the next moment according to the first mass data and the predicted speed includes:

[0011] Determining a target acceleration of the robot at a next moment according to the first mass data and the predicted speed;

[0012] The travel speed of the robot at the next moment is determined according to the target acceleration.

[0013] In a possible implementation, determining a target acceleration of the robot at a next moment according to the first mass data and the predicted speed includes:

[0014] determining a first acceleration of the robot at a next moment according to the first mass data and the predicted speed;

[0015] Obtaining the recommended acceleration of the robot at the next moment;

[0016] The target acceleration is determined according to the first acceleration and the recommended acceleration.

[0017] In a possible implementation, obtaining the recommended acceleration of the robot at the next moment includes:

[0018] Determine the second mass data of the robot at the current moment according to the travel height of the robot at the current moment; wherein the travel height represents the height that the robot has traveled during the speed change driving process; and the second mass data represents the weight interval of the stored goods in which the robot is located at the current moment;

[0019] A recommended acceleration of the robot at a next moment is determined according to the second mass data.

[0020] In a possible implementation manner, determining the target acceleration according to the first acceleration and the recommended acceleration includes:

[0021] If it is determined that the first acceleration is less than or equal to the recommended acceleration, determining the first acceleration as the target acceleration;

[0022] If it is determined that the first acceleration is greater than the recommended acceleration, the recommended acceleration is determined as the target acceleration.

[0023] In a possible implementation, determining a first acceleration of the robot at a next moment according to the first mass data and the predicted speed includes:

[0024] Determining a second acceleration of the robot at a next moment according to the predicted speed;

[0025] The second acceleration is corrected according to the first mass data to obtain the first acceleration.

[0026] In a possible implementation, determining a second acceleration of the robot at a next moment according to the predicted speed includes:

[0027] According to the predicted speed, predict the predicted height of the robot at the next moment; and determine a preset travel height; wherein the preset travel height represents the total height that the robot needs to travel during the speed change process;

[0028] The second acceleration is determined according to the predicted speed, the predicted height and the preset traveling height.

[0029] In a possible implementation, predicting the predicted speed of the robot at the next moment includes:

[0030] Predicting a predicted acceleration of the robot at a next moment according to the first mass data;

[0031] The predicted speed is determined based on the predicted acceleration.

[0032] In a possible implementation, predicting the predicted acceleration of the robot at the next moment according to the first mass data includes:

[0033] Determine the travel height of the robot at the current moment, and determine a preset travel height; wherein the travel height represents the height that the robot has traveled during the speed change process, and the preset travel height represents the total height that the robot needs to travel during the speed change process;

[0034] The predicted acceleration of the robot at the next moment is predicted according to the traveling height, the preset traveling height, the first mass data and the traveling speed of the robot at the current moment.

[0035] In a second aspect, an embodiment of the present disclosure provides a control device for a robot, comprising:

[0036] A first determination module is used to determine the first mass data of the robot at a current moment and predict the predicted speed of the robot at a next moment during the robot's speed change driving process; wherein the first mass data represents the mass of the robot itself and the transported goods;

[0037] a second determination module, configured to determine a travel speed of the robot at a next moment according to the first mass data and the predicted speed;

[0038] The control module is used to control the operation of the robot at the next moment according to the travel speed.

[0039] In a possible implementation, the second determination module is specifically used to: determine a target acceleration of the robot at a next moment according to the first mass data and the predicted speed; and determine a travel speed of the robot at a next moment according to the target acceleration.

[0040] In a possible implementation, the second determination module is specifically used to: determine a first acceleration of the robot at a next moment based on the first mass data and the predicted speed; obtain a recommended acceleration of the robot at the next moment; and determine the target acceleration based on the first acceleration and the recommended acceleration.

[0041] In a possible implementation, the second determination module is specifically used to: determine the second mass data of the robot at the current moment according to the travel height of the robot at the current moment; wherein the travel height represents the height that the robot has traveled during the speed change driving process; the second mass data represents the weight range of the stored goods in which the robot is located at the current moment; and determine the recommended acceleration of the robot at the next moment according to the second mass data.

