CN117405168A - Flexible touch sensor for sensing object deformability by mechanical hand - Google Patents
Flexible touch sensor for sensing object deformability by mechanical hand Download PDFInfo
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Abstract
The invention provides a flexible touch sensor for mechanically sensing the deformability of an object, comprising: the flexible layer is provided with a reduced graphene oxide layer facing one side of the middle flexible layer, and one side of the reduced graphene oxide layer, which is away from the upper flexible layer, is connected with the middle flexible layer in a laminating manner. According to the invention, the porous piezoresistive layer and the reduced graphene oxide layer are arranged in the same touch sensor, so that the pressure data and the strain data of the object are obtained simultaneously, the material hardness and the overall rigidity of the object can be supported to be measured simultaneously, and the deformability of the object can be measured accurately.
Description
Technical Field
The invention relates to the field of measurement, in particular to a flexible touch sensor for sensing the deformability of an object by mechanical hand.
Background
The current application of robots is gradually expanding from industrial to everyday life scenarios, thus similar haptic sensations are needed to reach the flexibility of the human level. In haptic perception, the perception of deformation-related properties provides valuable haptic cues for distinguishing, identifying deformable objects, and formulating appropriate operating strategies. In research in the field of haptic perception, determining the deformability of an object is particularly challenging, as it is generally affected by a number of deformation-related properties, such as young's modulus, shore hardness and stiffness. Young's modulus and Shore hardness represent the inherent deformable properties of a material, while stiffness describes the overall resistance of an object to elastic deformation, which is affected by various factors, including the size of the object, the hardness of the material, or the deformable structure. Deformable objects in everyday life are often composed of a combination of deformable materials and structures (e.g. balloons) or materials of different hardness (e.g. oranges). Thus, in a real-world unstructured environment, achieving a perception of deformability of a deformable object by a robot requires a coordinated perception of various deformation properties, such as material stiffness, overall stiffness, etc.
At present, in the field of robot touch perception, a sensor for separately measuring material hardness exists, and the sensor can only measure the pressure of three sites through a 1×3 magnetostrictive touch sensor, so that the material hardness cannot be measured accurately, and the integral rigidity of an object cannot be accurately calculated by utilizing the pressure data of the three sites, so that the object deformability measurement cannot be accurately performed.
Accordingly, the prior art has drawbacks and needs to be improved and developed.
Disclosure of Invention
The invention aims to solve the technical problems that the prior art is overcome by providing a flexible touch sensor for sensing the deformability of an object by mechanical hand, and aims to solve the problems that the touch sensor in the prior art can not measure the whole rigidity while measuring the hardness of a material and can not accurately measure the deformability of the object.
The technical scheme adopted for solving the technical problems is as follows:
a flexible tactile sensor for mechanically sensing the deformability of an object, comprising: the flexible layer is provided with a reduced graphene oxide layer facing one side of the middle flexible layer, and one side of the reduced graphene oxide layer, which is away from the upper flexible layer, is connected with the middle flexible layer in a laminating manner.
Further, the porous piezoresistive layer is formed by uniformly mixing conductive filler, sacrificial template particles and elastic polymer to prepare a piezoresistive sheet and removing the sacrificial template particles in the piezoresistive sheet.
Further, the side of the spiral interdigital electrode facing the porous piezoresistive layer is in an exposed state.
Further, the reduced graphene oxide layer comprises a reduced graphene oxide film, a first conductive metal film coated on a first end of the reduced graphene oxide film, and a second conductive metal film coated on a second end of the reduced graphene oxide film.
The invention also provides a measuring method for measuring deformability of an object, comprising:
acquiring pressure data and strain data obtained by measuring deformability of an object by using the flexible touch sensor, and acquiring kinesthesia data of a manipulator;
comparing the pressure data with preset contact pressure to obtain a comparison result, and determining the current state of the manipulator according to the comparison result;
when the manipulator is in a contact state, obtaining the overall rigidity of the object to be measured according to the kinesthesia data and the pressure data, and obtaining the material hardness of the object to be measured according to the pressure data and the strain data;
wherein the flexible tactile sensor is attached to the manipulator surface.
