A light-sensing bionic leaf and a whole-plant light-sensing bionic system composed of the same

Abstract

This invention discloses a light-sensing biomimetic leaf and the resulting overall plant light-sensing biomimetic system, comprising: a miniature photosensitive chip for sensing ambient light intensity and direction; a micromotor connected to the miniature photosensitive chip, capable of driving the chip to change its orientation according to control commands; a connecting rod, one end of which is fixedly connected to the output shaft of the micromotor, and the other end of which is fixedly connected to the miniature photosensitive chip; and a control interface connected to the micromotor for receiving external control commands. Therefore, this invention uses a micromotor as the driving unit, achieving active programmable control of the leaf's orientation, overcoming the limitations of existing biomimetic plants that rely on passive material deformation, and enabling dynamic adjustment based on real-time sensing data, resulting in faster response speed and higher control precision.

Description

Technical Field

[0001] This invention relates to the field of intelligent biomimetic materials and embodied intelligence, specifically to a light-sensing biomimetic leaf and the overall light-sensing biomimetic system of the plant it comprises. Background Technology

[0002] The deep integration of bionics and artificial intelligence is giving rise to a new generation of intelligent systems. In nature, plants have evolved over millions of years to develop remarkable adaptability to the external environment, especially light. Plant leaves can sense the direction and intensity of light and adjust the leaf orientation through the directional growth or movement of the petiole, maximizing light energy capture efficiency. This integrated "perception-decision-execution" intelligent behavior provides an excellent bionic model for the design of artificial systems.

[0003] In the prior art, researchers have attempted to develop biomimetic plant systems. For example, a biomimetic intelligent artificial plant system with environmental adaptation and automatic response deformation has been disclosed in the prior art. It uses photostimulation-responsive polymer fiber materials to prepare biomimetic stems, branches and leaves, and realizes the response to light through the passive deformation of the material. Although this scheme realizes a variety of photoinduced movements (including light-facing movement, backlighting movement and photoinduced torsional movement), it depends on the inherent properties of the material itself and has the following technical defects: (1) The response behavior is predetermined by the material winding angle and cannot be programmed on demand; (2) The leaf orientation adjustment is passive and cannot be preset, lacking the ability to make active decisions; (3) Each leaf unit is independent of each other and cannot work together to form overall intelligence.

[0004] In addition, while existing photoelectric sensor arrays or micro encoder modules (such as Broadcom HEDS series, Nisshinbo NJL5820R series, etc.) can achieve light sensing or position detection, they are usually used as independent components and lack biomimetic integrated design, thus failing to simulate the distributed sensing and coordinated movement capabilities of plant canopies.

[0005] Therefore, how to combine active control technology, miniaturized drive mechanisms, and biomimetic morphological design to build an intelligent system with distributed perception and collaborative decision-making capabilities has become an urgent technical problem to be solved. Summary of the Invention

[0006] This invention aims to at least solve one of the technical problems existing in the prior art. Therefore, in response to the above-mentioned problems, the purpose of this invention is to provide a light-sensing bionic leaf and a plant-wide light-sensing bionic system composed of it. This system can simulate the light-sensing and orientation-adjusting capabilities of plant leaves by combining a micro-photosensitive chip with a programmable micro-motor. Furthermore, through the clustered and distributed deployment of multiple light-sensing bionic leaves, a plant-wide light-sensing bionic system with overall environmental adaptability can be constructed.

[0007] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows: In a first aspect, the present invention provides a light-sensing biomimetic leaf, comprising: Miniature photosensitive chips are used to sense the intensity and direction of ambient light; A micro motor, connected to the micro photosensitive chip, can drive the micro photosensitive chip to change its orientation according to control commands; A connecting rod, one end of which is fixedly connected to the output shaft of the micro motor, and the other end of which is fixedly connected to the micro photosensitive chip; A control interface, connected to the micro motor, is used to receive external control commands.

[0008] In some possible implementations, the miniature photosensitive chip is a miniature photoelectric sensor chip with a size no larger than 5mm × 5mm × 2mm.

[0009] In some possible implementations, the micro motor is a micro hollow cup motor or a micro stepper motor, capable of bidirectional rotation control, with a diameter not exceeding 4mm and a length not exceeding 10mm.

