A method and system for adaptive adjustment of gripping force of a bionic hand, a terminal and a medium

Abstract

This invention discloses a method, system, terminal, and medium for adaptive adjustment of gripping force in a bionic hand, relating to the field of bionic hand technology. The method includes: receiving a gripping command; monitoring force information at the fingertips of the bionic hand; and determining whether the bionic hand is in contact with a target object based on the force information; after the bionic hand contacts the target object, acquiring information on the hardness or softness of the target object, and acquiring an initial gripping force based on the hardness or softness information; gripping the target object based on the initial gripping force, and monitoring preset influencing factor information in real time during the gripping process, and adaptively adjusting the gripping force of the bionic hand based on the influencing factor information, wherein the influencing factor information reflects factors that affect the gripping effect of the bionic hand. This invention can dynamically adjust the gripping force during the gripping process, which is beneficial for maintaining gripping stability under different influencing factor information.

Description

Technical Field

[0001] This invention relates to the field of bionic hand technology, and in particular to a method, system, terminal, and medium for adaptive adjustment of gripping force in a bionic hand. Background Technology

[0002] With the development of bionic robotics technology, bionic hands, as key components in human-computer interaction and assisted movement, are increasingly being used in fields such as prostheses, service robots, and industrial grasping. In practical applications, bionic hands face complex grasping objects and variable operating environments. Traditional bionic hands often use preset action sequences or constant grasping force to complete grasping tasks, lacking the ability to perceive the state of the grasped object in real time, resulting in poor grasping stability and a tendency to fail to grasp or damage the object.

[0003] Therefore, existing technologies still have shortcomings. Summary of the Invention

[0004] The technical problem to be solved by this invention is to provide a method, system, terminal, and medium for adaptive adjustment of gripping force in a bionic hand, addressing the aforementioned deficiencies of the prior art. The technical solution adopted by this invention is as follows:

[0005] In a first aspect, the present invention provides a method for adaptive adjustment of gripping force in a bionic hand, wherein the method includes:

[0006] It receives grasping commands, monitors the force information at the fingertips of the bionic hand, and determines whether the bionic hand is in contact with the target object based on the force information.

[0007] When the bionic hand comes into contact with the target object, it acquires information about the softness or hardness of the target object and obtains an initial gripping force based on the information about the softness or hardness.

[0008] The bionic hand grasps the target object based on the initial gripping force, and monitors preset influencing factor information in real time during the grasping process. Based on the influencing factor information, the gripping force of the bionic hand is adaptively adjusted. The influencing factor information reflects the factors that affect the gripping effect of the bionic hand.

[0009] In one implementation, monitoring the force information at the fingertips of the bionic hand and determining whether the bionic hand is in contact with a target object based on the force information includes:

[0010] The force information is obtained by monitoring the normal and tangential forces at the fingertips of the bionic hand using tactile sensors.

[0011] If the normal force is greater than or equal to a preset threshold, it is determined that the bionic hand is in contact with the target object.

[0012] In one implementation, after the bionic hand comes into contact with the target object, information on the hardness or softness of the target object is acquired, including:

[0013] When the bionic hand comes into contact with the target object, it monitors the change information of the normal force in real time within a preset time period to determine the rate of change of the normal force.

[0014] Based on the rate of change, the hardness or softness information of the target object is determined.

[0015] In one implementation, after the bionic hand comes into contact with the target object, information on the hardness or softness of the target object is acquired, including:

[0016] At the instant the bionic hand makes contact with the target object, the deformation information of the contact area between the bionic hand and the target object is obtained;

[0017] Based on the deformation information, the hardness or softness of the target object is determined.

[0018] In one implementation, preset influencing factor information is monitored in real time during the grasping process, including:

[0019] During the grasping process, information on the change in the grasping position between the bionic hand and the target object is acquired;

[0020] During the grasping process, the movement speed information of the bionic hand is acquired;

[0021] During the grasping process, information on the electrical changes of the bionic hand is acquired;

[0022] The information on changes in gripping position, movement speed, and current change is used as the influencing factor information.

