Intelligent equipment control method and device, medium, product and control equipment

Abstract

The invention relates to an intelligent equipment control method and device, a medium, a product and control equipment. The target mass of a load object needed by intelligent equipment is obtained; determining change limitation information of a target motion parameter of the intelligent equipment according to the target quality; and according to the target motion parameter and the change limitation information, controlling the intelligent equipment load object to operate. Therefore, the change limiting condition of the target motion parameter of the intelligent equipment is determined by combining the mass of the loaded object of the intelligent equipment, so that the change limiting condition of the target motion parameter of the intelligent equipment can be dynamically adjusted according to different masses of the loaded object when the operation of the loaded object of the intelligent equipment is controlled; therefore, the operation stability of the intelligent equipment is improved.

Description

Technical Field

[0001] The present application relates to the field of intelligent device control technology, and in particular to an intelligent device control method, device, medium, product and control device. Background Art

[0002] The existing intelligent device control method usually plans a path in advance and controls the operation of the intelligent device according to the pre-planned path.

[0003] However, due to various complex situations in real scenarios where smart devices carry objects and move them, there are problems such as objects falling during the process of moving smart devices, resulting in poor operating stability of smart devices. Summary of the invention

[0004] The embodiments of the present application provide a smart device control method, apparatus, storage medium, computer program product, and control device. By combining the mass of an item carried by the smart device, the change restriction conditions of the target motion parameters of the smart device are determined. When the smart device is controlled to carry an object, the change restriction conditions of the target motion parameters of the smart device can be dynamically adjusted according to the mass of the item carried by the smart device, so as to improve the stability of the control of the smart device during operation.

[0005] The present application provides a method for controlling a smart device, including:

[0006] Obtain the target mass of the load object required by the smart device;

[0007] Determining, according to the target mass, change restriction information of the target motion parameter of the smart device;

[0008] According to the target motion parameter and the change restriction information, the smart device is controlled to carry the object to run.

[0009] Accordingly, an embodiment of the present application provides a smart device control device, comprising:

[0010] A target mass acquisition unit, used to acquire the target mass of the load object required by the intelligent device;

[0011] a change restriction information determining unit, configured to determine change restriction information of a target motion parameter of the smart device according to the target mass;

[0012] A control unit is used to control the operation of the smart device carrying the object according to the target motion parameter and the change restriction information.

[0013] In addition, an embodiment of the present application also provides a storage medium, which stores a computer program. When the computer program runs on a smart device processor, the computer program is used to enable the smart device processor to execute any smart device control method provided in the embodiment of the present application.

[0014] In addition, an embodiment of the present application also provides a computer program product, including a computer program or instructions, which, when executed by a processor, implements any one of the smart device control methods provided in the embodiments of the present application.

[0015] In addition, an embodiment of the present application also provides a control device, including one or more processors and a memory, the memory stores a computer program, and the processor is used to run the computer program in the memory to implement the smart device control method provided in the embodiment of the present application.

[0016] In the embodiment of the present application, the target mass of the object to be loaded by the smart device is obtained; according to the target mass, the change restriction information of the target motion parameter of the smart device is determined; according to the target motion parameter and the change restriction information, the operation of the object loaded by the smart device is controlled. In this way, by combining the mass of the object loaded by the smart device, the change restriction conditions of the target motion parameter of the smart device are determined, so that when controlling the operation of the object loaded by the smart device, the change restriction conditions of the target motion parameter of the smart device can be dynamically adjusted according to the different masses of the objects loaded, so as to improve the stability of the operation of the smart device. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 This is a schematic diagram of an implementation environment scenario of the intelligent device control method provided in the embodiment of the present application;

[0019] Figure 2 This is a flow chart of a smart device control method provided by an embodiment of the present application;

[0020] Figure 3 This is a schematic diagram of a scenario of a smart device control method provided by an embodiment of the present application;

[0021] Figure 4 This is another scenario schematic diagram of the intelligent device control method provided by an embodiment of the present application;

[0022] Figure 5 This is a schematic diagram of a scenario in which local path planning is required in a smart device control method provided by an embodiment of the present application;

[0023] Figure 6 It is a schematic diagram of the running status information of the location point of the target local path in the intelligent device control method provided by one embodiment of the present application;

[0024] Figure 7 This is a schematic diagram of a scenario of local path planning of a smart device control method provided by an embodiment of the present application;

[0025] Figure 8 It is a target partial path and a flow chart of a smart device control method provided by an embodiment of the present application;

[0026] Fig. 9 It is a structural schematic diagram of an intelligent device control device provided by an embodiment of the present application;

[0027] Fig.10 It is a structural diagram of a control device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0029] In addition, the term "plurality" in the embodiments of the present application refers to two or more than two. The terms "first" and "second" in the embodiments of the present application are used to distinguish descriptions and should not be understood as implying relative importance.

[0030] The embodiments of the present application provide a method, device, storage medium, computer program product and control device for controlling an intelligent device. The intelligent device control device can be integrated in a control device, which can be a server or a terminal.

[0031] Among them, the server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, network acceleration services (Content Delivery Network, CDN), as well as big data and artificial intelligence platforms.

[0032] The terminal may be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, etc., but is not limited thereto. The terminal and the server may be directly or indirectly connected via wired or wireless communication, and this application does not limit this.

[0033] See also Figure 1 , taking the intelligent device control device integrated into the control device as an example, Figure 1 A schematic diagram of an implementation scenario of the smart device control method provided in an embodiment of the present application, wherein the control device may be a terminal device, which obtains the target mass of the load object required by the smart device; determines the change limit information of the target motion parameters of the smart device based on the target mass; and controls the operation of the load object of the smart device based on the target motion parameters and the change limit information.