[0042] In a possible implementation, the second determination module is further specifically used to: if it is determined that the first acceleration is less than or equal to the recommended acceleration, determine the first acceleration as the target acceleration; if it is determined that the first acceleration is greater than the recommended acceleration, determine the recommended acceleration as the target acceleration.

[0043] In a possible implementation manner, the second determination module is further specifically used to: determine a second acceleration of the robot at a next moment according to the predicted speed; and correct the second acceleration according to the first mass data to obtain the first acceleration.

[0044] In a possible implementation, the second determination module is further specifically used to: predict the predicted height of the robot at the next moment based on the predicted speed; and determine a preset travel height; wherein the preset travel height represents the total height that the robot needs to travel during the speed change driving process; determine the second acceleration based on the predicted speed, the predicted height and the preset travel height.

[0045] In a possible implementation manner, the first determination module is specifically configured to: predict a predicted acceleration of the robot at a next moment according to the first mass data; and determine the predicted speed according to the predicted acceleration.

[0046] In a possible implementation, the first determination module is specifically used to: determine the travel height of the robot at a current moment, and determine a preset travel height; wherein the travel height represents the height that the robot has traveled during the speed change driving process, and the preset travel height represents the total height that the robot needs to travel during the speed change driving process; based on the travel height, the preset travel height, the first mass data and the travel speed of the robot at the current moment, predict the predicted acceleration of the robot at the next moment.

[0047] In a third aspect, an embodiment of the present disclosure provides an electronic device, including: a memory, a processor;

[0048] The memory stores computer-executable instructions;

[0049] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0050] In a fourth aspect, an embodiment of the present disclosure 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 first aspect above and / or various possible implementations of the first aspect.

[0051] In a fifth aspect, an embodiment of the present disclosure provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementations of the first aspect.

[0052] In a sixth aspect, an embodiment of the present disclosure provides a robot, wherein the robot is provided with the electronic device as described in the third aspect above.

[0053] The robot control method, device, equipment and robot provided by the embodiments of the present disclosure determine the robot's travel speed at the next moment according to the quality of the robot itself and the goods it is transporting at the current moment, as well as the predicted speed of the robot at the next moment, during the robot's speed-changing driving process, so as to control the robot's operation at the next moment; thereby, the robot's motion parameters such as the travel speed during the speed-changing driving process can adapt to the robot's load, and the travel speed changes more smoothly, thereby improving the robot's operating stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] 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.

[0055] Figure 1 A schematic diagram of an application scenario provided by the present disclosure;

[0056] Figure 2 A schematic diagram of the principle of a trapezoidal speed planning method provided by the present disclosure;

[0057] Figure 3 A schematic flow chart of a robot control method provided by one embodiment of the present disclosure;

[0058] Figure 4 For this disclosure Figure 3A schematic diagram of the principle of the robot's speed-changing driving process in the illustrated embodiment;

[0059] Figure 5 A schematic flow chart of a robot control method provided by another embodiment of the present disclosure;

[0060] Figure 6 A schematic flow chart of a robot control method provided by yet another embodiment of the present disclosure;

[0061] Figure 7 A schematic diagram of the structure of a robot control device provided by one embodiment of the present disclosure;

[0062] Figure 8 A schematic diagram of the structure of an electronic device provided by an embodiment of the present disclosure;

[0063] Fig. 9 A schematic diagram of the structure of a robot provided in accordance with an embodiment of the present disclosure.

[0064] 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

[0065] 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.

[0066] Figure 1 A schematic diagram of an application scenario provided by the present disclosure. Figure 1 As shown, the specific application scenario of the present invention includes an electronic device 101 in the robot. When climbing the shelf from the ground, based on the electronic device 101, the robot is controlled to accelerate at a constant acceleration so that the robot crawls on the vertical track on the shelf to the preset cargo storage area to pick up and place the cargo.