Further, the kinesthetic data comprise displacements of the object to be measured at different time points, and the pressure data comprise pressure values at different time points; the step of obtaining the overall rigidity of the object to be measured according to the kinesthetic data and the pressure data comprises the following steps:
taking the displacement as a horizontal axis and the pressure value as a vertical axis, selecting displacement and pressure values corresponding to different time periods, and generating a displacement-pressure curve;
and performing linear fitting on the displacement-pressure curve to obtain a displacement-pressure curve slope, and obtaining the overall rigidity of the object to be measured according to the preset corresponding relation between the displacement-pressure curve slope and the overall rigidity.
Further, the strain data includes strain values at different times; the obtaining the material hardness of the object to be measured according to the pressure data and the strain data comprises the following steps:
intercepting the pressure data and the strain data using a time sliding window;
calculating the signal characteristics of each sliding time window;
and inputting the signal characteristics of each time sliding window into a trained multi-layer perceptron regression model to obtain the material hardness of the object to be detected.
Further, the calculating the signal characteristic of each sliding time window includes:
taking the strain value as a horizontal axis and the pressure value as a vertical axis, selecting the strain value and the pressure value corresponding to different time periods, generating a strain-pressure curve, and performing linear fitting on the strain-pressure curve to obtain a slope of the strain-pressure curve;
according to each pressure value in the sliding time window, a pressure average value is obtained;
obtaining a strain average value according to each strain value in the sliding time window;
the slope of the strain-pressure curve, the pressure average and the strain average are taken as the signal characteristics of each sliding time window.
The invention also provides an apparatus for measuring deformability of an object, wherein the apparatus comprises: the measuring device comprises a memory, a processor and a measuring program stored on the memory and capable of being executed on the processor for measuring the deformability of an object, wherein the measuring program realizes the steps of the measuring method when being executed by the processor.
The invention also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program executable for implementing the steps of the measurement method as described above.
The invention provides a flexible touch sensor for mechanically sensing the deformability of an object, comprising: the flexible layer is provided with a reduced graphene oxide layer facing one side of the middle flexible layer, and one side of the reduced graphene oxide layer, which is away from the upper flexible layer, is connected with the middle flexible layer in a laminating manner. According to the invention, the porous piezoresistive layer and the reduced graphene oxide layer are arranged in the same touch sensor, so that the pressure data and the strain data of the object are obtained simultaneously, the material hardness and the overall rigidity of the object can be supported to be measured simultaneously, and the deformability of the object can be measured accurately.
Drawings
FIG. 1 is a schematic diagram of a preferred embodiment of a flexible tactile sensor for mechanically sensing the deformability of an object in accordance with the present invention;
FIG. 2 is a schematic representation of the planar tensile strain insensitivity of a porous piezoresistive layer in accordance with the present invention;
FIG. 3 is a schematic diagram of the structure of a reduced graphene oxide layer according to the present invention;
FIG. 4 is a schematic diagram of the pressure insensitive nature of the strain sensing composite of the present invention;
FIG. 5 is a flow chart of a preferred embodiment of a measurement method for object deformability measurement in accordance with the present invention;
FIG. 6 is a schematic diagram of a quantitative calculation flow of material hardness in the present invention;
reference numerals illustrate:
10. a lower flexible layer; 20. spiral interdigital electrodes; 30. a porous piezoresistive layer; 40. an intermediate flexible layer; 50. reducing the graphene oxide layer; 60. an upper flexible layer; 51. reducing the graphene oxide film; 52. a first conductive metal film; 53. and a second conductive metal film.