[0034] It should be noted that Figure 1 The implementation environment scenario diagram of the smart device control method shown is only an example. The implementation environment scenario of the smart device control method described in the embodiment of the present application is to more clearly illustrate the technical solution of the embodiment of the present application, and does not constitute a limitation on the technical solution provided by the embodiment of the present application. It is known to those skilled in the art that with the evolution of data processing and the emergence of new business scenarios, the technical solution provided by the present application is also applicable to similar technical problems.

[0035] The solutions provided by the embodiments of the present application are specifically described by the following embodiments. It should be noted that the description order of the following embodiments is not intended to limit the preferred order of the embodiments.

[0036] This embodiment will be described from the perspective of an intelligent device control apparatus, which may be specifically integrated into a control device, which may be a terminal and / or a server, and this application does not limit this.

[0037] See also Figure 2 , Figure 2 1 is a flow chart of a smart device control method provided by an embodiment of the present application. The smart device control method may include the following steps S101 to S103:

[0038] S101. Obtain a target mass of a load object required by a smart device.

[0039] Among them, smart devices refer to devices that require load objects to operate.

[0040] The specific type of smart device can be selected according to actual conditions and is not limited in the embodiments of the present application.

[0041] In some optional embodiments, the intelligent device includes at least one of an automated guided vehicle (AGV) and an intelligent mechanical device. The guided vehicle may include a lurking automated guided vehicle, a towing automated guided vehicle, a dumping automated guided vehicle, a lifting automated guided vehicle, a forklift automated guided vehicle, etc. The intelligent mechanical device may include a manipulator, a robot, etc.

[0042] For example, the intelligent device can be an automatic guided vehicle, such as a lurking automatic guided vehicle, a towing automatic guided vehicle, a dumping automatic guided vehicle, a lifting automatic guided vehicle, a forklift automatic guided vehicle, etc. Among them, a lurking automatic guided vehicle refers to a guided vehicle that dives into the bottom of a material vehicle and realizes material delivery and recovery operations through an automatic hooking and detaching mechanism. A towing automatic guided vehicle refers to a guided vehicle that can automatically lift materials with a carrying platform and can operate synchronously with an assembly line. For other specific functions, please refer to existing guided vehicles, which will not be repeated here. For another example, the intelligent device can also be an intelligent mechanical device, such as a manipulator, a robot, etc.

[0043] The specific type of the object carried by the smart device can be selected according to the actual situation, and the embodiment of the present application does not limit it. For example, the object carried by the smart device is a shelf, or the object carried by the smart device is a shelf and goods placed on the shelf, or the object carried by the smart device is a pallet, or the object carried by the smart device is a container.

[0044] The specific content of the target mass can be selected according to the actual situation, and the embodiment of the present application does not limit it. For example, the target mass can be the actual mass of the object carried by the smart device, or the target mass can be the theoretical mass of the object carried by the smart device.

[0045] S102: Determine, according to the target quality, change restriction information of the target motion parameters of the smart device.

[0046] The target motion parameter refers to a motion parameter whose change can be limited by the smart device based on mass. The target motion parameter can be the acceleration of the smart device, and the target operation parameter can also be the speed of the smart device.

[0047] The change restriction information refers to the conditions for restricting the target motion parameters, and its specific content is adjusted according to the target quality.

[0048] S103: Control the operation of the object loaded by the smart device according to the target motion parameters and the change restriction information.

[0049] It can be seen that in the intelligent device control method provided in the embodiment of the present application, the target mass of the object to be loaded by the intelligent device is obtained; according to the target mass, the change restriction information of the target motion parameters of the intelligent device is determined; according to the target motion parameters and the change restriction information, the operation of the object loaded by the intelligent device is controlled. In this way, by combining the mass of the object loaded by the intelligent device, the change restriction conditions of the target motion parameters of the intelligent device are determined, so that when controlling the operation of the object loaded by the intelligent device, the change restriction conditions of the target motion parameters of the intelligent device can be dynamically adjusted according to the different masses of the objects loaded, so as to improve the stability of the operation of the intelligent device.

[0050] In some optional embodiments, the process of determining the change limit information of the target motion parameters of the smart device based on the target mass may include: determining the maximum acceleration of the smart device when it meets the stable operation conditions based on the target mass; and determining the change limit information of the target motion parameters of the smart device based on the maximum acceleration.

[0051] Among them, the stable operation condition refers to the condition that when the intelligent device is controlled to operate the object of the target mass, there will be no drop of the object due to excessive speed or other reasons.

[0052] The above-mentioned stable running condition includes that the resultant force acting on the object is not greater than the sliding friction acting on the object.

[0053] Specifically, the above stable operation condition can be expressed according to the following formula (1):

[0054] f>=F (1)

[0055] Among them, f refers to the sliding friction force exerted on the object, and F refers to the resultant force exerted on the object.

[0056] Based on this, in some optional embodiments, the process of determining the maximum acceleration of the smart device when it meets the stable operation conditions based on the target mass may include: determining the resultant force acting on the object based on the acceleration when the smart device loads the object and the target mass; determining the sliding friction acting on the object based on the pressure acting on the object and the dynamic friction coefficient; determining the acceleration when the resultant force acting on the object is equal to the sliding friction acting on the object, and using the acceleration as the maximum acceleration when the smart device meets the stable operation conditions.

[0057] Specifically, the resultant force on the object can be determined according to the following formula (2):

[0058] F=ma (2)

[0059] Among them, F refers to the resultant force acting on the object, m refers to the target mass, and a refers to the acceleration when the smart device loads the object.

[0060] Furthermore, the sliding friction force on the object is determined according to the following formula (3):

[0061] f=μN (3)

[0062] Among them, f refers to the sliding friction force exerted on the object, μ refers to the dynamic friction coefficient, and N refers to the pressure exerted on the object.