[0067] In one example, Figure 2A schematic diagram of the principle of a trapezoidal speed planning method provided by the present invention is based on the electronic device 101. In the initial stage, the robot is controlled to run at a constant acceleration and uniform acceleration. In the middle stage, the robot is controlled to run at a constant speed. In the final stage, the robot is controlled to run at a constant acceleration and uniform deceleration, so that the robot crawls on the vertical track on the shelf and reaches the preset position to pick up and place goods.

[0068] However, in the above method, since the acceleration of the robot in the acceleration section is constant, the acceleration cannot be adjusted in time to adapt to the robot load that changes due to picking and placing goods, resulting in unbalanced operation of the robot or even rushing out of the climbing track.

[0069] In response to the above technical problems, the present disclosure proposes the following technical concept: during the robot's speed-changing driving process, the robot's speed at the next moment is determined based on the robot's own quality and the goods it is carrying at the current moment, as well as the robot's predicted speed at the next moment, so as to control the robot's operation at the next moment. In this way, the problem in the prior art that the robot cannot adjust the acceleration to adapt to the changing robot load, resulting in unbalanced operation of the robot or even running out of the climbing track, can be solved.

[0070] 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.

[0071] Figure 3 A schematic diagram of a flow chart of a robot control method provided by an embodiment of the present disclosure, such as Figure 3 As shown, the method includes:

[0072] 201. During the robot's variable speed driving process, determine the first quality data of the robot at the current moment, and predict the predicted speed of the robot at the next moment; wherein the first quality data represents the quality of the robot itself and the transported goods.

[0073] Exemplarily, the execution subject of this embodiment may be an electronic device, hereinafter referred to as the device. The device may be a physical device or a virtual device for executing the control method of the robot. During the speed-changing driving process of the robot, such as the starting acceleration phase of the shelf robot when crawling the shelf or the final stop deceleration phase when it is about to reach the shelf target position, at each moment during the speed-changing driving process, the device can obtain the mass of the robot itself and the transported goods through the robot's internal weight sensor, and then obtain the mass of the robot itself and the transported goods, that is, the first mass data; and, through a preset speed prediction method, predict the predicted speed of the robot at the next moment, for example, the current travel speed of the robot, the speed change in the previous time period and other motion parameters can be calculated to obtain the predicted speed for processing.

[0074] 202. Determine the travel speed of the robot at the next moment according to the first mass data and the predicted speed.

[0075] Exemplarily, the device can calculate and process the first mass data of the robot at the current moment and the predicted speed at the next moment based on a preset speed planning algorithm to obtain the travel speed of the robot at the next moment.

[0076] 203. Control the robot's operation at the next moment according to the travel speed.

[0077] Exemplarily, the device controls the robot to change speed and travel to the next moment based on operating parameters such as the current moment's travel speed, so that the robot reaches the next moment's travel speed obtained based on the first mass data of the robot at the current moment.

[0078] For example, Figure 4 For this disclosure Figure 3The schematic diagram of the principle of the robot's variable speed driving process in the illustrated embodiment is as shown in the figure. When the robot is issued a task of picking up and placing goods, based on the known height of the shelf that the robot needs to climb, when the robot engages with the track on the shelf, when the robot performs speed planning, the target travel is divided into five sections, namely, the first section is an acceleration section for variable acceleration, the second section is a uniform speed section for uniform speed, the third section is a deceleration section for uniform deceleration, the fourth section is a crawling section for uniform speed, i.e., a slow-moving stage, and the fifth section is a stop section for uniform deceleration. Among them, the horizontal axis is the time axis, the vertical axis is the robot's travel speed, and the curve segment represents the change of the robot's travel speed over time in the above five stages, i.e., the process of the robot from starting acceleration to deceleration and stopping. Among them, in the acceleration section, the robot can be controlled to accelerate by using the above-mentioned method of processing the first mass data of the robot at the current moment and the predicted speed at the next moment to obtain the travel speed at the next moment. In the deceleration process, it can be as follows Figure 4 The uniform deceleration process shown can also be based on the above-mentioned method of calculating the travel speed at the next moment to control the robot to decelerate.