[0010] In some possible implementations, the connecting rod is 5-20 mm long and made of a lightweight, rigid material, enabling the micro photosensitive chip to be oriented within a range of ±90° under the drive of the micro motor.

[0011] Secondly, the present invention also provides a plant whole-plant light-sensing biomimetic system, characterized in that it comprises: Base; Multiple light-sensing bionic blades are arranged in an array on the base; The main controller is connected to the control interface of each of the light-sensing bionic blades and is used to send independent control commands to each of the micro motors and receive light-sensing data collected by the micro photosensitive chip. The power module is used to supply power to the main controller and each of the light-sensing bionic blades, wherein: The distribution pattern of the multiple light-sensing bionic leaves on the base simulates the aggregated distribution of natural plant canopies, with the density of the light-sensing bionic leaves in the central region being higher than that in the edge region, and / or the light-capturing optimization structure of the plant canopy is simulated by the change in the length of the connecting rod with position.

[0012] In some possible implementations, the main controller includes: The data acquisition unit is used to periodically acquire the light-sensing data of each of the micro photosensitive chips; A signal conditioning circuit is used to convert the voltage signal of the light-sensing data into light intensity data; The illumination analysis unit is used to perform fusion comparison analysis on the illumination intensity data, reconstruct the spatial distribution of ambient illumination using an interpolation fitting algorithm, and extract the spatial distribution features of ambient illumination based on the direction of maximum illumination intensity using a directional Gaussian weighted average algorithm. The decision control unit uses a PID control algorithm to generate a PWM control signal for each micro motor based on the spatial distribution characteristics of the ambient light, driving the micro photosensitive chip to rotate to the target orientation, thereby maximizing the light capture efficiency of the entire system.

[0013] In some possible implementations, a PID control algorithm is used to generate a PWM control signal for each micromotor, driving the micro photosensitive chip to rotate to the target orientation θ. i Where the target is oriented towards θ i The calculation formula is: θ i = α·θ sun + (1-α)·θ i,prev ; Where, θ sun Main illumination direction, θ i,prev The current orientation of the miniature photosensitive chip is α, which is the adjustment coefficient.

[0014] In some possible implementations, the main controller further includes a collaborative optimization unit, which is used to iteratively adjust the target orientation of each micro photosensitive chip based on its own perception and the state of adjacent micro photosensitive chips according to the current orientation and current light sensing data of each micro photosensitive chip using a distributed gradient optimization algorithm. The iterative adjustment aims to maximize the overall light capture efficiency and minimize mutual occlusion. After the algorithm converges, the orientation of each micro photosensitive chip forms an optimized configuration that adapts to the light distribution.

[0015] In some possible implementations, a distributed gradient optimization algorithm is used to iteratively adjust each of the micro-photosensitive chips based on its own sensing data and that of neighboring micro-photosensitive chips. The specific iterative process is as follows: 1) Initialize the orientation of each of the aforementioned micro-photosensitive chips to the current value; 2) Calculate the light intensity gradient for each of the micro-photosensitive chips; 3) Update the orientation of the miniature photosensitive chip according to the gradient; 4) Check for occlusion. If the occlusion coefficient of any two miniature sensing chips is greater than the threshold, increase the penalty. 5) Repeat steps 2) through 4) until convergence or the maximum number of iterations is reached.

[0016] In some possible implementations, a communication module is also included, which is used to upload the data collected by the data acquisition unit to an external device, or to receive control commands from an external device and transmit them to the main controller.

[0017] Because the present invention adopts the above technical solution, it has the following characteristics: 1. Active controllability: This invention uses a micro motor as the driving unit to realize active programming control of the orientation of the micro photosensitive chip, overcoming the limitations of existing biomimetic plants that rely on passive deformation of materials. It can dynamically adjust according to real-time sensing data, with faster response speed and higher control precision.

[0018] 2. Miniaturized integration: This invention achieves miniaturization of a single biomimetic blade by using a miniature photosensitive chip (millimeter level) and a micro motor (diameter ≤4mm), making it possible to deploy multiple blade clusters. The overall system size is controllable and highly adaptable.

[0019] 3. Distributed intelligence: This invention adopts a clustered deployment of multiple light-sensing bionic blades, combined with the collaborative optimization algorithm of the main controller, to realize an intelligent architecture that combines distributed sensing and centralized decision-making. It can sense the spatial distribution information of light and avoid mutual shading through collaborative adjustment. The overall light capture efficiency is better than that of independent adjustment schemes.