[0063] Combining formula (1) to formula (3), formula (4) can be derived. The above stable operation condition is expressed as follows:

[0064] μN>=ma (4)

[0065] It should be noted that, when the object is in horizontal condition, the pressure on the object can be expressed by the following formula (5):

[0066] N=mg (5)

[0067] Among them, N refers to the pressure on the object, m refers to the target mass, and g is the acceleration due to gravity.

[0068] It can be seen from this that when the dynamic friction coefficient and the acceleration of gravity are known, it is only necessary to find out the mass of the object loaded by the smart device lock and the acceleration of the smart device when it is running, so as to determine the stable motion state of the smart device when loading the object.

[0069] In some optional embodiments, the process of determining the sliding friction force exerted on the object based on the pressure exerted on the object and the dynamic friction coefficient may include: obtaining the influencing factors for the pressure exerted on the object and the influence coefficient of the influencing factors; determining the actual pressure exerted on the object based on the influencing factors, the influence coefficient of the influencing factors, the target mass and the acceleration of gravity; and determining the sliding friction force exerted on the object based on the actual pressure exerted on the object and the dynamic friction coefficient.

[0070] The pressure on an object under ideal conditions is as shown in formula (5). However, in reality, the pressure on an object is affected by many factors. Therefore, the actual pressure on the object can be obtained by combining the influencing factors of the pressure on the object and the influence coefficients of the influencing factors.

[0071] Specifically, the actual pressure on the object can be expressed according to the following formula (6):

[0072] N 实际 = mg-ζe g (6)

[0073] Among them, N actually refers to the actual pressure on the object, ζ refers to the influence coefficient, and e g Refers to influencing factors.

[0074] Taking the target mass as the actual mass as an example, combining the above formula (4) and formula (6), formula (7) can be derived, and the maximum acceleration is expressed as follows according to formula (7):

[0075]

[0076] Among them, a max Refers to the maximum acceleration, m a It refers to the actual quality.

[0077] It should be noted that the actual mass can be expressed according to the following formula (8):

[0078] m a =m+m e (8)

[0079] Among them, m a refers to the actual mass, m refers to the theoretical mass, and m e Refers to the mass error value.

[0080] By adjusting the maximum acceleration of the smart device for the different masses of the objects loaded on the smart device, the change restriction conditions of the target motion parameters of the smart device are determined. When controlling the operation of the smart device loaded with objects, the change restriction conditions of the target motion parameters of the smart device can be dynamically adjusted according to the different masses of the objects loaded, so as to improve the stability of controlling the operation of the smart device.

[0081] In some optional embodiments, the target motion parameter includes the speed of the smart device.

[0082] Based on this, the above process of controlling the smart device to load the object to run according to the target motion parameters and the change limit information may include: determining the second speed of the smart device at the next moment according to the first speed of the smart device at the current moment and the operation status model; if the speed direction of the first speed is different from the speed direction of the second speed, then controlling the smart device to load the object to run based on the operation status model, the change limit information, the first speed and the second speed.

[0083] The operating state model refers to a model determined based on a speed curve and a maximum acceleration of the smart device under load, and is used to ensure that the operation of the smart device meets stable operating conditions.

[0084] The first speed and the second speed are both vectors. The difference between the speed direction of the first speed and the speed direction of the second speed indicates a turning driving state of the smart device.

[0085] It should be noted that when a smart device is turning, due to the change in speed direction, the acceleration of the turning process in the direction before the turn may exceed the maximum acceleration configured for the smart device by the traditional method, resulting in the smart device being unable to run smoothly. For example, see Figure 3 , Figure 3 The figure is a speed diagram of the smart device in a 90° turning state, wherein v1 refers to the speed of the smart device at the previous moment in the actual application process, and v2 refers to the speed of the smart device at the current moment in the actual application process, wherein v1=v2, which makes the load object of the smart device run unsteadily in the turning state.

[0086] Since the system cannot directly obtain the acceleration, it is necessary to derive the acceleration and velocity components. Figure 4 , the relationship between acceleration and velocity v1 and velocity v2 can be expressed as follows:

[0087] v2sinθ>=v1-0.06a max

[0088] v2cosθ<0.06a max

[0089] v2<v max (9)

[0091] Wherein, θ refers to the angle between speed v1 and speed v2, and 0.06 represents a constant, which can be determined according to the operating cycle configured by the smart device. max is the maximum speed, a max It refers to the maximum acceleration.

[0092] The specific derivation process of the above formula (9) can be referred to the following formula (10):

[0093]

[0094] v 2y =v2sinθ

[0095] V 2x =V2cosθ

[0096]

[0097] It should be noted that the running state model is configured with at least one corresponding relationship between speed and time, and change restriction information.

[0098] Specifically, at least one corresponding relationship between the speed and time configured in the above running state model can be expressed according to the following formula (11):

[0099]

[0100] It should be noted that in formula (11), v0 to v6 are used to represent the initial speed in different time intervals, and v represents the terminal speed determined by the initial speed in different time intervals and the corresponding relationship between the speed and time in the time interval.

[0101] It should be noted that, in order to ensure the efficiency and safety of the smart device in the process of executing the task, at least one corresponding relationship between the speed and time configured by the running state model can be predetermined.

[0102] Exemplarily, the above formula (11) can be derived according to the following process:

[0103] Based on the speed curve, determine the time intervals of different speed states of the intelligent device during operation: the speed of the starting interval [t0-t1], the speed of the acceleration interval [t1-t2], the speed of the interval approaching stability [t2-t3], the speed of the stable interval [t3-t4], the speed of the deceleration interval [t4-t5] starting from the stable state, the speed of the deceleration interval [t5-t6], and the speed of the end interval [t6-t7];

[0104] Determine the acceleration at each time interval;

[0105] Based on the time interval and acceleration, the correspondence between speed and time is determined.

[0106] Specifically, the acceleration of the seven intervals of the above-mentioned smart device during operation can be determined according to the following formula (12):

[0107]

[0108] Wherein, a refers to the running acceleration of the smart device determined at a moment. max refers to the maximum acceleration, and J refers to the jerk, which is the rate of change of acceleration.