[0023] In one implementation, adaptively adjusting the gripping force of the bionic hand based on the influencing factor information includes:

[0024] The weight information corresponding to the grip position change information, movement speed information, and current change information is obtained respectively;

[0025] Based on the weight information, the gripping stability of the bionic hand is determined;

[0026] If the gripping stability is insufficient, the gripping force of the bionic hand is increased.

[0027] In one implementation, the method further includes:

[0028] If the bionic hand moves the target object to the target position, it receives a release command and controls the bionic hand to gradually reduce the gripping force until the gripping force is 0.

[0029] Secondly, embodiments of the present invention also provide a bionic hand grip force adaptive adjustment system, wherein the system is used to implement the steps of the bionic hand grip force adaptive adjustment method described above, and the system includes:

[0030] The contact judgment module is used to receive grasping commands, monitor the force information of the fingertips of the bionic hand, and determine whether the bionic hand is in contact with the target object based on the force information.

[0031] The soft-hardness analysis module is used to obtain the soft-hardness information of the target object after the bionic hand comes into contact with the target object, and to obtain the initial gripping force based on the soft-hardness information;

[0032] The gripping force adjustment module is used to grip the target object based on the initial gripping force, and to monitor preset influencing factor information in real time during the gripping process, and to adaptively adjust the gripping force of the bionic hand based on the influencing factor information. The influencing factor information reflects the factors that affect the gripping effect of the bionic hand.

[0033] Thirdly, embodiments of the present invention also provide a terminal, wherein the terminal includes a memory, a processor, and a bionic hand grip force adaptive adjustment program stored in the memory and executable on the processor. When the processor executes the bionic hand grip force adaptive adjustment program, it implements the steps of the bionic hand grip force adaptive adjustment method of any of the above solutions.

[0034] Fourthly, embodiments of the present invention also provide a computer-readable storage medium, wherein the computer-readable storage medium stores a gripping force adaptive adjustment program for a bionic hand, the gripping force adaptive adjustment program for the bionic hand implementing the steps of the gripping force adaptive adjustment method for the bionic hand as described in any of the above-described schemes on the computer-readable storage medium.

[0035] Beneficial Effects: Compared with existing technologies, this invention provides a method for adaptively adjusting the gripping force of a bionic hand. First, the invention receives a gripping command, monitors the force information at the fingertips of the bionic hand, and determines whether the bionic hand is in contact with a target object based on this force information. Once the bionic hand contacts the target object, it acquires the object's hardness / softness information and obtains an initial gripping force based on this information. Finally, the bionic hand grasps the target object based on the initial gripping force, and during the grasping process, it monitors preset influencing factors in real time and adaptively adjusts the gripping force of the bionic hand based on these influencing factors. These influencing factors reflect factors that affect the gripping effect of the bionic hand. This invention can adjust the gripping force of the bionic hand in real time based on different influencing factors, which helps maintain good gripping stability throughout the entire grasping process and avoids problems such as grasping failure or damage to the object. Attached Figure Description

[0036] Figure 1 A flowchart of a preferred embodiment of the bionic hand grip force adaptive adjustment method provided in this invention.

[0037] Figure 2 This is a schematic diagram of the bionic hand grip force adaptive adjustment system provided in an embodiment of the present invention.

[0038] Figure 3 A schematic diagram of a terminal provided in an embodiment of the present invention. Detailed Implementation

[0039] To make the objectives, technical solutions, and effects of this invention clearer and more explicit, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0040] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content, operations, or steps, nor does it require execution in the described order. For example, some operations or steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0041] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0042] It should be understood that, in order to clearly describe the technical solutions of the embodiments of the present invention, the terms "first" and "second" are used in the embodiments of the present invention to distinguish identical or similar items with essentially the same function and effect. For example, the first control information and the second control information are only used to distinguish different control information and do not limit their order.

[0043] Those skilled in the art will understand that the words "first" and "second" do not limit the quantity or the order of execution, and that the words "first" and "second" do not necessarily imply that they are different.