[0020] 4. Biomimetic morphology: This invention simulates the aggregation and distribution pattern of natural plant canopies, making the system highly biomimetic in morphology. At the same time, this distribution itself also conforms to the principle of optical optimization (the central area needs more leaves to capture direct light, and the edge area captures scattered light), thus achieving a unity of form and function.

[0021] 5. Scalability: The system of this invention adopts a modular design, with each light-sensing bionic blade being an independent module. The number of blades can be increased or decreased or the distribution pattern can be adjusted as needed to adapt to different application scenarios.

[0022] 6. Wide range of applications: This invention can be used in adaptive solar energy collection systems (such as building facades and mobile device charging), intelligent environmental monitoring networks (distributed light monitoring), biomimetic robot sensing systems, agricultural light simulation and control, and other fields.

[0023] In summary, this invention can be widely used in fields such as plant light adaptation pattern analysis, adaptive light energy harvesting, intelligent environmental monitoring, and distributed light sensing. Attached Figure Description

[0024] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. In the drawings: Figure 1 This is a schematic diagram of the structure of the light-sensing bionic leaf according to an embodiment of the present invention.

[0025] Figure 2 This is a schematic diagram of the overall plant light-sensing biomimetic system according to an embodiment of the present invention.

[0026] Figure 3 This is a block diagram of the overall architecture of the main controller in an embodiment of the present invention. Detailed Implementation

[0027] It should be understood that the terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “described” as used herein may also include the plural forms. The terms “comprising,” “including,” “containing,” and “having” are inclusive and therefore indicate the presence of the stated features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or combinations thereof. The method steps, processes, and operations described herein are not construed as requiring them to be performed in a particular order described or illustrated unless the order of performance is explicitly indicated. It should also be understood that additional or alternative steps may be used.

[0028] Although terms such as first, second, third, etc., may be used in this document to describe multiple elements, components, regions, layers, and / or segments, these elements, components, regions, layers, and / or segments should not be limited by these terms. These terms may be used only to distinguish one element, component, region, layer, or segment from another. Unless the context clearly indicates otherwise, terms such as "first," "second," and other numerical terms used herein do not imply order or sequence. Therefore, the first element, component, region, layer, or segment discussed below may be referred to as the second element, component, region, layer, or segment without departing from the teachings of the exemplary embodiments.

[0029] For ease of description, spatial relative terms may be used in the text to describe the relationship of one element or feature relative to another element or feature as shown in the figure. These relative terms include, for example, "inside," "outside," "middle," "outer," "below," "above," etc. Such spatial relative terms are intended to include different orientations of the device in use or operation, other than those depicted in the figure.

[0030] How to combine active control technology, miniaturized drive mechanisms, and biomimetic morphological design to construct an intelligent system with distributed perception and collaborative decision-making capabilities has become an urgent technical problem to be solved. This invention provides a light-sensing biomimetic leaf and the resulting plant-wide light-sensing biomimetic system. The light-sensing biomimetic leaf includes: a miniature photosensitive chip for sensing ambient light intensity and direction; a micro-motor mechanically connected to the miniature photosensitive chip, capable of driving the chip to change its orientation according to control commands; a connecting rod connecting the micro-motor and the miniature photosensitive chip; and a control interface for receiving external control signals. The plant-wide light-sensing biomimetic system includes a base, multiple light-sensing biomimetic leaves arranged in an array on the base, a main controller, and a power module. The main controller collects light-sensing data from each leaf, analyzes the ambient light distribution, and generates control commands to drive the leaves to collaboratively adjust their orientation, simulating the photoadaptive behavior of the plant canopy. Therefore, this invention constructs a plant-wide light-sensing bionic system with distributed perception and decision-making capabilities through the clustered deployment and collaborative optimization of multiple bionic leaves. It can be applied to fields such as plant light adaptation pattern analysis, adaptive solar energy collection, intelligent environmental monitoring, and bionic robots.

[0031] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the invention and to fully convey the scope of the invention to those skilled in the art.

