A fully intelligent car based on the neurons of Caenorhabditis elegans

Abstract

The present invention relates to a fully intelligent car based on C. elegans neurons. The fully intelligent car based on C. elegans neurons described in the present invention includes a signal acquisition module, a signal processing module and an action execution module; the signal acquisition module is used to obtain the surrounding environment data of the fully intelligent car, and transmit the surrounding environment data to the signal processing module; the signal processing module is a hardware circuit based on the simulation of the C. elegans neural network, the signal processing module is used to receive the surrounding environment data transmitted by the signal acquisition module, and generate action instructions according to the surrounding environment data, and control the action execution module to implement the action instructions; the action execution module is used to perform corresponding actions according to the action instructions. The fully intelligent car based on C. elegans neurons described in the present invention has a reaction ability and speed similar to that of C. elegans, and can complete simple actions without excessive human control and intervention.

Description

Technical Field

[0001] The present invention relates to the field of computational neuroscience, and in particular to a fully intelligent car based on Caenorhabditis elegans neurons. Background Art

[0002] With the continuous advancement of science and technology, robot-related technologies have also developed by leaps and bounds and are beginning to develop in the direction of intelligence. In traditional robot control technology, in order to make it act according to human intentions, remote control or pre-trained programs are usually used to control the robot to perform related actions. The interaction method is single and has poor robustness. For example, visual jitter, blur or other noise information that often appears during the robot's walking process poses a great challenge to the stable control of the model. Now some intelligent robot control methods based on bionic biological neural networks can be separated from remote controls and pre-set action programs to achieve bionic, intelligent, and highly robust intelligent robot control.

[0003] Robots in factories or laboratories are programmed by humans to perform certain actions or functions. In the true sense, they have no autonomy and no adaptability. Summary of the invention

[0004] Based on this, the purpose of the present invention is to provide a fully intelligent car based on C. elegans neurons, which has a reaction ability and speed similar to that of C. elegans and can complete simple actions without excessive human control and intervention.

[0005] The present invention provides a fully intelligent car based on Caenorhabditis elegans neurons:

[0006] It includes a signal acquisition module, a signal processing module and an action execution module;

[0007] The signal acquisition module is used to obtain the surrounding environment data of the fully intelligent car and transmit the surrounding environment data to the signal processing module;

[0008] The signal processing module is a hardware circuit implemented based on the simulation of the neural network of Caenorhabditis elegans. The signal processing module is used to receive the surrounding environment data transmitted by the signal acquisition module, and generate action instructions according to the surrounding environment data, and control the action execution module to implement the action instructions;

[0009] The action execution module is used to perform corresponding actions according to the action instruction.

[0010] Furthermore, the steps of building the hardware circuit include:

[0011] Use simulink in MATLAB software to build a model of the Caenorhabditis elegans neural network;

[0012] After obtaining a model whose simulation results are consistent with the physiological response results of C. elegans, a PCB schematic diagram corresponding to the model is drawn;

[0013] According to the PCB schematic diagram, the hardware circuit of the model is constructed.

[0014] Furthermore, the model of a single neuron of Caenorhabditis elegans is selected as:

[0015]

[0016] Among them, Cm is the membrane capacitance, V is the membrane voltage, that is, the potential difference between the two solutions separated by the membrane, Ica is the calcium current, IK is the potassium current, Isk is the intercellular calcium-gated potassium channel current, ILeak is the leakage current, Istimuli is the input direct current from the stimulus to the sensory neuron, Isyn is the current injected into the neuron by the chemical synapse, and Igap is the current injected into the neuron by the electrical synapse.

[0017] Furthermore, the potassium ion channel current model is:

[0018] Ik=Gknk 4 (V-Ek)

[0019] Among them, V is the membrane voltage, Ek is the potassium ion equilibrium potential, the equilibrium potential is the potential difference between the inside and outside of the cell membrane under resting conditions, nk is the voltage-gated potassium channel, and Gk is the potassium ion channel conductance.