[0109] Specifically, the corresponding relationship between speed and time can be derived according to the following formula (12):

[0110] The initial acceleration a0 and the final acceleration a per unit time can be expressed as follows: t The relationship between:

[0111] a t=Jt+a0 (13)

[0112] Combined with formula (13), the average acceleration per unit time can be expressed as follows according to formula (14):

[0113]

[0114] Combining formula (13) to formula (14), and based on the relationship between acceleration, speed and time, the relationship between speed and time can be derived according to the following formula (15):

[0115]

[0116]

[0117] When the initial acceleration is 0, the relationship between velocity and time is expressed as follows:

[0118]

[0119] Since the velocity is a variable when the acceleration remains constant, we can introduce variables τ and T:

[0120] τ k =tt k-1

[0121] T k =t k -t k-1 (17)

[0122] Among them, T k refers to the total duration of the kth time interval, τ k Refers to a specific time in a time interval.

[0123] By combining the above formula (12) to the above formula (17), the above formula (11) can be derived.

[0124] Specifically, the above change restriction information can be expressed in the above running state model according to the following formula (18):

[0125] V next sinθ>=V now -0.06a max

[0126] V next cosθ<0.06a max

[0127] V next <V max (18)

[0128] Among them, 0.06 represents a constant, which can be determined according to the operating cycle configured by the smart device. next Refers to the speed calculated based on the running state model, that is, the second speed, v now It refers to the speed of the corresponding relationship between speed and time in the input running state model, that is, the first speed, and θ refers to v next and v now The angle between them, v max It refers to the maximum speed.

[0129] Combining formula (7) and formula (18), formula (19) representing the above change restriction information can be derived:

[0130]

[0131] V next <V max (19)

[0133] Combining formula (9) and formula (17), it can be seen that when the mass of the object carried by the smart device is known, the running state model can be combined to control the running state model to run smoothly.

[0134] In some optional embodiments, the above-mentioned operating status model is configured with at least one corresponding relationship between speed and time.

[0135] Based on this, the process of determining the second speed of the smart device at the next moment based on the first speed of the smart device at the current moment and the operating status model may include: determining the target correspondence relationship from the multiple correspondences between speed and time configured by the operating status model based on the first speed of the smart device at the current moment; determining the second speed of the smart device at the next moment based on the first speed of the smart device at the current moment and the target correspondence relationship.

[0136] The target corresponding relationship is used to indicate that the operating state model is configured with at least one corresponding relationship between speed and time, which is used to calculate the corresponding relationship of the second speed.

[0137] In some optional embodiments, the smart device control method may further include: if the speed direction of the first speed is the same as the speed direction of the second speed, controlling the smart device to load the object to run according to the second speed.

[0138] Specifically, the speed direction of the first speed is the same as the speed direction of the second speed, indicating that the driving state of the smart device is straight-line driving. The smart device can be directly controlled to carry the object according to the second speed determined by the above formula (11).

[0139] In some optional embodiments, the process of controlling the operation of the object loaded by the smart device based on the operating status model, the change limit information, the first speed and the second speed includes: determining the angle value between the speed direction of the first speed and the speed direction of the second speed; determining the speed value range for limiting the second speed according to the angle value, the first speed, the operating status model and the change limit information; and controlling the operation of the object loaded by the smart device based on the second speed and the speed value range.

[0140] Specifically, the above speed value range can be a value range determined based on the above formula (19).

[0141] In some optional embodiments, the speed value range includes a maximum speed value and a minimum speed value, and the maximum speed value is not greater than the maximum operating speed of the smart device.

[0142] Based on this, the above process of controlling the operation of the object loaded by the smart device based on the second speed and the speed value range may include: if the second speed is less than the minimum speed, controlling the operation of the object loaded by the smart device according to the minimum speed; if the second speed is greater than the maximum speed, controlling the operation of the object loaded by the smart device according to the maximum speed; if the second speed falls within the speed value range, controlling the operation of the object loaded by the smart device according to the second speed.

[0143] In some optional embodiments, the process of controlling the smart device to carry the object for operation based on the target motion parameters and the change restriction information may include: determining the operation path of the smart device; generating operation status information of multiple position points of the operation path based on the operation path, the target motion parameters and the change restriction information; generating operation control information based on the operation status information of multiple position points of the operation path; and controlling the smart device to carry the object for operation according to the operation path based on the operation control information.

[0144] Among them, the running path of the smart device can be a global path, and the running path of the smart device can also be a local path. The specific path can be adjusted according to actual conditions, and the embodiments of the present application do not limit it.

[0145] Among them, the operating status information includes the posture information of the smart device corresponding to the location point on the map, the location information of the location point on the map, the posture information of the smart device corresponding to the location point, the maximum acceleration of the smart device when it loads the object, and the maximum speed of the smart device.

[0146] The operation control information refers to information such as instructions or tasks used to control the smart device to carry the object to operate according to the operation path.

[0147] In some optional embodiments, the above-mentioned process of generating the running status information of multiple position points of the running path based on the running path, the target motion parameters and the change restriction information may include: if local path planning is required, determining the starting position point and the ending position point of the target local path to be generated from the running path; determining the target local path according to the starting position point and the ending position point; generating the running status information of multiple position points of the target local path according to the target local path, the target motion parameters and the change restriction information.

[0148] The situation where local path planning is required can be adjusted according to the actual situation, and the embodiments of the present application do not limit it. For example, when the smart device runs according to the running path, if an obstacle is detected on the running path, local path planning is required. For another example, when a local path planning instruction is received from an industrial computer, local path planning is required.