[0079] In the present embodiment, a control method for a robot is provided. During the speed-changing driving process of the robot, the travel speed of the robot at the next moment is determined according to the quality of the robot itself and the transported goods at the current moment, as well as the predicted speed of the robot at the next moment, so as to control the operation of the robot at the next moment; thereby, the movement parameters such as the travel speed of the robot during the speed-changing driving process can adapt to the robot load, the travel speed changes more smoothly, and the operation stability of the robot is improved.

[0080] Figure 5 A schematic flow chart of a robot control method provided by another embodiment of the present disclosure is shown as follows: Figure 5 As shown, the method includes:

[0081] 301. During the robot's speed-changing driving process, determine the first quality data of the robot at the current moment, and predict the predicted speed of the robot at the next moment; wherein the first quality data represents the quality of the robot itself and the transported goods.

[0082] Exemplarily, this step may refer to step 201 and will not be described in detail here.

[0083] 302. Determine a target acceleration of the robot at a next moment according to the first mass data and the predicted speed.

[0084] Exemplarily, the device can calculate and process the first mass data of the robot at the current moment and the predicted speed at the next moment based on a preset acceleration planning algorithm to obtain the target acceleration of the robot at the next moment, that is, the final variable speed travel acceleration of the robot from the current moment to the next moment.

[0085] In one example, step 302 includes the following steps:

[0086] The first step of step 302 is to determine the first acceleration of the robot at the next moment according to the first mass data and the predicted speed.

[0087] The second step of step 302 is to obtain the recommended acceleration of the robot at the next moment.

[0088] The third step of step 302 is to determine the target acceleration according to the first acceleration and the recommended acceleration.

[0089] Exemplarily, the device can calculate and process the first mass data of the robot at the current moment and the predicted speed at the next moment based on a preset acceleration planning algorithm to obtain the first acceleration of the robot at the next moment; obtain the recommended acceleration of the robot at the next moment, which can be preset or calculated through the motion parameters of the robot at the current moment; based on the preset acceleration planning algorithm, comprehensively analyze and process the first acceleration and recommended acceleration of the robot at the next moment to determine the target acceleration of the robot at the next moment.

[0090] In one example, the first step of step 302 includes:

[0091] Step 1: Determine the second acceleration of the robot at the next moment based on the predicted speed.

[0092] Step 2: Correct the second acceleration according to the first mass data to obtain the first acceleration.

[0093] Specifically, in order to obtain more accurate acceleration and further improve the smoothness of speed changes, the device can pre-process the currently predicted speed of the robot at the next moment and other motion parameters of the current robot based on a preset prediction algorithm to obtain the second acceleration of the robot at the next moment. Based on a preset correction algorithm, the first mass data of the robot at the current moment and the second acceleration at the next moment are corrected and calculated to obtain the corrected second acceleration, i.e., the first acceleration.

[0094] For example, in order to simplify the calculation process, a speed increment step length can also be set, wherein the speed increment step length is determined according to the speed finally reached by the robot in the acceleration section and the running time in the acceleration section to characterize the speed change, which can be the speed change of the robot during the entire speed change driving process, or the speed change of the robot within the previous preset time; based on the preset algorithm, the motion parameter of the speed increment step length and the predicted speed of the robot at the next moment are processed to obtain the second acceleration of the robot at the next moment, and then based on the first mass data m of the robot at the current moment, the corresponding correction parameter k is determined. m , according to the correction parameter k m , the second acceleration of the robot at the next moment is corrected to obtain the first acceleration.

[0095] In one example, step 1 of the first step of step 302 includes: predicting the predicted height of the robot at the next moment based on the predicted speed; and determining a preset travel height; wherein the preset travel height represents the total height that the robot needs to travel during the speed change driving process; determining the second acceleration based on the predicted speed, the predicted height and the preset travel height.