[0044] It should also be understood that the terms "and / or" as used in this specification and the appended claims refer to any combination of one or more of the associated listed items and all possible combinations, and include such combinations.

[0045] To address the problems of existing technologies, this embodiment provides a method for adaptive adjustment of the gripping force of a bionic hand. This method can handle different influencing factors and adjust the gripping force in real time throughout the gripping process to ensure gripping effectiveness. In specific applications, this embodiment first receives a gripping command, monitors the force information at the fingertips of the bionic hand, and determines whether the bionic hand is in contact with a target object based on this force information. When the bionic hand contacts the target object, it acquires the hardness / softness information of the target object and obtains an initial gripping force based on this information. Finally, it grips the target object based on the initial gripping force, and monitors preset influencing factor information in real time during the gripping process, adaptively adjusting the gripping force of the bionic hand based on this influencing factor information. The influencing factor information reflects factors that affect the gripping effect of the bionic hand.

[0046] The bionic hand grip force adaptive adjustment method of this embodiment can be applied to terminals, such as computers, smart TVs, and mobile phones. In practical applications, the bionic hand grip force adaptive adjustment method of this embodiment can also be applied to bionic hands, which are intelligent products capable of data acquisition, data analysis, and action execution. Figure 1 As shown, the bionic hand's grip force adaptive adjustment method includes the following steps:

[0047] Step S100: Receive a grasping command, monitor the force information of the fingertips of the bionic hand, and determine whether the bionic hand is in contact with the target object based on the force information.

[0048] The host computer or system can first issue a grasping command to the bionic hand in this embodiment. After receiving the grasping command, the bionic hand initiates a preparation process for the grasping action, including waking up the finger joints of the bionic hand and adjusting the grasping direction of the bionic hand towards the target object. It can also initially adjust the grip posture of the finger joints. For example, if the target object is on the left, the grasping direction of the bionic hand can be adjusted to face the left, and the finger joints of the bionic hand can be in a semi-grip state to facilitate grasping. Next, this embodiment begins to monitor the force information at the fingertips of the bionic hand, analyzes the force information, and determines whether the fingertips of the bionic hand are in contact with the target object based on changes in the force information.

[0049] In one implementation, this embodiment includes the following steps when determining whether the fingertip is in contact with the target object:

[0050] Step S101: Based on the tactile sensor, monitor the normal force and tangential force at the fingertips of the bionic hand to obtain the force information;

[0051] Step S102: If the normal force is greater than or equal to a preset threshold, determine that the bionic hand is in contact with the target object.

[0052] Specifically, the bionic hand in this embodiment is equipped with a tactile sensor, which can detect the force information at the tip of the bionic finger. This force information includes normal force and tangential force. The normal force is the force perpendicular to the contact point between the fingertip and the target object, and the tangential force is the force parallel to the contact point between the fingertip and the target object. Next, this embodiment compares the normal force with a preset threshold. If the normal force is greater than or equal to the preset threshold, it is determined that the bionic hand is in contact with the target object.

[0053] In practical applications, when a bionic hand grasps a target object, it's not necessarily the fingertips that make initial contact; other parts of the hand may also do so. Therefore, in other implementations, this embodiment can also collect force information from other parts of the bionic hand, such as the palm, using a tactile sensor. The tactile sensor detects the normal and tangential forces on the palm, and when the normal force is greater than or equal to a preset threshold, it's determined that the bionic hand has made contact with the target object. This allows for multi-faceted assessment of contact, improving accuracy. The tactile sensor in this embodiment can be a strain gauge sensor, a capacitive tactile sensor, or a piezoresistive tactile sensor. Capacitive tactile sensors detect touch, pressure, or force by varying the distance between capacitor plates, while piezoresistive tactile sensors sense external pressure or force by detecting changes in the resistance of a piezoresistive resistor. This embodiment is not limited to either type.

[0054] Step S200: When the bionic hand comes into contact with the target object, it obtains the softness and hardness information of the target object and obtains the initial gripping force based on the softness and hardness information.