[0032] Example 1: As Figure 1 As shown, the light-sensing bionic leaf provided in this embodiment includes: Miniature photosensitive chip 1, used to sense the intensity and direction of ambient light; The micro motor 2 is connected to the micro photosensitive chip 1, enabling the micro photosensitive chip 1 to change its orientation according to control commands. One end of the connecting rod 3 is fixedly connected to the output shaft of the micro motor 2, and the other end is fixedly connected to the micro photosensitive chip 1; The control interface is connected to the micro motor 2 and is used to receive external control signals.

[0033] In some preferred embodiments of the present invention, the miniature photosensitive chip 1 may be a miniature photoelectric sensor chip with a size not greater than 5mm×5mm×2mm. It is preferred to use the NJL5820R series reflective photoelectric sensor chip or its equivalent chip, which is used as an example, but is not limited thereto.

[0034] In some preferred embodiments of the present invention, the micro motor 2 can be a micro hollow cup motor or a micro stepper motor, which can realize bidirectional rotation control, and its diameter is no greater than 4mm and its length is no greater than 10mm.

[0035] In some preferred embodiments of the present invention, the length of the connecting rod 3 can be 5-20 mm, and it is made of a lightweight rigid material, so that the micro photosensitive chip 1 can achieve orientation adjustment within a range of ±90° under the drive of the micro motor 2.

[0036] In some preferred embodiments of the present invention, the control interface includes a power line and a signal line. The power line is used to connect the miniature photosensitive chip 1 and the micro motor 2 for power supply, and the signal line is used to receive PWM control signals or digital control commands for signal transmission.

[0037] Example 2: Figure 2 As shown, this embodiment also provides a plant whole-plant light-sensing biomimetic system, including: Base 4; Multiple light-sensing bionic blades 5 are arranged in an array on the base 4; The main controller is connected to the control interface of each light-sensing bionic blade 5, and is used to send independent control commands to each micro motor 2 and receive light-sensing data collected by each micro photosensitive chip 5. The power module is used to power the main controller and each light-sensing bionic blade 5, wherein: The distribution pattern of multiple light-sensing biomimetic leaves 5 on the base 4 simulates the aggregated distribution of natural plant canopies, including: the leaf density in the central region is higher than that in the edge region, and / or the length of the connecting rod 3 varies with position to simulate the light-harvesting optimization structure of the plant canopy.

[0038] In a preferred embodiment of the present invention, such as Figure 3 As shown, the overall architecture of the main controller includes a perception layer, a decision layer, a communication layer, and an execution layer. Specifically, the main controller includes: The data acquisition unit is used to periodically acquire the light-sensing data of each miniature photosensitive chip 1 through a 12-bit ADC at a sampling rate of 100Hz. The sampling rate is used as an example, but is not limited to this. The signal conditioning circuit is used to convert the voltage signal of the acquired light sensor data into light intensity data. The illumination analysis unit is used to fuse and compare the above illumination intensity data, and to reconstruct the spatial distribution of ambient illumination using interpolation fitting algorithms such as cubic spline interpolation fitting algorithms. Based on the direction of maximum illumination intensity, the spatial distribution features of ambient illumination are extracted using a directional Gaussian weighted average algorithm, including the main illumination direction and illumination intensity gradient. The decision control unit is used to generate PWM control signals for each micro motor 2 based on the analysis results of the illumination analysis unit and the PID control algorithm, so as to drive the micro photosensitive chip 1 to rotate to the target orientation, thereby maximizing the light capture efficiency of the overall system.

[0039] Furthermore, the main controller also includes a collaborative optimization unit, which executes a distributed gradient optimization algorithm based on the current orientation and current light sensing data of each micro photosensitive chip 1 to iteratively adjust the target orientation in order to maximize the overall light capture efficiency and minimize mutual occlusion; after the algorithm converges, the orientation of each micro photosensitive chip 1 forms an optimized configuration that adapts to the light distribution.

[0040] In a preferred embodiment of the present invention, the plant whole-system light-sensing bionic system further includes a communication module for uploading the collected light-sensing data to an external device, or for receiving external control commands from a host computer via a host computer protocol line.

[0041] In a preferred embodiment of the present invention, the number of light-sensing bionic leaves 5 can be 30, which are distributed in a spiral or layered manner on the base 1 to simulate the canopy structure of plants such as sunflowers. The number is not limited to this example and can be determined according to specific circumstances.