[0096] Specifically, the device can calculate and process the predicted speed of the robot at the next moment according to a preset algorithm, and predict the predicted height of the robot at the next moment; at the same time, determine the preset height set in advance, that is, the total height that the robot needs to travel on the shelf during the acceleration or deceleration process; call the preset algorithm, and combine the preset speed increment step to calculate and process the predicted speed, predicted height, and preset travel height of the robot at the next moment, and obtain a second acceleration for correction processing.

[0097] For example, the device determines the height that the robot has traveled on the shelf at the current moment through the encoder, and can predict the robot's speed V at the next moment based on the preset algorithm. 预测 , the robot's current speed and travel height are calculated and processed to obtain the robot's predicted height H at the next moment 预测 , according to the preset formula The predicted speed V of the robot at the next moment 预测 , predicted height H 预测 , preset travel height H, preset speed increment step length V add Calculation processing is performed to obtain the second acceleration a.

[0098] In one example, the second step of step 302 includes:

[0099] Step 1: Determine the second mass data of the robot at the current moment according to the travel height of the robot at the current moment; wherein the travel height represents the height that the robot has traveled during the speed change driving process; and the second mass data represents the weight range of the stored goods in which the robot is located at the current moment.

[0100] Step 2: Determine the recommended acceleration of the robot at the next moment according to the second mass data.

[0101] Specifically, the device determines the weight range of the stored goods where the robot is located at the current moment, that is, the traveling height, through the internal encoder of the robot, and determines the second mass data corresponding to the traveling height of the robot at the current moment according to the preset correspondence between each traveling height and each second mass data, wherein each second mass data represents the weight range of the stored goods where the robot is located at the current moment; according to the preset correspondence between each second mass data and each recommended acceleration, the recommended acceleration corresponding to the second mass data of the robot at the current moment can be determined.

[0102] For example, three different cargo box weight intervals can be set in the shelf height direction, that is, three different current travel heights correspond to three different stored cargo weight intervals, which can be determined according to the maximum load capacity of the robot, and then each cargo weight interval has a corresponding acceleration recommendation value, and then, the corresponding acceleration recommendation value can be determined according to the current travel height.

[0103] In one example, the third step of step 302 includes: if it is determined that the first acceleration is less than or equal to the recommended acceleration, determining the first acceleration as the target acceleration; if it is determined that the first acceleration is greater than the recommended acceleration, determining the recommended acceleration as the target acceleration.

[0104] Specifically, the device compares the recommended acceleration of the robot at the next moment with the first acceleration. If it is determined that the first acceleration is less than or equal to the recommended acceleration, the first acceleration is determined as the target acceleration of the robot at the next moment. If it is determined that the first acceleration is greater than the recommended acceleration, the recommended acceleration is determined as the target acceleration of the robot at the next moment.

[0105] 303. Determine the robot's travel speed at the next moment according to the target acceleration.

[0106] Exemplarily, the device can control the robot to change speed to the next moment at the target acceleration based on the motion parameters such as the travel speed at the current moment according to the determined target acceleration of the robot at the next moment, so that the robot reaches a suitable operating speed at the next moment, that is, the travel speed of the robot at the next moment.

[0107] 304. Control the operation of the robot at the next moment according to the travel speed.

[0108] Exemplarily, this step may refer to step 203 and will not be described in detail here.

[0109] In this embodiment, on the basis of the above embodiment, the corresponding recommended acceleration is determined based on the mass condition and travel height of the robot at the current moment, and then the appropriate target acceleration can be determined in combination with the calculated first acceleration. This can not only ensure the smooth operation of the robot during the operation process based on the target acceleration, but also reduce the impact deformation on the shelf and extend the service life of the shelf track.

[0110] Figure 6 A flowchart of a robot control method provided by another embodiment of the present disclosure is shown as follows: Figure 6 As shown, the method includes:

[0111] 401. During the speed change process of the robot, determine the first mass data of the robot at the current moment.

[0112] Exemplarily, this step may refer to step 201 and will not be described in detail here.

[0113] 402. Predict the predicted acceleration of the robot at the next moment according to the first mass data.