[0020] Furthermore, the intercellular calcium-gated potassium ion channel current model is:

[0021] Isk=Gsk msk(V-Esk)

[0022] Among them, V is the membrane voltage, Esk is the equilibrium potential of the intercellular calcium-gated potassium ion channel, msk is the voltage-gated channel of the intercellular calcium-gated potassium ion channel, and Gsk is the conductance of the intercellular calcium-gated potassium channel.

[0023] Furthermore, the leakage current ion channel current model is:

[0024] Ileak=Gleak(V-Eleak)

[0025] Where V is the membrane voltage, Eleak is the equilibrium potential of the leakage current channel, and GLeak is the conductance of the leakage current channel.

[0026] Further, the signal acquisition module includes an ultrasonic rangefinder, and the action execution module includes a motor and a wheel;

[0027] The ultrasonic rangefinder is used to detect the distance between the vehicle and the object in front;

[0028] The signal processing module is used to generate an action instruction according to the distance detected by the ultrasonic rangefinder, and send the action instruction to the action execution module; the action instruction includes at least one of the following: forward, backward, stop;

[0029] The motor and the wheel are used to perform corresponding actions according to the action instructions.

[0030] Further, the signal acquisition module includes a pressure sensor, and the action execution module includes a motor and a wiper;

[0031] The pressure sensor is used to obtain the pressure and frequency of raindrops, and transmit the pressure and frequency data to the signal processing module;

[0032] The signal processing module is used to generate an action instruction according to the pressure and frequency, and send the action instruction to the action execution module; the action instruction includes whether the wiper performs a reciprocating motion and the speed of the reciprocating motion;

[0033] The motor and the wiper are used to perform corresponding actions according to the action instructions.

[0034] The present invention provides a fully intelligent car based on the neurons of C. elegans. The core of the car is the hardware module of the neuron. The module is the control cell of C. elegans. It is installed on the car body to control the intelligent car. Its reaction ability and speed should be similar to those of C. elegans. Its reaction can complete simple actions without excessive human control and intervention. Further in-depth research can complicate the model. For example, it can not only simulate a single neuron, but also combine multiple neurons to complete multiple complex actions. The number of neurons can be selected according to the complexity of the action. Complex intelligent cars are widely used in industry and life business, with strong operability, short development cycle, low cost and easy production.

[0035] For better understanding and implementation, the present invention is described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A schematic diagram of the steps for building a hardware circuit used in one embodiment of the present invention;

[0037] Figure 2 A schematic diagram of a simulink sub-model structure used in another embodiment of the present invention;

[0038] Figure 3 A model diagram of a single neuron of the nematode Caenorhabditis elegans in a simulink hardware model diagram drawn in another embodiment of the present invention;

[0039] Figure 4 The hardware model part of the potassium ion channel drawn for the present invention;

[0040] Figure 5 The hardware model part of the calcium ion channel drawn for the present invention;

[0041] Figure 6 The hardware model part of the intracellular calcium-gated potassium channel drawn for the present invention;

[0042] Figure 7 This is part of the leakage current ion channel hardware model drawn for the present invention. DETAILED DESCRIPTION

[0043] In order to make the objectives, technical solutions and advantages of the present application more clear, the embodiments of the present application will be further described in detail below with reference to the accompanying drawings.

[0044] It should be clear that 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 ordinary technicians in this field without creative work are within the scope of protection of the embodiments of the present application.

[0045] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the embodiments of the present application. The singular forms of "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0046] When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims. In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects, and do not have to be used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances.

[0047] In addition, in the description of this application, unless otherwise specified, "plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0048] In view of the problems in the background technology, the present application provides a fully intelligent car based on Caenorhabditis elegans neurons, the car comprising:

[0049] Signal acquisition module, signal processing module and action execution module.

[0050] The signal acquisition module is used to obtain the surrounding environment data of the fully intelligent car and transmit the surrounding environment data to the signal processing module.

[0051] The signal processing module is a hardware circuit implemented based on the simulation of the neural network of Caenorhabditis elegans. The signal processing module is used to receive the surrounding environment data transmitted by the signal acquisition module, and generate action instructions based on the surrounding environment data, and control the action execution module to implement the action instructions.

[0052] The action execution module is used to perform corresponding actions according to the action instruction.