[0055] Once the bionic hand makes contact with the target object, this embodiment begins detecting the object's hardness / softness information. This information reflects whether the object's material is relatively soft or hard. If the object is relatively hard, the bionic hand can use a larger gripping force to ensure a good grip. Conversely, if the object is relatively soft, the bionic hand can use a smaller gripping force to avoid damaging the object. Therefore, after analyzing the object's hardness / softness information, this embodiment can obtain a corresponding initial gripping force. The initial gripping force in this embodiment is pre-set to correspond to the hardness / softness information. In practical applications, a gripping force reference table can be set, which lists the gripping forces corresponding to different levels of hardness / softness. Specifically, the hardness / softness information can be categorized into levels; for example, a level 1 hardness corresponds to a gripping force of A, and a level 2 hardness corresponds to a gripping force of B. Therefore, after analyzing the hardness information of the target object, the hardness information can be directly matched with the gripping force reference table, and the resulting gripping force is the initial gripping force.

[0056] In one implementation, this embodiment includes the following steps when analyzing the hardness / softness information of a target object:

[0057] Step S201: After the bionic hand comes into contact with the target object, the change information of the normal force within a preset time period is monitored in real time to determine the rate of change of the normal force;

[0058] Step S202: Based on the rate of change, determine the hardness or softness information of the target object.

[0059] During the grasping process, the hardness or softness of the target object affects the normal force at the contact point between the fingertips and the target object. For example, if the target object is hard, the bionic hand will use a larger grasping force to maintain the grasp, resulting in a rapid increase in the normal force at the contact point between the fingertips and the target object within a short period. Conversely, if the target object is soft, the bionic hand will use a smaller grasping force to minimize damage, resulting in a gradual increase in the normal force at the contact point between the fingertips and the target object within a short period. Therefore, in this embodiment, once the bionic hand contacts the target object, it begins the grasping action. This embodiment can monitor the change in the normal force at the contact point between the fingertips and the target object within a preset time period (e.g., 0.5 seconds). Based on this change information, the rate of change of the normal force can be determined. In this embodiment, determining the rate of change of the normal force is to determine whether the normal force at the contact point between the fingertips and the target object increases gradually or rapidly. This allows for the determination of the hardness or softness of the target object based on the rate of change. In practical applications, since the rate of change is a specific numerical value, and the rate of change of the normal force is positively correlated with the hardness information, the greater the rate of change of the normal force, the higher the hardness level of the target object, indicating that the target object is harder. To intuitively determine the hardness information of the target object, this embodiment can also set a hardness reference table. This hardness reference table reflects the mapping relationship between the rate of change of the normal force and the hardness information. For example, when the rate of change of the normal force is V1, the corresponding hardness information is level one; when the rate of change of the normal force is V2, the corresponding hardness information is level two. Therefore, after analyzing the rate of change of the normal force, the corresponding hardness information can be determined based on this hardness reference table. In other implementations, this embodiment can train a hardness classification model, which can automatically analyze the hardness information directly based on the input normal force change information.

[0060] In another implementation, this embodiment may further include the following steps when analyzing the hardness / softness information of the target object:

[0061] Step S21: At the instant when the bionic hand comes into contact with the target object, obtain the deformation information of the contact area between the bionic hand and the target object;

[0062] Step S22: Based on the deformation information, determine the hardness information of the target object.

[0063] During the grasping process, the hardness or softness of the target object affects the deformation information of the contact area between the target object and the bionic hand. For example, if the target object is hard, the bionic hand will use a larger grasping force to maintain the grasp, resulting in a larger deformation at the contact area. Conversely, if the target object is soft, the bionic hand will use a smaller grasping force to reduce damage, resulting in a smaller deformation at the contact area. Therefore, this embodiment acquires the deformation information of the contact area between the bionic hand and the target object at the instant the bionic hand makes contact. Then, based on this deformation information, the hardness or softness of the target object is determined. In practical applications, the deformation information of the contact area between the target object and the bionic hand is positively correlated with the hardness or softness of the target object; the larger the deformation information, the higher the level of hardness or softness, indicating a harder target object. Similarly, the hardness reference table in this embodiment includes not only the mapping relationship between the rate of change of normal force and the hardness information, but also the mapping relationship between the deformation information of the contact area between the target object and the bionic hand and the hardness information. For example, deformation information 'a' corresponds to a first-level hardness, and deformation information 'b' corresponds to a second-level hardness. Therefore, after analyzing the deformation information of the contact area between the target object and the bionic hand, the corresponding hardness information can be directly matched based on the hardness reference table. Likewise, this embodiment can also automatically output hardness information based on the input deformation information using a hardness classification model. This embodiment determines the initial gripping force of the bionic hand by analyzing the hardness information of the target object.