[0114] Exemplarily, the device may process the first mass data of the robot at the current moment based on a preset prediction algorithm and in combination with the motion parameters of the robot at the current moment, and predict the predicted acceleration of the robot at the next moment.

[0115] In one example, step 402 includes:

[0116] Step 1: determine the current travel height of the robot and determine the preset travel height; wherein the travel height represents the height that the robot has traveled during the speed change process, and the preset travel height represents the total height that the robot needs to travel during the speed change process;

[0117] Step 2: predict the predicted acceleration of the robot at the next moment according to the traveling height, the preset traveling height, the first mass data and the traveling speed of the robot at the current moment.

[0118] Specifically, in the process of predicting acceleration, the device can first obtain the height that the robot has traveled during the speed change process from the encoder, for example, the height that the robot has climbed on the shelf, and determine the preset travel height, that is, the total height that the robot needs to travel during the speed change process; then, the device is based on a preset algorithm, such as the calculation formula The robot's current speed V t , Travel height H h , preset travel height H, first mass data m and preset speed increment step length V add Calculate and get the predicted acceleration a of the robot at the next moment 预测 ; Among them, the first mass data m can be directly the total weight of the robot itself and the transported goods, or it can be a mass parameter obtained based on the total weight of the robot itself and the transported goods.

[0119] 403. Determine a predicted speed based on the predicted acceleration.

[0120] For example, the device can use the relationship between speed and acceleration, such as predicting the speed V 预测 =V t +a 预测 *Δt, and combined with the current first mass data of the robot, to calculate the predicted acceleration of the robot at the next moment, the current travel speed, the time interval between the current moment and the next moment, and predict the predicted speed of the robot at the next moment for subsequent calculation of the travel speed of the robot at the next moment.

[0121] 404. Determine the travel speed of the robot at the next moment according to the first mass data and the predicted speed.

[0122] Exemplarily, this step may refer to step 202 and will not be described in detail here.

[0123] 405. Control the operation of the robot at the next moment according to the travel speed.

[0124] Exemplarily, this step may refer to step 203 and will not be described in detail here.

[0125] In this embodiment, on the basis of the above embodiment, the predicted acceleration of the robot at the next moment is predicted by combining the mass condition of the robot at the current moment, and then a more accurate predicted speed is predicted, which is used to determine a more accurate operating speed of the robot at the next moment, so that the speed change of the robot during the speed change process is smoother, so as to reduce the wear between the gears and racks of the robot and ensure the smooth operation and service life of the robot.

[0126] Figure 7 A schematic diagram of the structure of a robot control device provided by an embodiment of the present disclosure is shown in FIG. Figure 7 As shown, the device 50 comprises:

[0127] The first determination module 501 is used to determine the first quality data of the robot at the current moment and predict the predicted speed of the robot at the next moment during the robot's speed change driving process; wherein the first quality data represents the quality of the robot itself and the transported goods;

[0128] A second determination module 502 is used to determine the travel speed of the robot at the next moment according to the first quality data and the predicted speed;

[0129] The control module 503 is used to control the operation of the robot at the next moment according to the travel speed.

[0130] In a possible implementation, the second determination 502 module is specifically used to: determine the target acceleration of the robot at the next moment according to the first mass data and the predicted speed; and determine the travel speed of the robot at the next moment according to the target acceleration.

[0131] In a possible implementation, the second determination module 502 is specifically used to: determine a first acceleration of the robot at a next moment according to the first quality data and the predicted speed; obtain a recommended acceleration of the robot at the next moment; and determine a target acceleration according to the first acceleration and the recommended acceleration.

[0132] In a possible implementation, the second determination module 502 is specifically used to: determine the second mass data of the robot at the current moment according to the travel height of the robot at the current moment; wherein the travel height represents the height that the robot has traveled during the speed change driving process; the second mass data represents the weight range of the stored goods in which the robot is located at the current moment; and determine the recommended acceleration of the robot at the next moment according to the second mass data.