Detailed Description
The invention provides a flexible touch sensor for sensing object deformability by mechanical hand, which is further described in detail below with reference to the accompanying drawings and examples in order to make the objects, technical solutions and effects of the invention more clear and definite. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The technical scheme is realized based on the application of the robot. At present, the application of the robot has been widely applied to the daily life scene, and the touch perception of the robot has become an important research field. Some current tactile sensors can measure the hardness of materials, such as a V-shaped structure piezoelectric sensor, and the V-shaped structure piezoelectric sensor corrects hardness values measured at different angles through different driving modes of two piezoelectric bimorphs, which is essentially to measure the hardness through resonance frequency information of the piezoelectric sensor. In addition to the measurement angle, however, the object size also affects the resonance frequency and thus the measurement of stiffness. Therefore, the piezoelectric sensor with the V-shaped structure cannot accurately measure the hardness of the material. Meanwhile, the piezoelectric sensor with the V-shaped structure cannot be well combined with a manipulator, and the manipulator operation can be influenced when the piezoelectric sensor is assembled on the manipulator. One skilled in the art also proposes a solution to infer the hardness of a material by pressing the probe into a specified location and measuring the pressure on the probe at the specified location by means of a fiber optic sensor to make a measurement of the hardness of the material. The scheme needs to preset positions and cannot realize self-adaptive sensing. Meanwhile, in order to enable the measurement result not to be influenced by the size of an object, the probe of the scheme needs to be small enough and is not matched with the size of a manipulator commonly used at present. The technical scheme can not realize simultaneous measurement of the hardness and the overall rigidity of the object material. Therefore, when the softness and the overall rigidity of the materials of the two objects are opposite, the deformability of the objects cannot be accurately judged.
The measuring method can simultaneously measure the material hardness and the overall rigidity of the object, does not need preset force or position when measuring the material hardness of the object, and has strong adaptability to the size of the object. Pressure and in-plane tensile strain at the same contact site can be measured self-decoupleably. Meanwhile, the touch sensor is made of flexible materials, so that the touch sensor has overall flexibility and certain shock resistance, can be well attached to a humanoid robot fingertip, is simple in structure and manufacturing process, and effectively reduces the processing cost of the sensor.
The technical solution of the present invention provides a flexible touch sensor for sensing object deformability by mechanical hand, as shown in fig. 1, comprising: the lower flexible layer 10, the spiral interdigital electrode 20, the porous piezoresistive layer 30, the middle flexible layer 40 and the upper flexible layer 60 which are sequentially connected in a laminating mode, a reduced graphene oxide layer 50 is arranged on one side, facing the middle flexible layer 40, of the upper flexible layer 60, and one side, facing away from the upper flexible layer 60, of the reduced graphene oxide layer 50 is connected with the middle flexible layer 40 in a laminating mode.
The pressure sensing combination layer is composed of a lower flexible layer 10, a spiral interdigital electrode 20 and a porous piezoresistive layer 30 and is used for measuring pressure data of an object. The strain sensing combination layer is composed of the intermediate flexible layer 40, the reduced graphene oxide layer 50 and the upper flexible layer 60 for measuring strain data of an object. By applying the object to the touch sensor, the pressure sensing combination layer and the strain sensing combination layer can simultaneously measure the pressure value and the strain value of the object, and the material hardness and the overall rigidity of the object can be obtained simultaneously by combining the displacement of the manipulator, so that the deformability of the object can be measured more accurately.
The position of the pure reduced graphene oxide film in the reduced graphene oxide layer 50 determines the plane position of the strain sensing combination layer for strain sensing. The position of the spiral interdigitated electrodes 20 determines the planar position of the pressure sensing assembly for pressure sensing. The planar locations of the strain sensing and pressure sensing are overlapping.
In one embodiment of the present invention, the porous piezoresistive layer 30 is formed by uniformly mixing conductive filler, sacrificial template particles and an elastic polymer to form a piezoresistive sheet, and removing the sacrificial template particles from the piezoresistive sheet.