[0149] Specifically, see Figure 5 , Figure 5 This is a schematic diagram of a scenario where local path planning is required for this application, where S represents the starting point, G represents the ending point, and the black part is an obstacle. The starting point and the ending point are combined to determine the target local path. Combined with the operation status model, the planned operation time, and the operation cycle, the number of location points on the target local path and the operation status information of each location point can be determined. For example, refer to Figure 6 The 2000 position points shown in the figure, as well as the running status information of each position point, where the left side is the acceleration process, the middle is the uniform speed process, and the right side is the deceleration process. The 2000 position points obtained above are substituted into the target local path, and the entire target local path is divided into 2000 points. The running status information (x, y, theta, a) of each position point is determined. max , v max ). Among them, theta is used to indicate the posture information (such as angle, position information) of the smart device itself.

[0150] In some optional embodiments, the process of determining the target local path based on the starting position point and the ending position point may include: obtaining constraint parameters, the constraint parameters including at least one of the angle difference between the starting position point and the ending position point, the distance between the starting position point and the obstacle on the running path, and the speed difference between the starting position point and the ending position point; determining the target local path based on the constraint parameters, the starting position point and the ending position point, the target local path not including the obstacle.

[0151] Furthermore, the weight of the constraint parameter may be determined, and based on the constraint parameter, the weight of the constraint parameter, the starting position point and the ending position point, a target local path is determined, wherein the target local path does not include the obstacle.

[0152] For example, Figure 7 As stated, Figure 7 The green part in is all possible operation conditions under the change restriction information determined based on the above formula (19). From all these possible operation conditions, combined with the trajectory evaluation function, we can select Figure 8 The target partial path is shown.

[0153] The trajectory evaluation function can be expressed as follows:

[0154] G(v, theta)=α*heading(v, theta)+β*dist(v, theta)+γ*velocity(v, theta) (20)

[0155] Among them, α, β, and γ are the weights of the constraint parameters, heading(v, theta) refers to the angle evaluation function, which is used to determine the angle difference between the starting position point and the ending position point, dist(v, theta) is used to determine the distance between the starting position point and the obstacle on the running path, velocity(v, theta) is used to determine the speed difference between the starting position point and the ending position point, and G(v, theta) is the evaluation value. The target local path is determined according to the evaluation values ​​of different local paths.

[0156] In some optional embodiments, there are multiple ways to obtain the target mass of the load object required by the smart device.

[0157] For example, when the smart device is equipped with a lifting device, and the lifting device loads the object, the process of obtaining the target mass of the object that the smart device needs to load may include: determining the force value of the lifting device in the vertical direction, and the first distance between the lifting device and a preset fulcrum; determining the second distance between the center of gravity of the object carried by the smart device and the preset fulcrum; and determining the target mass of the object based on the force value, the first distance, the second distance, and the acceleration of gravity.

[0158] It should be noted that the above content can be adjusted according to actual conditions and this application does not impose any restrictions.

[0159] Exemplarily, assume that the smart device is a forklift-type guided vehicle, equipped with a fork and a binocular depth camera. The focal length of the binocular depth camera, the distance between the two cameras, and two reference points on the actual object can be used to determine the distance of the actual object from the camera and the length of the actual object. Combined with the length of the actual object, the starting distance of the actual object on the fork of the forklift-type guided vehicle, and the length of the pallet on which the actual object is located, the center of gravity of the actual object on the fork is determined. Combined with the center of gravity of the actual object on the fork and the principle of leverage, the mass of the actual object can be determined. The formula is relatively existing and will not be repeated here.

[0160] In some optional embodiments, the target mass includes an actual mass; the process of determining the target mass of the object based on the force value, the first distance, the second distance, and the gravitational acceleration may include: obtaining a mass error value; determining a theoretical mass of the object based on the force value, the first distance, the second distance, and the gravitational acceleration; and determining the actual mass of the object based on the theoretical mass and the mass error value.

[0161] In order to better implement the intelligent device control method provided in the embodiment of the present application, the embodiment of the present application also provides a device based on the above intelligent device control method. The meanings of the terms are the same as those in the above intelligent device control method, and the specific implementation details can refer to the description in the method embodiment.

[0162] For example, Fig. 9 As shown, the intelligent device control apparatus may include a target quality acquisition unit 201, a change restriction information determination unit 202 and a control unit 203, as follows:

[0163] A target mass acquisition unit 201 is used to acquire a target mass of a load object required by the smart device;

[0164] A change restriction information determining unit 202, configured to determine change restriction information of a target motion parameter of the smart device according to the target quality;

[0165] The control unit 203 is used to control the operation of the object loaded by the smart device according to the target motion parameters and the change restriction information.

[0166] In an embodiment of the present application, the change restriction information determining unit 202 includes:

[0167] A maximum acceleration determination subunit, used to determine the maximum acceleration of the intelligent device when it meets the stable operation condition according to the target quality;

[0168] The change limit information determination subunit is used to determine the change limit information of the target motion parameter of the smart device according to the maximum acceleration.

[0169] In one embodiment of the present application, the above-mentioned stable operation condition includes that the resultant force acting on the object is not greater than the sliding friction acting on the object.

[0170] Based on this, the maximum acceleration determination subunit includes:

[0171] A resultant force determination module, used to determine the resultant force on the object according to the acceleration and target mass when the smart device is loading the object;

[0172] A sliding friction force determination module is used to determine the sliding friction force on the object according to the pressure on the object and the dynamic friction coefficient;

[0173] The maximum acceleration determination module is used to determine the acceleration when the resultant force on the object is equal to the sliding friction force on the object, and use the acceleration as the maximum acceleration when the intelligent device meets the stable operation conditions.

[0174] In one embodiment of the present application, the sliding friction force determination module includes:

[0175] The influencing factor acquisition submodule is used to obtain the influencing factors of the pressure on the object and the influencing coefficients of the influencing factors;

[0176] An actual pressure determination submodule, used to determine the actual pressure exerted on the object based on the influencing factors, the influencing coefficients of the influencing factors, the target mass and the gravitational acceleration;

[0177] The sliding friction force determination submodule is used to determine the sliding friction force exerted on the object based on the actual pressure exerted on the object and the dynamic friction coefficient.