[0064] Step S300: Grasp the target object based on the initial gripping force, and monitor preset influencing factor information in real time during the gripping process, and adaptively adjust the gripping force of the bionic hand based on the influencing factor information. The influencing factor information reflects the factors that affect the gripping effect of the bionic hand.

[0065] After determining the hardness or softness of the target object, this embodiment can determine the corresponding initial gripping force based on this information. Then, the bionic hand begins to grasp the target object using this initial gripping force. During the grasping process, the bionic hand continuously monitors preset influencing factors. These influencing factors reflect information about factors affecting the grasping effect of the bionic hand, such as gripping position changes, movement speed, and current changes. Specifically, this embodiment acquires information on the contact position changes between the bionic hand and the target object, the movement speed of the bionic hand, and the current changes of the bionic hand during the grasping process. Then, the contact position changes, movement speed, and current changes are used as the influencing factors. In this embodiment, the contact position changes reflect the displacement between the bionic hand and the target object, the movement speed reflects the movement speed of the bionic hand when grasping the target object, and the current changes reflect the change in current value during the movement of the bionic hand while grasping the target object. Based on the above information on influencing factors, this embodiment can conduct a comprehensive analysis and then adjust the gripping force of the bionic hand accordingly.

[0066] In one implementation, adjusting the gripping force of the bionic hand based on influencing factor information may include the following steps:

[0067] Step S301: Obtain the weight information corresponding to the contact position change information, movement speed information, and current change information, respectively;

[0068] Step S302: Determine the gripping stability of the bionic hand based on the weight information;

[0069] Step S303: If the gripping stability is insufficient, increase the gripping force of the bionic hand.

[0070] Specifically, this embodiment sets corresponding weight information for contact position change information, movement speed information, and current change information. This weight information is set based on the degree of influence of these three information on grip stability. For example, if the negative impact of contact position change information on grip stability is significant, its corresponding weight information will be larger; if the negative impact of current change information on grip stability is small, its corresponding weight information will be smaller. In practical applications, the weight information corresponding to contact position change information, movement speed information, and current change information is summed to 1. For example, the weight information for contact position change information is 0.5, the weight information for movement speed information is 0.3, and the weight information for current change information is 0.2. Next, since contact position change information, movement speed information, and current change information can all be represented by specific numerical values, this embodiment, after determining the weight information for contact position change information, movement speed information, and current change information, can further perform a weighted sum based on these information and their respective weight information to obtain a final value. Based on this final value, grip stability can be determined.

[0071] In practical applications, since the final value calculated in this embodiment is based on the specific values ​​of the aforementioned influencing factors, and these influencing factors directly negatively impact grip stability, the calculated final value is negatively correlated with grip stability. A larger final value indicates weaker grip stability, and a smaller final value indicates stronger grip stability. Furthermore, if grip stability is insufficient, specifically if the final value exceeds a preset value, the gripping force of the bionic hand needs adjustment. For example, the gripping force can be gradually increased from an initial value to a fixed value. Then, new influencing factor information is repeatedly acquired, and a new final value is recalculated based on this new information. A new gripping stability is then determined, and the process of repeatedly judging whether further adjustment of the bionic hand's gripping force is needed is repeated. This achieves adaptive adjustment of the bionic hand's gripping force throughout the entire gripping process, ensuring optimal gripping performance.