The porous piezoresistive layer 30 of the present invention has a porous structure, which is adaptable in shape. The porous piezoresistive layer 30 is a three-dimensional percolation conductive network that converts pressure into an electrical signal. As shown in fig. 2, as the pressure increases, the relative conductance changes also increase, i.e., the electrical resistance of the porous piezoresistive layer 30 becomes smaller and smaller, exhibiting a negative pressure resistance effect. The porous piezoresistive layer 30 has the mechanical properties of a low modulus (which is a few tenths of the modulus of the flexible layer) and a low poisson's ratio (approximately 0). When compressed, no lateral strain is generated such that the resistance of the multi-Kong Yazu layer 30 increases to interfere with pressure sensing, thereby rendering the pressure combination sensing layer plane strain insensitive and allowing more accurate measurement of pressure values.
In the preferred embodiment of the present invention, the side of the spiral interdigital electrode 20 facing the porous piezoresistive layer 30 is exposed.
Specifically, the spiral interdigitated electrode 20 is a filament-like electrode having a spiral shape for inducing a change in resistance of the porous piezoresistive layer 30. The spiral interdigital electrode 20 is hollow to ensure good contact between the electrode and the porous piezoresistive layer when the sensor is assembled. Meanwhile, one side of the spiral interdigital electrode 20 facing the porous piezoresistive layer 30 is in a bare state and is in direct contact with the porous piezoresistive layer 30, so that the spiral interdigital electrode 20 and the porous piezoresistive layer 30 are in closer contact, the signal transmission is more efficient, the problems of contact resistance and poor contact can be reduced, the stability and reliability of signals are improved, the measurement error caused by the contact problem is reduced, and the space of the sensor is saved.
In a preferred embodiment of the present invention, as shown in fig. 3, the reduced graphene oxide layer 50 includes a reduced graphene oxide film 51, a first conductive metal film 52 coated on a first end of the reduced graphene oxide film, and a second conductive metal film 53 coated on a second end of the reduced graphene oxide film.
Specifically, the first conductive metal film 52 is a silver nanowire (AgNWs) electrode, and the second conductive metal film 53 is a silver nanowire (AgNWs) electrode. The reduced graphene oxide layer 50 in the present invention is strain-sensed with high sensitivity by cracks in the reduced graphene oxide film, and the strain causes separation and expansion of crack edges in the reduced graphene oxide film (rGO film), thereby increasing the resistance. The normal pressure causes normal contact between graphene oxide sheets, resulting in a decrease in electrical resistance. But the former increases the resistance much more than the latter decreases. As shown in FIG. 4, in the strain sensing combination layer, the relative resistance change is stable and has no obvious change along with the increase of the pressure, so that the strain sensing combination layer is insensitive to the pressure, and the strain value can be measured more accurately.
In one embodiment of the present invention, the reduced graphene oxide layer 50 is semi-embedded in the upper flexible layer 60.
In a preferred embodiment of the present invention, the preparation method of the reduced graphene oxide thin film includes:
dripping graphene oxide gel on a rigid substrate to obtain a graphene film;
oxidizing the graphene film by using a laser direct writing mode to obtain an initial reduced graphene oxide film;
and (3) dripping silver nanowires on two ends of the initial reduced graphene oxide film to obtain the reduced graphene oxide film.
Specifically, the initial reduced graphene oxide film is a conductive reduced graphene oxide film with a preset pattern.
The invention also provides a measuring method for measuring the deformability of an object, as shown in fig. 5, the implementation steps of the measuring method are as follows:
s100, acquiring pressure data and strain data obtained by measuring the deformability of an object by using the flexible touch sensor, and acquiring kinesthesia data of a manipulator;
specifically, the invention utilizes the flexible touch sensor to measure the deformability of the object, applies the object to be measured on the flexible touch sensor, and simultaneously measures the material hardness and the overall rigidity of the object to be measured. When an object to be detected is applied to the flexible touch sensor, the signal conditioning and data acquisition module controls the touch sensor to acquire data, pressure data and strain data are obtained, and the pressure data and the strain data are transmitted to the computer terminal. The signal conditioning and data acquisition module comprises a signal acquisition submodule and a data acquisition submodule. The signal conditioning sub-module is used for converting the resistance signal of the touch sensor into a voltage signal, and the data acquisition module is used for providing voltage for the touch sensor and transmitting the pressure data and the stress data of the touch sensor to the computer terminal. And the computer terminal sends a control signal to the manipulator controller, and the manipulator controller controls the manipulator to move. The manipulator is provided with an encoder, the displacement of the output end can be calculated, namely the displacement information of the manipulator is obtained, and the manipulator controller obtains kinesthesia data according to the displacement information and transmits the kinesthesia data to the computer terminal. And the computer terminal simultaneously acquires pressure data and strain data of the flexible touch sensor and kinesthesia data of the manipulator, and is used for judging the subsequent contact state and calculating the integral rigidity and the material hardness.