[0178] In one embodiment of the present application, the target motion parameter includes the speed of the smart device.

[0179] Based on this, the control unit 203 includes:

[0180] A second speed determination subunit, used to determine a second speed of the smart device at a next moment according to the first speed of the smart device at a current moment and the operation state model;

[0181] The first operation control subunit is used to control the operation of the object loaded by the intelligent device based on the operation state model, the change restriction information, the first speed and the second speed if the speed direction of the first speed is different from the speed direction of the second speed.

[0182] In one embodiment of the present application, the above-mentioned operating status model is configured with at least one corresponding relationship between speed and time.

[0183] Based on this, the second speed determination subunit includes:

[0184] A target correspondence determination module, configured to determine a target correspondence from a plurality of correspondences between speed and time configured by the running state model according to a first speed of the smart device at a current moment;

[0185] The second speed determination module is used to determine the second speed of the smart device at the next moment according to the first speed of the smart device at the current moment and the target corresponding relationship.

[0186] In one embodiment of the present application, the above-mentioned intelligent device control device further includes:

[0187] The second operation control subunit is used to control the operation of the object loaded by the intelligent device according to the second speed if the speed direction of the first speed is the same as the speed direction of the second speed.

[0188] In one embodiment of the present application, the first operation control subunit includes:

[0189] An angle value determination module, used to determine an angle value between a speed direction of the first speed and a speed direction of the second speed;

[0190] The speed value range module is used to determine the speed value range for limiting the second speed according to the angle value, the first speed, the operating state model and the change limit information.

[0191] The control module is used to control the operation of the object loaded by the intelligent device based on the second speed and the speed value range.

[0192] In one embodiment of the present application, the above-mentioned speed value range includes a maximum speed value and a minimum speed value, and the maximum speed value is not greater than the maximum operating speed of the smart device.

[0193] Based on this, the above control module includes:

[0194] A first control submodule, configured to control the operation of the object loaded by the smart device according to the minimum speed value if the second speed is less than the minimum speed value;

[0195] A second control submodule is used to control the operation of the object loaded by the smart device according to the maximum speed if the second speed is greater than the maximum speed;

[0196] The third control submodule is used to control the operation of the object loaded by the intelligent device according to the second speed if the second speed falls within the speed value range.

[0197] In one embodiment of the present application, the control unit 203 includes:

[0198] An operation path determination subunit, used to determine the operation path of the smart device;

[0199] An operation status information determination subunit, for generating operation status information of a plurality of position points of the operation path based on the operation path, the target motion parameter and the change restriction information;

[0200] An operation control information generating subunit, used for generating operation control information based on the operation status information of a plurality of position points of the operation path;

[0201] The second control subunit is used to control the intelligent device to carry the object according to the operation path based on the operation control information.

[0202] In one embodiment of the present application, the above-mentioned operation status information determination subunit includes:

[0203] A position point determination module is used to determine the starting position point and the ending position point of the target local path to be generated from the running path if local path planning is required;

[0204] A target local path determination module is used to determine the target local path according to the starting position point and the ending position point;

[0205] The operation status information determination module is used to generate the operation status information of multiple position points of the target local path according to the target local path, the target motion parameters and the change restriction information.

[0206] In one embodiment of the present application, the target local path determination module includes:

[0207] A constraint parameter acquisition submodule is used to acquire constraint parameters, wherein the constraint parameters include at least one of an angle difference between a starting position point and an ending position point, a distance between a starting position point and an obstacle on a running path, and a speed difference between a starting position point and an ending position point;

[0208] The target local path determination submodule is used to determine the target local path according to the constraint parameters, the starting position point and the ending position point, and the target local path does not include obstacles.

[0209] In one embodiment of the present application, the above-mentioned smart device is equipped with a lifting device, and the above-mentioned lifting device carries an object.

[0210] Based on this, the target quality acquisition unit 201 includes:

[0211] A first distance determination subunit, used to determine a force value of the jacking device in a vertical direction and a first distance between the jacking device and a preset fulcrum;

[0212] A second distance determination subunit, used to determine a second distance between the center of gravity of the object carried by the smart device and a preset fulcrum;

[0213] The target mass determination subunit is used to determine the target mass of the object according to the force value, the first distance, the second distance and the gravitational acceleration.

[0214] In an embodiment of the present application, the target mass includes the actual mass.

[0215] Based on this, the above target quality determination subunit includes:

[0216] A mass error value acquisition module, used to acquire a mass error value;

[0217] A theoretical mass determination module, used to determine the theoretical mass of the object according to the force value, the first distance, the second distance, and the gravitational acceleration;

[0218] The actual mass determination module is used to determine the actual mass of the object according to the theoretical mass and the mass error value.

[0219] In one embodiment of the present application, the above-mentioned intelligent device includes at least one of a guided vehicle and an intelligent mechanical device.

[0220] It can be seen that the intelligent device control device provided in the embodiment of the present application obtains the target mass of the object required to be loaded by the intelligent device through the target mass acquisition unit 201; the change restriction information determination unit 202 determines the change restriction information of the target motion parameters of the intelligent device according to the target mass; the control unit 203 controls the operation of the object loaded by the intelligent device according to the target motion parameters and the change restriction information. In this way, by combining the mass of the object loaded by the intelligent device, the change restriction conditions of the target motion parameters of the intelligent device are determined, so that when controlling the operation of the object loaded by the intelligent device, the change restriction conditions of the target motion parameters of the intelligent device can be dynamically adjusted according to the different masses of the objects loaded by the intelligent device, so as to improve the stability of the operation of the intelligent device.