[0072] Furthermore, after the bionic hand moves the target object to the target position, it receives a release command and controls the bionic hand to gradually reduce its gripping force until it reaches zero. During the process of reducing the gripping force, the tactile sensor simultaneously monitors the normal force at the contact point between the fingertip and the target object. Once the normal force decreases to zero, it is confirmed that the target object has detached from the bionic hand, completing the release. The tactile sensor is then reset to prepare for the next gripping command.

[0073] In other implementations, this embodiment can further collect other index data during the bionic hand's grasping action, such as the tangential force fluctuation at the contact point between the bionic hand and the target object, and the displacement of the target object during its fall. Based on these index data, the risk of the target object slipping can be analyzed, and corresponding measures can be taken to improve the gripping stability of the bionic hand and prevent the target object from falling off the bionic hand.

[0074] In summary, this embodiment first receives a grasping command, monitors the force information at the fingertips of the bionic hand, and determines whether the bionic hand is in contact with the target object based on the force information. Once the bionic hand contacts the target object, it acquires the object's hardness / softness information and obtains an initial grasping force based on this information. Finally, it grasps the target object based on the initial grasping force, and during the grasping process, it monitors preset influencing factor information in real time and adaptively adjusts the bionic hand's grasping force based on this information. This influencing factor information reflects factors that affect the grasping effect of the bionic hand. This embodiment can adjust the bionic hand's grasping force in real time based on different influencing factor information, which helps maintain good grasping stability throughout the grasping process and avoids problems such as grasping failure or damage to the object.

[0075] Based on the above embodiments, the present invention also provides a bionic hand grip force adaptive adjustment system, which is used to implement the steps in the above method embodiments. Figure 2 As shown, the bionic hand's gripping force adaptive adjustment system in this embodiment includes: a contact judgment module 10, a softness / hardness analysis module 20, and a gripping force adjustment module 30. Specifically, the contact judgment module 10 is used to receive gripping commands, monitor the force information at the fingertips of the bionic hand, and determine whether the bionic hand is in contact with a target object based on the force information. The softness / hardness analysis module 20 is used to obtain the softness / hardness information of the target object after the bionic hand contacts the target object, and obtain an initial gripping force based on the softness / hardness information. The gripping force adjustment module 30 is used to grasp the target object based on the initial gripping force, and monitor preset influencing factor information in real time during the grasping process, and adaptively adjust the gripping force of the bionic hand based on the influencing factor information. The influencing factor information reflects the factors that affect the gripping effect of the bionic hand.

[0076] The working principle of each module in the bionic hand grip force adaptive adjustment system of this embodiment is the same as that of each step in the above method embodiment, and will not be repeated here.

[0077] The modules in the aforementioned bionic hand's adaptive grip force adjustment system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the terminal in hardware form or independent of it, or stored in the terminal's memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0078] Based on the above embodiments, the present invention also provides a terminal, the principle block diagram of which can be as follows: Figure 3 As shown. The terminal may include one or more processors 100 ( Figure 3 (Only one is shown in the diagram), memory 101, and computer program 102 stored in memory 101 and executable on one or more processors 100. For example, a bionic hand grip force adaptive adjustment program. When one or more processors 100 execute computer program 102, they can implement the various steps in the bionic hand grip force adaptive adjustment method embodiment. Alternatively, when one or more processors 100 execute computer program 102, they can implement the functions of various modules / units in the bionic hand grip force adaptive adjustment system embodiment, without limitation herein.

[0079] In one embodiment, the processor 100 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0080] In one embodiment, memory 101 may be an internal storage unit of an electronic device, such as a hard drive or RAM. Memory 101 may also be an external storage device of the electronic device, such as a plug-in hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc. Furthermore, memory 101 may include both internal and external storage units. Memory 101 is used to store computer programs and other programs and data required by the terminal. Memory 101 can also be used to temporarily store data that has been output or will be output.