S200, comparing the pressure data with preset contact pressure to obtain a comparison result, and determining the current state of the manipulator according to the comparison result;
specifically, the computer terminal compares the pressure data with a preset contact pressure to obtain a comparison result. When the comparison result is that the pressure data is larger than the preset contact pressure, confirming that the manipulator is in a contact state at the moment; and when the comparison result is that the pressure data is smaller than the preset contact pressure, confirming that the manipulator is in a non-contact state at the moment.
S300, when the manipulator is in a contact state, obtaining the overall rigidity of the object to be detected according to the kinesthesia data and the pressure data, and obtaining the material hardness of the object to be detected according to the pressure data and the strain data;
wherein the flexible tactile sensor is attached to the manipulator surface.
Specifically, the computer terminal can calculate the overall rigidity of the object to be measured according to the acquired kinesthesia data and the pressure data, and meanwhile, the material hardness of the object to be measured is obtained according to the acquired pressure data and the strain data.
In one implementation, after the step S200, the method further includes:
and when the manipulator is in a non-contact state, the pressure data, the strain data and the kinesthesia data are not processed.
In one implementation, the upper flexible layer of the flexible tactile sensor is affixed to the manipulator surface.
In one implementation, the kinesthesia data includes displacements of the object under test at different points in time, and the pressure data includes pressure values at different points in time; the step of obtaining the overall rigidity of the object to be measured according to the kinesthetic data and the pressure data comprises the following steps:
taking the displacement as a horizontal axis and the pressure value as a vertical axis, selecting displacement and pressure values corresponding to different time periods, and generating a displacement-pressure curve;
and performing linear fitting on the displacement-pressure curve to obtain a displacement-pressure curve slope, and obtaining the overall rigidity of the object to be measured according to the preset corresponding relation between the displacement-pressure curve slope and the overall rigidity.
Specifically, the smaller the slope of the displacement-pressure curve, the greater the overall stiffness representing the object to be measured.
In one implementation, the strain data includes strain values at different times; the obtaining the material hardness of the object to be measured according to the pressure data and the strain data comprises the following steps:
intercepting the pressure data and the strain data using a time sliding window;
calculating the signal characteristics of each sliding time window;
and inputting the signal characteristics of each time sliding window into a trained multi-layer perceptron regression model to obtain the material hardness of the object to be detected.
In particular, the present invention utilizes machine learning to map haptic sense signals onto corresponding material hardness. The invention utilizes the multi-layer perceptron regression Model (MLP) to realize quantitative calculation of material hardness. And intercepting the pressure data and the strain data by utilizing the time sliding window, and then calculating the signal characteristic of each sliding time window as the input of a multi-layer perceptron regression model, wherein the multi-layer perceptron regression model outputs a corresponding material hardness value, so that the quantitative estimation of the material hardness is realized.
In one implementation, the flexible tactile sensor may require training of the multi-layer sensor regression model prior to use to obtain a trained multi-layer sensor regression model that may be considered as calibrating material hardness. The step of training the multi-layer perceptron regression model includes:
preparing cylindrical samples with different hardness;
measuring the material hardness of the cylindrical sample by using a durometer to obtain a first material hardness;
pressing the cylindrical sample with different pressing displacements by using a manipulator equipped with a sensor, and collecting a pressure signal and a strain signal of each pressing;
or using a manipulator equipped with a sensor to press the cylindrical sample with different applied forces, and collecting a pressure signal and a strain signal of each press;
performing signal extraction on the pressure signal and the strain signal collected each time by using a sliding time window;
calculating the characteristic value of the signal extracted by the sliding time window to obtain a signal characteristic value;
and training the multi-layer perceptron regression model by taking the signal characteristic value as input data of the multi-layer perceptron regression model and taking the first material hardness as a label until a stopping condition is met, so as to obtain the trained multi-layer perceptron regression model.