[0042] In summary, the working process of the plant-based bionic light-sensing system of the present invention is as follows: In the initial state, the micro-photosensitive chips of each bionic light-sensing leaf 5 are oriented towards a preset initial direction. When the ambient light conditions change, each micro-photosensitive chip 1 collects light intensity data under the current orientation in real time and transmits the data to the main controller. The main controller performs fusion analysis on the multi-channel light-sensing data and uses a directional Gaussian weighted average algorithm based on the direction of maximum light intensity to determine information such as the main light direction and the uniformity of light distribution in the environment. Based on the analysis results, the main controller sends independent control commands to each micro-motor 2 to drive each micro-photosensitive chip 1 to rotate to the optimal orientation. The optimal orientation is determined by a distributed gradient descent algorithm, so that the total light energy captured by the overall system is maximized or reaches the preset light collection target. In this process, the plant-based bionic light-sensing system can realize the core feature of embodied intelligence: through real-time interaction between the physical body (bionic light-sensing leaf) and the environment (light sensing), and by utilizing the embedded intelligent algorithm (light analysis and decision control), adaptive behavior (leaf orientation adjustment) is generated, thereby optimizing the overall light capture efficiency. Therefore, by deploying 30 miniature photosensitive chips 5 in a cluster, the present invention enables the system to sense the spatial distribution gradient of light and simulate the dynamic light adaptation behavior of the plant canopy through coordinated regulation.

[0043] The following detailed embodiments illustrate the preparation of the light-sensing bionic leaf of the present invention and the construction and application of the whole-plant light-sensing bionic system.

[0044] I. Preparation of a single light-sensing bionic leaf.

[0045] Specifically, this embodiment provides a method for preparing a light-sensing biomimetic leaf, the process of which is as follows: Step 1: Select miniature photosensitive chip 1: In this embodiment, the Nisshinbo NJL5820R-TE4 reflective photoelectric sensor chip is selected. Its size is 2.6mm×2.5mm×0.8mm. It has a built-in photosensitive element and signal processing circuit, and can output an electrical signal proportional to the light intensity. The chip has an operating voltage of 2.7-5.5V, low power consumption, and is suitable for miniaturization integration.

[0046] Step 2, Select Micro Motor 2: In this embodiment, a miniature hollow cup motor with a diameter of 4mm (such as the Namiki 04C series), a length of 8mm, a rated voltage of 3V, and an unloaded speed of 12000rpm is selected. Equipped with a miniature reducer (reduction ratio 1:30), the output shaft speed is reduced to 400rpm, increasing torque and enabling stable rotation of the miniature photosensitive chip. The micro-motor has a built-in magneto-electric encoder, enabling closed-loop position control with a rotational accuracy of ±1°.

[0047] Step 3: Make connecting rod 3: In this embodiment, a 10mm long connecting rod 3 is fabricated using 3D printing technology. The material used is photosensitive resin, which is lightweight (approximately 0.1g) and has good rigidity. One end of the connecting rod 3 is provided with a mounting hole that matches the output shaft of the micro motor 2, and the other end is provided with a flat surface for attaching the micro photosensitive chip 1.

[0048] Step 4, Assembly: In this embodiment, the connecting rod 3 is fixedly connected to the output shaft of the micro motor 2 (using an interference fit or adhesive bonding), and then the micro photosensitive chip 1 is pasted onto the flat surface at the end of the connecting rod 3, ensuring that the photosensitive surface faces the predetermined direction. The flexible circuit board (FPC) connecting the micro motor 2 and the micro photosensitive chip 1 is arranged along the connecting rod 3 to avoid interfering with rotation.

[0049] Step 5: Connect the control interface: In this embodiment, the power lines and encoder signal lines of the micro motor 2 and the power lines and signal lines of the micro photosensitive chip 1 are integrated into the same flexible cable, with a standard connector (such as a 1.0mm pitch FPC connector) leading out at the end for connection with the main controller.

[0050] In summary, the light-sensing bionic blade prepared in this embodiment has an overall height (from the bottom of the motor to the top of the micro photosensitive chip) of about 18 mm, a width (at the micro photosensitive chip) of about 3 mm, and a weight of less than 1 g, and can achieve rotation control within a range of ±90°.

[0051] II. This embodiment provides the construction of a plant-wide light-sensing biomimetic system.