[0053] The present invention provides a fully intelligent car based on C. elegans neurons, which utilizes the known number of neurons and synaptic connections of C. elegans and combines the subject of artificial intelligence. Its reaction ability and speed are similar to those of C. elegans and it can complete simple actions without excessive human control and intervention.

[0054] In a preferred embodiment, the steps of building the hardware circuit include:

[0055] S01: Build a model of the Caenorhabditis elegans neural network using simulink in MATLAB software.

[0056] The anatomical structure of the nervous system of C. elegans is very simple, with only 302 cells, accounting for about one-third of the total number of cells in the entire animal body. It is suitable for the simplest model of studying the nervous system of higher animals. Therefore, it is reliable to choose C. elegans as the basic model, and it is also reliable to use it for simulation. Although there are countless studies on C. elegans, there are more software than hardware, and there are more hardware in FPGA, but there are still few studies on CMOS simulation of C. elegans, only simulation experiments and network research. Because the parameter control of hardware implementation often has errors with software, there will be a large deviation between CMOS simulation implementation and simulation that is difficult to control. CMOS simulation implementation has greater modifiability than FPGA, and the simulation devices are also more basic and less, which makes it easier to implement hardware. The present invention is based on the nerve cells of C. elegans, and is intended to use the simplest model to achieve more complex and more functions, with wider industrial applications, lower costs, shorter development cycles, and wider applicability.

[0057] In model selection, biological neurons are screened and compared to obtain the advantages and controllability of Caenorhabditis elegans. Caenorhabditis elegans cells are selected to find the model and simulate it on Simulink which comes with MATLAB. The simulation process is the process of realizing the model. The model is the entirety of a single neuron, including connections and nodes. How data is transmitted, the influence and delay between the various structures are also taken into consideration. Since the model is large, it is more appropriate to use Simulink for simulation. Simulink simulation has good real-time performance, the software is easy to use, convenient and easy to understand, the devices are complete, and the simulation results are less affected.

[0058] Therefore, in a preferred embodiment, Figure 2 As shown, the present invention utilizes the known number of neurons and synaptic connections of C. elegans, combined with artificial intelligence disciplines, to create a virtual worm brain on MATLAB / Simulink, observe its reactions, and check the simulation results. Then, CMOS simulation is performed through multisim to create a hardware platform to form a micro-computing system. The embedded system is a micro-special-purpose computer embedded in the object system, which is simpler, more personalized, more operational, and has lower power consumption than ordinary computers.

[0059] S02: After obtaining a model whose simulation results are consistent with the physiological response results of C. elegans, draw a PCB schematic diagram corresponding to the model.

[0060] In a specific embodiment, the simulink hardware model diagram is as follows: Figure 3-7 As shown. Among them, Figure 3 A hardware model of a single neuron in Caenorhabditis elegans. Figure 4-7They are potassium channel hardware model, calcium channel hardware model, intracellular calcium gate potassium channel hardware model, and leakage current channel hardware model. The triangle in the figure is an amplifier, also known as a multiplier, the circle is an adder, and the square is mostly a constant module. In addition, it also includes integrators, dividers, etc. Specifically, Constant is a constant module, Gain is an amplifier, Integrator is an integrator, Divide is a divider, Product is a multiplier, Math Function is a digital function module, and Fcn is a custom function module.

[0061] Caenorhabditis elegans single neuron model:

[0062]

[0063] Among them, Cm is the membrane capacitance, V is the membrane voltage, that is, the potential difference between the two solutions separated by the membrane, Ica is the calcium current, IK is the potassium current, Isk is the intercellular calcium-gated potassium channel current, ILeak is the leakage current, Istimuli is the input direct current from the stimulus to the sensory neuron, Isyn is the current injected into the neuron by the chemical synapse, and Igap is the current injected into the neuron by the electrical synapse (gap junction).

[0064] The total membrane current of a C. elegans neuron is maintained by the sum of the inward and outward currents passing through it, which is generated by the propagation of ions across the cell membrane. The model shows that the current on the cell membrane can be reflected by other current models, including potassium ion current, intercellular calcium-gated potassium ion channel current, leakage current, and calcium ion current. Calcium ions are changes in calcium ions inside the cell. The current applied to the cell is the stimulus current Istimuli. The formula is interpreted as the change in action potential caused by the stimulus current. The total current is expressed as the product of capacitance multiplied by voltage over time.