In one implementation, the calculating the signal characteristic for each sliding time window includes:
taking the strain value as a horizontal axis and the pressure value as a vertical axis, selecting the strain value and the pressure value corresponding to different time periods, generating a strain-pressure curve, and performing linear fitting on the strain-pressure curve to obtain a slope of the strain-pressure curve;
according to each pressure value in the sliding time window, a pressure average value is obtained;
obtaining a strain average value according to each strain value in the sliding time window;
the slope of the strain-pressure curve, the pressure average and the strain average are taken as the signal characteristics of each sliding time window.
Specifically, as shown in FIG. 6, signal extraction is performed using a sliding time windowAccording to each pressure value P in the sliding time window i Obtaining the average value P of the pressure avg And according to each strain value S within the sliding time window i Obtaining a strain average value S avg . Slope of strain-pressure curve, average pressure P avg Average value S of strain avg As a signal characteristic of each sliding time window. The smaller the slope of the strain-pressure curve, the harder the material hardness representing the object to be measured. And inputting the signal characteristics of each sliding time window into a trained multi-layer perceptron regression model to obtain the material hardness of the object to be detected. According to the invention, quantitative calculation of the hardness of the material can be realized by using the multi-layer perceptron regression model, the interference of the size of the object on the measurement result is reduced, the self-adaptive perception of the deformability of the object is realized, and further, the accurate measurement of the deformability of the object is realized.
In one implementation, the step S300 further includes: and adjusting the contact pressure according to the material hardness and the overall rigidity.
Specifically, the invention performs sensing feedback operation through the flexible touch sensor, the manipulator and the controller thereof, the signal conditioning and data acquisition module and the computer terminal. The computer terminal receives the relative resistance change value of the pressure sensing combination layer in the touch sensor transmitted by the data acquisition module in real time, and when the relative resistance change value of the pressure sensing combination layer exceeds a certain threshold value, the computer terminal judges that contact is generated. At this time, the computer terminal transmits a control signal to the manipulator controller, and controls the manipulator to press into an arbitrary displacement for sensing the deformable dual properties (i.e., the material hardness and the overall rigidity) of the object. And the computer terminal calculates the hardness and the overall rigidity of the material according to the pressure data and the strain data of the flexible touch sensor and the displacement of the manipulator, plans the proper contact pressure between the material and the object, and automatically adjusts the contact pressure to achieve the target contact pressure. The invention combines the kinescope signal of the manipulator and the bimodal signal (namely pressure signal and strain signal) of the flexible touch sensor to measure the material hardness and the integral rigidity of the object at the same time, and can realize the accurate measurement of the variability of the object.
The invention also provides an apparatus for measuring deformability of an object, wherein the apparatus comprises: a memory, a processor and a measurement program stored on the memory and executable on the processor for measuring deformability of an object, the measurement program, when executed by the processor, implementing the steps of the measurement method as described above; as described in detail above.
The present invention also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program executable for implementing the steps of the measurement method as described above; as described in detail above.
In summary, the flexible touch sensor for sensing object deformability mechanically provided by the present invention includes: the flexible layer is provided with a reduced graphene oxide layer facing one side of the middle flexible layer, and one side of the reduced graphene oxide layer, which is away from the upper flexible layer, is connected with the middle flexible layer in a laminating manner. According to the invention, the porous piezoresistive layer and the reduced graphene oxide layer are arranged in the same touch sensor, so that the pressure data and the strain data of the object are obtained simultaneously, the material hardness and the overall rigidity of the object can be supported to be measured simultaneously, and the deformability of the object can be measured accurately.