[0052] Specifically, this embodiment provides the construction of a whole-plant light-sensing biomimetic system with 30 leaves (taking this as an example, but not limited to this), the process of which is as follows: Step 1, Design base 4: In this embodiment, the base 4 adopts a hemispherical structure with a diameter of 100mm, made of ABS plastic, and manufactured by 3D printing. The surface of the base 4 has 30 mounting positions, each containing a micro-motor mounting base and a flexible cable interface. The distribution of the mounting positions simulates the clustered distribution pattern of natural plant canopies: 12 mounting positions are set in the central area (top), with a denser distribution; 10 mounting positions are set in the middle area; and 8 mounting positions are set in the edge area (bottom), with a sparser distribution. Simultaneously, the connecting rods 3 have different lengths in different areas: the connecting rod length in the central area is 8mm (simulating the short petioles at the top of the canopy), and the connecting rod length in the edge area is 15mm (simulating the long petioles at the outer edge of the canopy) to optimize the light-harvesting angle.

[0053] Step 2: Install light-sensing bionic blades: In this embodiment, the 30 light-sensing bionic blades 5 are installed in their respective mounting positions, and the micro motors 2 are fixed with screws or clips. The flexible ribbon cable is connected to the interface inside the base 4. The initial orientation of each micro photosensitive chip 1 is uniformly set to vertically upward (i.e., the plane of the micro photosensitive chip 1 is parallel to the cutting plane of the base 4).

[0054] Step 3: Connect the main controller: In this embodiment, the main controller uses an STM32F407 series microcontroller as its core processor, with a main frequency of 168MHz. It has a multi-channel ADC interface and PWM output capability. The main controller includes the following functional modules: Data acquisition unit: Acquires voltage signals from 30 micro photosensitive chips at a sampling rate of 100Hz via a 12-bit ADC.

[0055] Signal conditioning circuit: used to convert voltage signals into light intensity values.

[0056] Illumination Analysis Unit: It performs fusion analysis on 30 channels of illumination data, reconstructs the spatial distribution of ambient illumination using a cubic spline interpolation fitting algorithm, and extracts the spatial distribution features of ambient illumination based on the direction of maximum illumination intensity using a directional Gaussian weighted average algorithm, identifying the main illumination direction (the direction of maximum illumination intensity) and illumination gradient.

[0057] Decision control unit: Based on the PID control algorithm, a PWM control signal is generated for each micro-motor 2 to drive the micro-photosensitive chip 1 to rotate to the target orientation. The formula for calculating the target orientation is: θ i = α·θ sun + (1-α)·θ i,prev ; Where, θ sun Main illumination direction, θ i,prev The current orientation of the miniature photosensitive chip is α, which is an adjustment coefficient (0≤α≤1) used to balance tracking speed and stability.

[0058] Collaborative optimization unit: Employing a distributed gradient descent algorithm, each micro-photosensitive chip 1 iteratively adjusts its target orientation based on its own perceived light intensity and the orientation information of adjacent leaves to maximize overall light capture efficiency and minimize mutual occlusion. After algorithm convergence, the orientation of each micro-photosensitive chip 1 forms an optimized configuration adapted to the light distribution. Specifically, the distributed gradient descent algorithm iteratively adjusts the orientation of each micro-photosensitive chip 1 based on its own perception and the state of adjacent leaves. The specific iterative process is as follows: 1) Initialize the orientation of each miniature photosensitive chip 1 to the current value; 2) Calculate the light intensity gradient for each miniature photosensitive chip 1; 3) Update the orientation of the miniature photosensitive chip 1 according to the gradient; 4) Check for occlusion: If the occlusion coefficient of any two micro photosensitive chips 1 is greater than the threshold, the penalty is increased. For example, the angle between the two micro photosensitive chips is increased by 20%. If such a dead loop is detected on both sides of a certain micro photosensitive chip, the angle is increased by another 20% on one side. 5) Repeat steps 2) through 4) until convergence or the maximum number of iterations is reached: Step 4: Integration of Power Supply and Communication In this embodiment, the power module is powered by a 3.7V lithium battery, which outputs 3.3V via a voltage regulator circuit to power the main controller and the micro photosensitive chip 1, and 3.0V to power the motor. The communication module uses Wi-Fi (ESP8266) to achieve a wireless connection with the host computer, which can upload real-time illumination data and blade orientation status, and can also receive external control commands (such as manually setting the orientation of each blade).