[0065] Among them, various channels such as voltage-gated potassium channels, calcium-gated potassium channels, voltage-gated calcium channels and leak channels work together with calcium pumps to establish the membrane potential of neurons. The current is equal to the integral of the capacitance multiplied by the voltage over time.

[0066] like Figure 4 As shown, the potassium ion channel current model is: Ik = Gk nk 4 (V-Ek), the influence of equilibrium potential on potassium ions is reflected in Ek, Ek is the equilibrium potential of potassium ions, and the equilibrium potential is the potential difference between the inside and outside of the cell membrane under resting conditions. nk is the voltage-gated potassium channel, and the voltage-gated channel refers to a type of plasma membrane channel protein regulated by membrane potential. When the membrane potential changes, the channel opens or closes, that is, in the channel molecular structure, there are some genes or subunits that are sensitive to changes in transmembrane potential, and the membrane potential induces changes in the functional state of the entire channel molecule.

[0067] like Figure 6 As shown, the intercellular calcium-gated potassium ion channel current model is: Isk=Gsk msk(V-Esk), Esk is the equilibrium potential of the intercellular calcium-gated potassium ion channel, Gsk is the conductance of the intercellular calcium-gated potassium channel, and conductance is a physical quantity that describes the conductivity of a conductor, that is, a measure of the ease with which a conductor allows current to pass through it. The channel is affected by intracellular calcium ions.

[0068] like Figure 7 As shown, the leakage current ion channel current model is: Ileak=Gleak(V-Eleak), Eleak is the equilibrium potential of the leakage current channel, and GLeak is the conductance of the leakage current channel.

[0069] After selecting the model, perform simulation in simulink, predict the reaction results of the model and the relationship between the selected model and the organism itself, observe the reaction of the online simulation results and the biological model, and whether the predicted results are consistent. Use direct current Istimuli to stimulate Caenorhabditis elegans, observe the changes in the values ​​of various ion channels in a single neuron of Caenorhabditis elegans, detect the voltage value on the cell membrane, and the result is that the cell membrane voltage value is proportional to the stimulation current, that is, when the input current is a square wave, the output result is approximately a square wave state.

[0070] The second is circuit simulation, which reflects the software simulation results on circuit components:

[0071] Potassium current channel hardware simulation model: Ik = 9.75nk 4 (V-(-81)), the equilibrium potential of potassium current is selected as -81mV according to the needs, and the potassium conductance Gk parameter is selected as 9.75. The potassium current gating channel is nk, and the nk value is input by the parameter. The fourth power can select the exponential simplified circuit.

[0072] Intercellular calcium gate potassium channel current model: Isk = 0.25msk (V-(-80)), the intercellular calcium gate potassium ion equilibrium potential is selected as -80mV, the Gsk intercellular calcium gate potassium channel conductance parameter is selected as 0.25, the intercellular calcium gate potassium ion gated channel is controlled by the calcium ion cell concentration, and the value is input according to the calcium concentration parameter.

[0073] Leakage current ion channel current model: Ileak = 0.0525 (V-(-60)), the leakage current ion equilibrium potential is selected as -60mV, and the leakage current channel conductance parameter is selected as 0.0525. The leakage current has no gated channel and changes with the membrane voltage, showing a proportional function image. The leakage current increases as the membrane voltage increases.

[0074] After the above circuit simulation, a simulated circuit diagram is obtained, and then the PCB schematic diagram is drawn.

[0075] S03: According to the PCB schematic diagram, the hardware circuit of the model is constructed.

[0076] In a preferred embodiment, the scene setting uses the simulated circuit diagram in real life, and the activities of the nematode such as moving forward, moving backward, foraging, and thermotropism can all be reflected:

[0077] The Ik model is used in Caenorhabditis elegans to set the resting potential, allowing neurons to return from an excited state to a resting equilibrium state.