It is to be understood that the invention is not limited in its application to the examples described above, but is capable of modification and variation in light of the above teachings by those skilled in the art, and that all such modifications and variations are intended to be included within the scope of the appended claims.
Claims (10)
1. A flexible tactile sensor for mechanically sensing the deformability of an object, comprising: the flexible layer is provided with a reduced graphene oxide layer facing one side of the middle flexible layer, and one side of the reduced graphene oxide layer, which is away from the upper flexible layer, is connected with the middle flexible layer in a laminating manner.
2. The flexible tactile sensor for mechanical sensing of object deformability according to claim 1, wherein the porous piezoresistive layer is formed by uniformly mixing conductive filler, sacrificial template particles and elastic polymer to obtain a piezoresistive sheet, and removing the sacrificial template particles from the piezoresistive sheet.
3. The flexible tactile sensor for mechanical sensing of object deformability according to claim 1, wherein the side of the spiral interdigitated electrode facing the porous piezoresistive layer is bare.
4. The flexible tactile sensor for mechanical sensing of object deformability of claim 1, wherein the reduced graphene oxide layer comprises a reduced graphene oxide film, a first conductive metal film coated on a first end of the reduced graphene oxide film, and a second conductive metal film coated on a second end of the reduced graphene oxide film.
5. A measurement method for measuring deformability of an object, comprising:
acquiring pressure data, strain data obtained by measuring deformability of an object using the flexible tactile sensor according to any one of claims 1 to 4, and acquiring kinesthesia data of a manipulator;
comparing the pressure data with preset contact pressure to obtain a comparison result, and determining the current state of the manipulator according to the comparison result;
when the manipulator is in a contact state, obtaining the overall rigidity of the object to be detected according to the kinesthesia data and the pressure data, and obtaining the material hardness of the object to be detected according to the pressure data and the strain data;
wherein the flexible tactile sensor is attached to the manipulator surface.
6. The measurement method according to claim 5, wherein the kinesthesia data includes displacements of the object to be measured at different time points, and the pressure data includes pressure values at different time points; the step of obtaining the overall rigidity of the object to be measured according to the kinesthetic data and the pressure data comprises the following steps:
taking the displacement as a horizontal axis and the pressure value as a vertical axis, selecting displacement and pressure values corresponding to different time periods, and generating a displacement-pressure curve;
and performing linear fitting on the displacement-pressure to obtain a displacement-pressure curve slope, and obtaining the overall rigidity of the object to be measured according to the preset corresponding relation between the displacement-pressure curve slope and the overall rigidity.
7. The method of measurement according to claim 6, wherein the strain data comprises strain values at different times; the obtaining the material hardness of the object to be measured according to the pressure data and the strain data comprises the following steps:
intercepting the pressure data and the strain data using a time sliding window;
calculating the signal characteristics of each sliding time window;
and inputting the signal characteristics of each time sliding window into a trained multi-layer perceptron regression model to obtain the material hardness of the object to be detected.
8. The method of measuring of claim 7, wherein said calculating signal characteristics for each sliding time window comprises:
taking the strain value as a horizontal axis and the pressure value as a vertical axis, selecting the strain value and the pressure value corresponding to different time periods, generating a strain-pressure curve, and performing linear fitting on the strain-pressure curve to obtain a slope of the strain-pressure curve;
according to each pressure value in the sliding time window, a pressure average value is obtained;
obtaining a strain average value according to each strain value in the sliding time window;
the slope of the strain-pressure curve, the pressure average and the strain average are taken as the signal characteristics of each sliding time window.
9. An apparatus for measuring deformability of an object, the apparatus comprising: memory, a processor and a measurement program stored on the memory and executable on the processor for measuring deformability of an object, which measurement program, when being executed by the processor, implements the steps of the measurement method according to any of claims 5-8.
10. A computer readable storage medium, characterized in that it stores a computer program executable for implementing the steps of the measuring method according to any one of claims 5-8.
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