[0059] III. System Workflow and Testing.

[0060] The test scenario in this embodiment is as follows: The constructed plant-based bionic light-sensing system with 30 micro-photosensitive chips is placed in an experimental environment with an adjustable light source. The initial light source is top light (vertical illumination), and each micro-photosensitive chip is oriented vertically upwards. The light intensity values ​​of the 30 micro-photosensitive chips in the initial state are recorded, and the sum is denoted as P0. The test process is as follows: Step 1, Response to changes in illumination: In this embodiment, the light source direction is adjusted to be incident at a 45° angle. The system detects changes in the light intensity of each micro-photosensitive chip: the micro-photosensitive chip facing the light source (on the base side) receives increased illumination, while the micro-photosensitive chip facing away from the light source receives decreased illumination. The illumination analysis unit of the main controller identifies the main illumination direction as 45°.

[0061] Step 2, Adjusting the orientation of the miniature photosensitive chip: In this embodiment, the decision control unit generates the initial target orientation of each micro-photosensitive chip 1 based on the main illumination direction (uniformly adjusted to face the 45° direction). The PID controller drives each micro-motor 2 to rotate, and the orientation adjustment of the 30 micro-photosensitive chips 1 is completed within 3 seconds. After adjustment, the normal direction of all micro-photosensitive chips points to the 45° direction. The total illumination intensity P1 at this time is measured, and P1 is about 40% higher than P0, verifying the system's adaptability to changes in illumination direction.

[0062] Step 3, Collaborative Optimization: In this embodiment, the system enters a collaborative optimization unit, where each micro-photosensitive chip 1 fine-tunes its position based on the positions of adjacent micro-photosensitive chips 1 and the light intensity it senses. After 5 seconds of iterative optimization, the micro-photosensitive chips 1 are oriented to form an optimized distribution that adapts to the canopy structure: the leaves in the central region remain facing 45°, while the leaves in the edge regions are slightly tilted outward (increasing by 5-10°) to capture more scattered light and reduce shading of the central leaves. The total light intensity P2 after optimization is measured, and P2 is 12% higher than P1, verifying the effectiveness of the collaborative optimization.

[0063] Step 4, Adaptation to Extreme Light: In this embodiment, the light source intensity is adjusted to an extremely high value (simulating a strong light environment). The system detects that the light intensity of some leaves exceeds a threshold (preset to 80% of the saturation value of the micro-photosensitive chip). The collaborative optimization unit triggers a light-avoidance strategy: by controlling the connecting rod 3, the orientation of the affected leaves is adjusted to deviate from the direction of the light source to reduce excessive light, while the surrounding leaves adjust accordingly to compensate for light capture. After adjustment, the light intensity of each leaf returns to below the threshold, and the total light capture remains above 85% of P1, verifying the system's environmental adaptability.

[0064] In summary, the light-sensing biomimetic leaf and the overall light-sensing biomimetic system of the plant composed of this invention have broad application prospects: Adaptive solar energy harvesting: The system is scaled up and applied to solar panel arrays on building exteriors, enabling each solar panel to dynamically adjust its orientation according to the sun's position, thereby improving power generation efficiency. The multi-blade distributed design can adapt to complex lighting conditions such as local shading.

[0065] Intelligent environmental monitoring: The system can be deployed as a distributed light sensor network in farmland, forest or urban environments to monitor light distribution in real time and provide data support for agricultural management and urban planning.

[0066] Bionic robot perception system: The miniaturized system is integrated on the top of the robot, enabling the robot to sense the distribution of ambient light and assist in localization and navigation.

[0067] Space applications: Simulating the folding and unfolding mechanism of plant canopies, we designed retractable biomimetic solar panels to save launch space. After entering orbit, the panels automatically unfold and adjust their orientation according to the sun's direction.

[0068] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In the description of this specification, the terms "a preferred embodiment," "furthermore," "specifically," "in this embodiment," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the embodiments in this specification. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0069] 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 light-sensing biomimetic leaf, characterized in that, include: Miniature photosensitive chips are used to sense the intensity and direction of ambient light; A micro motor, connected to the micro photosensitive chip, can drive the micro photosensitive chip to change its orientation according to control commands; A connecting rod, one end of which is fixedly connected to the output shaft of the micro motor, and the other end of which is fixedly connected to the micro photosensitive chip; A control interface, connected to the micro motor, is used to receive external control commands.