[0078] The Ik value range can be used as the forward, backward, and stop states of the car. The output Ik value greater than a certain parameter range is defined as forward movement, and less than a certain parameter range is defined as backward state. The stop state is quite special. Select the middle parameter and the car's movement state is similar to that of the Caenorhabditis elegans moving forward and backward.

[0079] Isk is affected by intracellular calcium concentration in Caenorhabditis elegans and changes with changes in intracellular calcium concentration.

[0080] Isk is set in the obstacle avoidance function. The influence of the input signal is controlled by the intracellular calcium concentration parameter, that is, the obstacle avoidance is set based on the distance range between the car and the front.

[0081] The scene application setting should be consistent with the model and biological response of the C. elegans cell itself, reflecting the unique action response of C. elegans and embodied in the car, that is, the car is controlled by the circuit model, and the car's forward, backward, obstacle avoidance, tracking and other actions are all simulated C. elegans itself. The car is an intelligent car based on the nerve cells of C. elegans. The nerve cells of C. elegans are the "brain" of the car, and the control module of the car is also C. elegans. On the one hand, the biological response of C. elegans cells can be further observed, which is helpful for biological brain science research and has certain physiological significance for neural computing science. On the other hand, the situation of biological control of the car can be used to promote the development of artificial intelligence and realize the true intelligence of artificial intelligence.

[0082] After setting up the scene application, you need to add the converter required by the scene application in multisim to convert the output value. The input value of the car's obstacle avoidance ultrasonic module is transmitted to Isk. If the input value is not within the value range of Isk, it needs to be converted to a reasonable value.

[0083] The circuit simulation and scene setting are completed, realizing the overall picture of the car:

[0084] Connect the motor and wheel modules, and test the car's motion status through the Ik model;

[0085] Assemble the servo and ultrasonic module and use the Isk model to detect whether the obstacle avoidance status meets the results;

[0086] Turn on the power supply to perform simulated operations and observe the experimental results and the intelligence of the car.

[0087] After the CMOS simulation neural network is realized, the hardware realization of the neural network can be completed by drawing the PCB schematic diagram, welding and connecting the various components. The completed module is the hardware module of the C. elegans itself, the visualization of the "brain" of the C. elegans, and the hardware module is assembled into the ultrasonic module and motor module of the car. The nerve cells of the C. elegans are used to control the action of the car. The actions realized by the car are all the behaviors of the nerve cells, without human control, or setting thresholds or functions in advance, etc. It has autonomous consciousness, which is reflected in the conscious actions and reactions of the C. elegans. The feature that is different from the traditional smart car is that the direction of the car is controlled by not a single-chip microcomputer, but a hardware module built by a biological neural network. This module can be defined as a chip, but it is not a chip in the traditional sense, but a nerve cell evolved from biological evolution, with consciousness, and the behavior is almost the same as that of the C. elegans, which is equivalent to making a C. elegans itself, but the morphology of the C. elegans is in the "driving state".

[0088] From the perspective of intelligence, it has been realized that more complex actions can be realized by using the smallest basic unit, with low cost, short development cycle, greater industrial significance, and it can also be made into a hardware platform for integrated circuits to form a micro-computing system. The embedded system is a micro-special computer embedded in the object system, which is simpler, more personalized, more operable, and has lower power consumption than ordinary computers. In turn, the research and simulation of biological models can further promote the development and progress of brain science, allowing us to better understand the subtle models and implementation methods of organisms.

[0089] In other embodiments, the leakage current can be set in other scene inputs. The smart car can automatically change the wiper speed according to the daily rain intensity. When the rain is light but affects driving, the wiper speed can be slower. When the rain is heavy, the wiper speed can be faster, but an upper limit value needs to be set to ensure that the wiper speed is not fast enough to affect normal driving.

[0090] After the scene is set up, you can add sensors, ultrasonic ranging modules, servo-controlled ultrasonic ranging, and the car's motor and wheel modules, etc., assemble the car's hardware modules, complete the overall appearance of the car, test the car to observe the phenomenon, and if it meets the expected results, complete the fully intelligent car based on C. elegans neurons.