[0221] In specific implementation, the above modules can be implemented as independent entities, or can be arbitrarily combined and implemented as the same or several entities. The specific implementation methods and corresponding beneficial effects of the above modules can be found in the previous method embodiments, which will not be repeated here.

[0222] The present application also provides a control device, such as Fig.10 As shown, it shows a schematic diagram of the structure of the control device involved in the embodiment of the present application, specifically:

[0223] The control device may include one or more processing core processors 301, one or more storage media memories 302, a power supply 303, an input unit 304 and other components. Those skilled in the art will appreciate that Fig.10 The control device structure shown in the figure does not constitute a limitation on the control device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0224] in:

[0225] The processor 301 is the control center of the control device, and uses various interfaces and lines to connect various parts of the entire control device. By running or executing computer programs and / or modules stored in the memory 302, and calling data stored in the memory 302, the processor 301 performs various functions of the control device and processes data. Optionally, the processor 301 may include one or more processing cores; preferably, the processor 301 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 301.

[0226] The memory 302 can be used to store computer programs and modules. The processor 301 executes various functional applications and security controls by running the computer programs and modules stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, a computer program required for at least one function (such as a sound playback function, a navigation function, etc.), etc.; the data storage area may store data created according to the use of the control device, etc. In addition, the memory 302 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.

[0227] The control device also includes a power supply 303 for supplying power to each component. Preferably, the power supply 303 can be logically connected to the processor 301 through a power management system, so as to manage charging, discharging, and power consumption through the power management system. The power supply 303 can also include any components such as one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, and power status indicators.

[0228] The control device may further include an input unit 304, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0229] Although not shown, the control device may further include a display unit, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 301 in the control device will load the executable files corresponding to the processes of one or more computer programs into the memory 302 according to the following instructions, and the processor 301 will run the computer programs stored in the memory 302, thereby realizing various functions, such as:

[0230] Obtain the target mass of the load object required by the smart device;

[0231] Determine the change limit information of the target motion parameters of the smart device according to the target quality;

[0232] According to the target motion parameters and change restriction information, the operation of the object loaded by the intelligent device is controlled.

[0233] It can be seen that the smart device provided in the embodiment of the present application obtains the target mass of the object to be loaded by the smart device; determines the change restriction information of the target motion parameters of the smart device according to the target mass; and controls the operation of the object loaded by the smart device according to the target motion parameters and the change restriction information. In this way, by combining the mass of the object loaded by the smart device, the change restriction conditions of the target motion parameters of the smart device are determined, so that when controlling the operation of the object loaded by the smart device, the change restriction conditions of the target motion parameters of the smart device can be dynamically adjusted according to the different masses of the objects loaded by the smart device, so as to improve the stability of the operation of the smart device.

[0234] The specific implementation methods and corresponding beneficial effects of the above operations can be found in the detailed description of the smart device control method above, which will not be elaborated here.

[0235] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be accomplished by a computer program, or by controlling related hardware through a computer program. The computer program may be stored in a storage medium and loaded and executed by a processor.

[0236] To this end, an embodiment of the present application provides a storage medium in which a computer program is stored, and the computer program can be loaded by a processor to execute the steps in any smart device control method provided in the embodiment of the present application. For example, the computer program can execute the following steps:

[0237] Obtain the target mass of the load object required by the smart device;

[0238] Determine the change limit information of the target motion parameters of the smart device according to the target quality;

[0239] According to the target motion parameters and change restriction information, the operation of the object loaded by the intelligent device is controlled.

[0240] It can be seen that the storage medium provided in the embodiment of the present application obtains the target mass of the object to be loaded by the smart device; determines the change restriction information of the target motion parameters of the smart device according to the target mass; and controls the operation of the object loaded by the smart device according to the target motion parameters and the change restriction information. In this way, by combining the mass of the object loaded by the smart device, the change restriction conditions of the target motion parameters of the smart device are determined, so that when controlling the operation of the object loaded by the smart device, the change restriction conditions of the target motion parameters of the smart device can be dynamically adjusted according to the different masses of the objects loaded by the smart device, so as to improve the stability of the operation of the smart device.

[0241] The specific implementation methods and corresponding beneficial effects of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0242] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0243] Since the computer program stored in the storage medium can execute the steps in any one of the smart device control methods provided in the embodiments of the present application, the beneficial effects that can be achieved by any one of the smart device control methods provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0244] According to one aspect of the present application, a computer program product or a computer program is provided, the computer program product or the computer program includes computer instructions, and the computer instructions are stored in a storage medium. A processor of a computer device reads the computer instructions from the storage medium, and the processor executes the computer instructions, so that the computer device executes the above-mentioned intelligent device control method.

[0245] The above is a detailed introduction to an intelligent device control method, device, storage medium and control device provided in the embodiments of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, according to the ideas of the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for controlling an intelligent device, characterized in that: The method comprises: Obtain the target mass of the load object required by the smart device; Determining, according to the target mass, change restriction information of the target motion parameter of the smart device; According to the target motion parameter and the change restriction information, the smart device is controlled to carry the object to run.

2. The intelligent device control method according to claim 1, characterized in that: The step of determining the change restriction information of the target motion parameter of the smart device according to the target mass includes: Determining, according to the target mass, a maximum acceleration of the smart device when it meets a stable operation condition; According to the maximum acceleration, change limit information of the target motion parameter of the smart device is determined.

3. The intelligent device control method according to claim 2, characterized in that: The stable operation condition includes that the resultant force on the object is not greater than the sliding friction on the object; and determining the maximum acceleration of the smart device when the stable operation condition is met according to the target mass includes: Determine the resultant force on the object according to the acceleration of the smart device when the object is loaded and the target mass; Determining the sliding friction force exerted on the object according to the pressure exerted on the object and the dynamic friction coefficient; The acceleration when the resultant force acting on the object is equal to the sliding friction force acting on the object is determined, and the acceleration is used as the maximum acceleration when the smart device meets the stable operation condition.