2. The light-sensing bionic leaf according to claim 1, characterized in that, The micro photosensitive chip is a micro photoelectric sensor chip with a size of no more than 5mm×5mm×2mm.

3. The light-sensing bionic leaf according to claim 1, characterized in that, The micro motor is a micro hollow cup motor or a micro stepper motor, which can achieve bidirectional rotation control. Its diameter is no more than 4mm and its length is no more than 10mm.

4. The light-sensing bionic leaf according to claim 1, characterized in that, The connecting rod is 5-20mm long and made of lightweight rigid material, which enables the micro photosensitive chip to be oriented within a range of ±90° under the drive of the micro motor.

5. A biomimetic system for whole-plant light sensing, characterized in that, include: Base; Multiple light-sensing bionic blades as described in any one of claims 1 to 4, wherein the multiple light-sensing bionic blades are arranged in an array on the base; The main controller is connected to the control interface of each of the light-sensing bionic blades and is used to send independent control commands to each of the micro motors and receive light-sensing data collected by the micro photosensitive chip. The power module is used to supply power to the main controller and each of the light-sensing bionic blades, wherein: The distribution pattern of the multiple light-sensing bionic leaves on the base simulates the aggregated distribution of natural plant canopies, with the density of the light-sensing bionic leaves in the central region being higher than that in the edge region, and / or the light-capturing optimization structure of the plant canopy is simulated by the change in the length of the connecting rod with position.

6. The plant whole-body light-sensing biomimetic system according to claim 5, characterized in that, The main controller includes: The data acquisition unit is used to periodically acquire the light-sensing data of each of the micro photosensitive chips; A signal conditioning circuit is used to convert the voltage signal of the light-sensing data into light intensity data; The illumination analysis unit is used to perform fusion comparison analysis on the illumination intensity data, reconstruct the spatial distribution of ambient illumination using an interpolation fitting algorithm, and extract the spatial distribution features of ambient illumination based on the direction of maximum illumination intensity using a directional Gaussian weighted average algorithm. The decision control unit uses a PID control algorithm to generate a PWM control signal for each micro motor based on the spatial distribution characteristics of the ambient light, driving the micro photosensitive chip to rotate to the target orientation, thereby maximizing the light capture efficiency of the entire system.

7. The plant whole-body light-sensing biomimetic system according to claim 6, characterized in that, A PID control algorithm is used to generate a PWM control signal for each micromotor, driving the micro photosensitive chip to rotate to the target orientation θ. i Where the target is oriented towards θ i The calculation formula is: i i = a·θ sun + (1-a)·θ i,prev ; Where, θ sun Main illumination direction, θ i,prev The current orientation of the miniature photosensitive chip is α, which is the adjustment coefficient.

8. The plant whole-body light-sensing biomimetic system according to claim 6, characterized in that, The main controller further includes a collaborative optimization unit, which is used to iteratively adjust the target orientation of each micro photosensitive chip based on its own perception and the state of adjacent micro photosensitive chips according to the current orientation and current light sensing data of each micro photosensitive chip. The iterative adjustment aims to maximize the overall light capture efficiency and minimize mutual occlusion. After the algorithm converges, the orientation of each micro photosensitive chip forms an optimized configuration that adapts to the light distribution.

9. The plant whole-body light-sensing biomimetic system according to claim 8, characterized in that, Based on a distributed gradient optimization algorithm, each of the micro-photosensitive chips is iteratively adjusted according to its own sensing and that of the adjacent micro-photosensitive chips. The specific iterative process is as follows: 1) Initialize the orientation of each of the aforementioned micro-photosensitive chips to the current value; 2) Calculate the light intensity gradient for each of the micro-photosensitive chips; 3) Update the orientation of the miniature photosensitive chip according to the gradient; 4) Check for occlusion. If the occlusion coefficient of any two miniature sensing chips is greater than the threshold, increase the penalty. 5) Repeat steps 2) through 4) until convergence or the maximum number of iterations is reached.

10. The plant whole-body light-sensing biomimetic system according to claim 6, characterized in that, It also includes a communication module, used to upload the data collected by the data acquisition unit to an external device, or to receive control commands from an external device and transmit them to the main controller.

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