[0091] The present invention provides a fully intelligent car based on the neurons of C. elegans. The core of the car is the hardware module of the neuron. The module is the control cell of C. elegans. It is installed on the car body to control the intelligent car. Its reaction ability and speed should be similar to those of C. elegans. Its reaction can complete simple actions without excessive human control and intervention. Further in-depth research can complicate the model. For example, it can not only simulate a single neuron, but also combine multiple neurons to complete multiple complex actions. The number of neurons can be selected according to the complexity of the action. Complex intelligent cars are widely used in industry and life business, with strong operability, short development cycle, low cost and easy production.

[0092] The above-mentioned embodiments only express several implementation methods of the present invention, and the description is relatively specific and detailed, but it cannot be understood as limiting the scope of the invention patent. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A fully intelligent car based on Caenorhabditis elegans neurons, characterized by: It includes a signal acquisition module, a signal processing module and an action execution module; The signal acquisition module is used to obtain the surrounding environment data of the fully intelligent car and transmit the surrounding environment data to the signal processing module; The signal processing module is a hardware circuit implemented based on the simulation of the neural network of Caenorhabditis elegans. The signal processing module is used to receive the surrounding environment data transmitted by the signal acquisition module, and generate action instructions according to the surrounding environment data, and control the action execution module to implement the action instructions; The action execution module is used to perform corresponding actions according to the action instruction; The steps of building the hardware circuit include: Use simulink in MATLAB software to build a model of the Caenorhabditis elegans neural network; After obtaining a model whose simulation results are consistent with the physiological response results of C. elegans, a PCB schematic diagram corresponding to the model is drawn; According to the PCB schematic diagram, build the hardware circuit of the model; The model of a single neuron of Caenorhabditis elegans is selected as: Wherein, Cm is the membrane capacitance, V is the membrane voltage, i.e., the potential difference between the two solutions separated by the membrane, Ica is the calcium current, IK is the potassium current, Isk is the intercellular calcium-gated potassium channel current, ILeak is the leakage current, Istimuli is the input direct current from the stimulus to the sensory neuron, i.e., the input direct current, Isyn is the current injected into the neuron by the chemical synapse, and Igap is the current injected into the neuron by the electrical synapse; The potassium channel current model is: I=Gk nk 4 (V-I) Where V is the membrane voltage, Ek is the potassium ion equilibrium potential, which is the potential difference between the inside and outside of the cell membrane under resting conditions, nk is the voltage-gated potassium channel, and Gk is the potassium ion channel conductance; The model of the intercellular calcium-gated potassium ion channel current is: Isk=Gsk msk(V-Esk) Wherein, V is the membrane voltage, Esk is the equilibrium potential of the intercellular calcium-gated potassium ion channel, msk is the voltage-gated channel of the intercellular calcium-gated potassium ion channel, and Gsk is the conductance of the intercellular calcium-gated potassium channel; The leakage current ion channel current model is: Ileak=Gleak(V-Eleak) Where V is the membrane voltage, Eleak is the equilibrium potential of the leakage current channel, and GLeak is the conductance of the leakage current channel.

2. The fully intelligent car based on the neurons of Caenorhabditis elegans according to claim 1, characterized in that: The signal acquisition module includes an ultrasonic rangefinder, and the action execution module includes a motor and a wheel; The ultrasonic rangefinder is used to detect the distance between the vehicle and the object in front; The signal processing module is used to generate an action instruction according to the distance detected by the ultrasonic rangefinder, and send the action instruction to the action execution module; the action instruction includes at least one of the following: forward, backward, stop; The motor and the wheel are used to perform corresponding actions according to the action instructions.

3. The fully intelligent car based on the neurons of Caenorhabditis elegans according to claim 1, characterized in that: The signal acquisition module includes a pressure sensor, and the action execution module includes a motor and a wiper; The pressure sensor is used to obtain the pressure and frequency of raindrops, and transmit the pressure and frequency data to the signal processing module; The signal processing module is used to generate an action instruction according to the pressure and frequency, and send the action instruction to the action execution module; the action instruction includes whether the wiper performs a reciprocating motion and the speed of the reciprocating motion; The motor and the wiper are used to perform corresponding actions according to the action instructions.

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