[0133] In a possible implementation, the second determination module 502 is further specifically configured to: if it is determined that the first acceleration is less than or equal to the recommended acceleration, determine the first acceleration as the target acceleration; if it is determined that the first acceleration is greater than the recommended acceleration, determine the recommended acceleration as the target acceleration.

[0134] In a possible implementation, the second determination module 502 is further specifically configured to: determine a second acceleration of the robot at a next moment according to the predicted speed; and perform correction processing on the second acceleration according to the first mass data to obtain the first acceleration.

[0135] In a possible implementation, the second determination module 502 is further specifically used to: predict the predicted height of the robot at the next moment based on the predicted speed; and determine a preset travel height; wherein the preset travel height represents the total height that the robot needs to travel during the speed change driving process; and determine the second acceleration based on the predicted speed, the predicted height and the preset travel height.

[0136] In a possible implementation, the first determination module 501 is specifically used to: predict the predicted acceleration of the robot at the next moment according to the first quality data; and determine the predicted speed according to the predicted acceleration.

[0137] In a possible implementation, the first determination module 501 is specifically used to: determine the travel height of the robot at the current moment, and determine a preset travel height; wherein the travel height represents the height that the robot has traveled during the speed change driving process, and the preset travel height represents the total height that the robot needs to travel during the speed change driving process; based on the travel height, the preset travel height, the first mass data and the travel speed of the robot at the current moment, predict the predicted acceleration of the robot at the next moment.

[0138] The device of this embodiment can execute the technical solution in the above method. Its specific implementation process and technical principles are the same and will not be repeated here.

[0139] It should be noted that it should be understood that the division of the various modules of the above device is only a division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated. And these modules can all be implemented in the form of software called by processing elements; they can also be all implemented in the form of hardware; some modules can also be implemented in the form of software called by processing elements, and some modules can be implemented in the form of hardware. Each module can be a separately established processing element, or it can be integrated in a chip of the above device. In addition, it can also be stored in the memory of the above device in the form of program code, and called and executed by a processing element of the above device. The functions of each module. In addition, all or part of these modules can be integrated together, or they can be implemented independently. The processing element here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each module above can be completed by an integrated logic circuit of hardware in the processor element or instructions in the form of software.

[0140] Figure 8 A schematic diagram of the structure of an electronic device provided by an embodiment of the present disclosure, such as Figure 8 As shown, the electronic device 60 includes: a memory 601 and a processor 602; the memory 601 is a memory for storing instructions executable by the processor 602.

[0141] The processor 602 is configured to execute the method provided in the above embodiment.

[0142] The electronic device further includes a receiver 603 and a transmitter 604. The receiver 603 is used to receive instructions and data sent by other devices, and the transmitter 604 is used to send instructions and data to external devices.

[0143] The specific implementation process of the processor can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0144] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0145] The memory may include a high-speed memory (Random Access Memory, referred to as RAM), and may also include a non-volatile memory (Non-volatile Memory, referred to as NVM), such as at least one disk memory.

[0146] For example, Fig. 9 A schematic diagram of the structure of a robot provided by an embodiment of the present disclosure; Fig. 9 As shown, the handling robot 80 includes a chassis component 81, a climbing component 82 and a pick-and-place component 83, and the robot 80 can walk in the lane through the chassis component 81. The climbing component 82 is arranged on the chassis component 81, and the robot 80 can climb to different heights on the shelf through the cooperation of the climbing component 82 and the rack, and can pick up and place the material box at the cargo position in the shelf through the pick-and-place component 83.

[0147] The disclosed embodiment also provides a chip for executing instructions, which is used to execute the technical solution of the processing method in the above embodiment.

[0148] The embodiment of the present disclosure further provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed on a computer, the computer executes the technical solution of the processing method of the above embodiment.

[0149] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory, electrically erasable programmable read-only memory, erasable programmable read-only memory, programmable read-only memory, read-only memory, magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0150] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in a dedicated integrated circuit. Of course, the processor and the readable storage medium can also exist in a device as discrete components.