4. The intelligent device control method according to claim 3, characterized in that: Determining the sliding friction force exerted on the object according to the pressure exerted on the object and the dynamic friction coefficient includes: Obtaining an influencing factor of the pressure on the object and an influencing coefficient of the influencing factor; Determining the actual pressure on the object based on the influencing factor, the influencing coefficient of the influencing factor, the target mass and the gravitational acceleration; The sliding friction force experienced by the object is determined based on the actual pressure experienced by the object and the dynamic friction coefficient.

5. The intelligent device control method according to claim 1, characterized in that: The target motion parameter includes the speed of the smart device, and controlling the smart device to carry the object to run according to the target motion parameter and the change restriction information includes: Determine a second speed of the smart device at a next moment according to the first speed of the smart device at a current moment and the operation state model; If the speed direction of the first speed is different from the speed direction of the second speed, the smart device is controlled to load the object to run based on the running state model, the change restriction information, the first speed, and the second speed.

6. The intelligent device control method according to claim 5, characterized in that: The running state model is configured with at least one corresponding relationship between speed and time; and determining the second speed of the smart device at a next moment according to the first speed of the smart device at a current moment and the running state model includes: According to the first speed of the smart device at the current moment, determining a target corresponding relationship from a plurality of corresponding relationships between speed and time configured in the running state model; A second speed of the smart device at a next moment is determined according to the first speed of the smart device at a current moment and the target corresponding relationship.

7. The intelligent device control method according to claim 5, characterized in that: The method further comprises: If the speed direction of the first speed is the same as the speed direction of the second speed, the smart device is controlled to carry the object according to the second speed.

8. The intelligent device control method according to claim 5, characterized in that: The controlling the smart device to load the object to run based on the running state model, the change limit information, the first speed, and the second speed includes: determining an angle value between a speed direction of the first speed and a speed direction of the second speed; Determine a speed value range for limiting the second speed according to the angle value, the first speed, the operating state model, and the change limit information; Based on the second speed and the speed value range, the smart device is controlled to carry the object to run.

9. The intelligent device control method according to claim 8, characterized in that: The speed value range includes a maximum speed value and a minimum speed value, and the maximum speed value is not greater than the maximum operating speed of the smart device; and based on the second speed and the speed value range, controlling the smart device to load the object to operate, includes: If the second speed is less than the minimum speed value, controlling the smart device to carry the object to run according to the minimum speed value; If the second speed is greater than the maximum speed, controlling the smart device to carry the object to run according to the maximum speed; If the second speed falls within the speed value range, the smart device is controlled to carry the object to run according to the second speed.

10. The intelligent device control method according to claim 1, characterized in that: The step of controlling the smart device to carry the object to run according to the target motion parameter and the change restriction information includes: Determining an operation path of the smart device; Based on the running path, the target motion parameter and the change restriction information, generating running state information of a plurality of position points of the running path; generating operation control information based on the operation status information of the plurality of position points of the operation path; Based on the operation control information, the smart device is controlled to load the object and operate according to the operation path.

11. The intelligent device control method according to claim 10, characterized in that: The step of generating the running status information of a plurality of position points of the running path based on the running path, the target motion parameter and the change restriction information includes: If local path planning is required, the starting point and the ending point of the target local path to be generated are determined from the running path; Determine a target local path according to the starting position point and the ending position point; The running state information of a plurality of position points of the target partial path is generated according to the target partial path, the target motion parameter and the change restriction information.

12. The intelligent device control method according to claim 11, characterized in that: The determining of the target local path according to the starting position point and the ending position point includes: Obtaining constraint parameters, wherein the constraint parameters include at least one of an angle difference between the starting position point and the ending position point, a distance between the starting position point and an obstacle on the running path, and a speed difference between the starting position point and the ending position point; A target partial path is determined according to the constraint parameters, the starting position point and the ending position point, and the target partial path does not include the obstacle.

13. The intelligent device control method according to any one of claims 1 to 12, characterized in that: The smart device is equipped with a lifting device, and the lifting device carries the object. The step of obtaining the target mass of the object required to be loaded by the smart device includes: Determine the force value of the jacking device in the vertical direction and the first distance between the jacking device and a preset fulcrum; Determining a second distance between the center of gravity of the object carried by the smart device and the preset fulcrum; The target mass of the object is determined according to the force value, the first distance, the second distance, and the gravitational acceleration.

14. The intelligent device control method according to claim 13, characterized in that: The target quality includes the actual quality; The determining the target mass of the object according to the force value, the first distance, the second distance, and the gravitational acceleration includes: Get the mass error value; Determining a theoretical mass of the object according to the force value, the first distance, the second distance, and gravitational acceleration; The actual mass of the object is determined according to the theoretical mass and the mass error value.

15. The intelligent device control method according to any one of claims 1 to 12, characterized in that: The intelligent device includes at least one of a guided vehicle and an intelligent mechanical device.

16. A smart device control device, characterized in that: The device comprises: A target mass acquisition unit, used to acquire the target mass of the load object required by the intelligent device; a change restriction information determining unit, configured to determine change restriction information of a target motion parameter of the smart device according to the target mass; A control unit is used to control the operation of the smart device carrying the object according to the target motion parameter and the change restriction information.

17. A storage medium, characterized in that: The invention comprises a computer program, and when the computer program is run on a processor, the computer program is used to make the processor execute the steps of the intelligent device control method according to any one of claims 1 to 15.

18. A computer program product, characterized in that The method comprises a computer program or an instruction, which, when executed by a processor, implements the steps of the intelligent device control method according to any one of claims 1 to 15.

19. A control device, characterized in that: The invention comprises one or more processors and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the intelligent device control method according to any one of claims 1 to 15.

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