[0081] Those skilled in the art will understand that Figure 3 The block diagram shown is merely a partial structural diagram related to the present invention and does not constitute a limitation on the terminal to which the present invention is applied. A specific terminal may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0082] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, operational databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual operating data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for adaptive adjustment of gripping force in a bionic hand, characterized in that, The method includes: It receives grasping commands, monitors the force information at the fingertips of the bionic hand, and determines whether the bionic hand is in contact with the target object based on the force information. When the bionic hand comes into contact with the target object, it acquires information about the softness or hardness of the target object and obtains an initial gripping force based on the information about the softness or hardness. The target object is grasped based on the initial gripping force, and preset influencing factor information is monitored in real time during the grasping process. The gripping force of the bionic hand is adaptively adjusted based on the influencing factor information. The influencing factor information reflects the factors that affect the gripping effect of the bionic hand. During the grasping process, preset influencing factors are monitored in real time, including: During the grasping process, information on the change in the grasping position between the bionic hand and the target object is acquired; During the grasping process, the movement speed information of the bionic hand is acquired; During the grasping process, information on the electrical changes of the bionic hand is acquired; The information on changes in gripping position, movement speed, and current change is used as the influencing factor information. The bionic hand adaptively adjusts its grip strength based on the aforementioned influencing factor information, including: The weight information corresponding to the grip position change information, movement speed information, and current change information is obtained respectively; Based on the weight information, the gripping stability of the bionic hand is determined; If the gripping stability is insufficient, the gripping force of the bionic hand is increased.

2. The bionic hand grip force adaptive adjustment method according to claim 1, characterized in that, Monitoring the force information at the fingertips of the bionic hand, and determining whether the bionic hand is in contact with a target object based on the force information, includes: The force information is obtained by monitoring the normal and tangential forces at the fingertips of the bionic hand using tactile sensors. If the normal force is greater than or equal to a preset threshold, it is determined that the bionic hand is in contact with the target object.

3. The bionic hand grip force adaptive adjustment method according to claim 2, characterized in that, When the bionic hand comes into contact with the target object, it acquires information about the hardness or softness of the target object, including: When the bionic hand comes into contact with the target object, it monitors the change information of the normal force in real time within a preset time period to determine the rate of change of the normal force. Based on the rate of change, the hardness or softness information of the target object is determined.

4. The bionic hand grip force adaptive adjustment method according to claim 2, characterized in that, When the bionic hand comes into contact with the target object, it acquires information about the hardness or softness of the target object, including: At the instant the bionic hand makes contact with the target object, the deformation information of the contact area between the bionic hand and the target object is obtained; Based on the deformation information, the hardness or softness of the target object is determined.

5. The bionic hand grip force adaptive adjustment method according to claim 1, characterized in that, The method further includes: If the bionic hand moves the target object to the target position, it receives a release command and controls the bionic hand to gradually reduce the gripping force until the gripping force is 0.

6. A bionic hand grip force adaptive adjustment system, characterized in that, The system is used to implement the steps of the bionic hand grip force adaptive adjustment method according to any one of claims 1-5, the system comprising: The contact judgment module is used to receive grasping commands, monitor the force information of the fingertips of the bionic hand, and determine whether the bionic hand is in contact with the target object based on the force information. The soft-hardness analysis module is used to obtain the soft-hardness information of the target object after the bionic hand comes into contact with the target object, and to obtain the initial gripping force based on the soft-hardness information; The gripping force adjustment module is used to grip the target object based on the initial gripping force, and to monitor preset influencing factor information in real time during the gripping process, and to adaptively adjust the gripping force of the bionic hand based on the influencing factor information. The influencing factor information reflects the factors that affect the gripping effect of the bionic hand.

7. A terminal, characterized in that, The terminal includes a memory, a processor, and a bionic hand grip force adaptive adjustment program stored in the memory and executable on the processor. When the processor executes the bionic hand grip force adaptive adjustment program, it implements the steps of the bionic hand grip force adaptive adjustment method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a bionic hand grip force adaptive adjustment program, which implements the steps of the bionic hand grip force adaptive adjustment method as described in any one of claims 1-5 on the computer-readable storage medium.

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