[0151] The embodiments of the present disclosure also provide a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When the at least one processor executes the computer program, the technical solution of the processing method in the above embodiments can be implemented.

[0152] Those skilled in the art will appreciate that all or part of the steps of implementing the above-mentioned method embodiments may be completed by hardware associated with program instructions. The aforementioned program may be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed.

[0153] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A robot control method, characterized in that: include: During the robot's speed-changing driving process, determining the first mass data of the robot at the current moment, and predicting the predicted speed of the robot at the next moment; wherein the first mass data represents the mass of the robot itself and the transported goods; Determining the travel speed of the robot at the next moment according to the first mass data and the predicted speed; According to the travel speed, the operation of the robot at the next moment is controlled.

2. The method according to claim 1, characterized in that Determining the travel speed of the robot at a next moment according to the first mass data and the predicted speed includes: determining a target acceleration of the robot at a next moment according to the first mass data and the predicted speed; The travel speed of the robot at the next moment is determined according to the target acceleration.

3. The method according to claim 2, characterized in that Determining a target acceleration of the robot at a next moment according to the first mass data and the predicted speed includes: determining a first acceleration of the robot at a next moment according to the first mass data and the predicted speed; Obtaining the recommended acceleration of the robot at the next moment; The target acceleration is determined according to the first acceleration and the recommended acceleration.

4. The method according to claim 3, characterized in that Obtaining the recommended acceleration of the robot at the next moment, including: Determine the second mass data of the robot at the current moment according to the travel height of the robot at the current moment; wherein the travel height represents the height that the robot has traveled during the speed change driving process; and the second mass data represents the weight range of the stored goods in which the robot is located at the current moment; A recommended acceleration of the robot at a next moment is determined according to the second mass data.

5. The method according to claim 4, characterized in that Determining the target acceleration according to the first acceleration and the recommended acceleration includes: If it is determined that the first acceleration is less than or equal to the recommended acceleration, determining the first acceleration as the target acceleration; If it is determined that the first acceleration is greater than the recommended acceleration, the recommended acceleration is determined as the target acceleration.

6. The method according to claim 3, characterized in that Determining a first acceleration of the robot at a next moment according to the first mass data and the predicted speed includes: Determining a second acceleration of the robot at a next moment according to the predicted speed; The second acceleration is corrected according to the first mass data to obtain the first acceleration.

7. The method according to claim 6, characterized in that Determining a second acceleration of the robot at a next moment according to the predicted speed includes: According to the predicted speed, predict the predicted height of the robot at the next moment; and determine a preset travel height; wherein the preset travel height represents the total height that the robot needs to travel during the speed change process; The second acceleration is determined according to the predicted speed, the predicted height and the preset traveling height.

8. The method according to any one of claims 1 to 7, characterized in that Predicting the predicted speed of the robot at the next moment, including: predicting a predicted acceleration of the robot at a next moment according to the first mass data; The predicted speed is determined based on the predicted acceleration.

9. The method according to claim 8, characterized in that Predicting the predicted acceleration of the robot at the next moment according to the first mass data includes: Determine the travel height of the robot at the current moment, and determine a preset travel height; wherein the travel height represents the height that the robot has traveled during the speed change process, and the preset travel height represents the total height that the robot needs to travel during the speed change process; The predicted acceleration of the robot at the next moment is predicted according to the traveling height, the preset traveling height, the first mass data and the traveling speed of the robot at the current moment.

10. A robot control device, characterized in that: include: A first determination module is used to determine the first mass data of the robot at a current moment and predict the predicted speed of the robot at a next moment during the robot's speed change driving process; wherein the first mass data represents the mass of the robot itself and the transported goods; a second determination module, configured to determine a travel speed of the robot at a next moment according to the first mass data and the predicted speed; The control module is used to control the operation of the robot at the next moment according to the travel speed.

11. An electronic device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 9 when executed by a processor.

13. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

14. A robot, characterized in that: The robot is provided with the electronic device as claimed in claim 11.

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