Invertebrate directional control method, apparatus, device, and storage medium

Abstract

The application discloses an invertebrate directional control method, device, equipment and storage medium. The method comprises the following steps: acquiring multi-dimensional animal features and multi-view images of a target invertebrate in a target area by a feature acquisition device to obtain current animal features and a target animal image sequence of at least two views; determining a target animal category of the target invertebrate according to the current animal features by an animal recognition device, and sending the target animal category to a data processing device when it is determined that the target animal category meets animal management conditions; determining target directional control parameters of the target invertebrate according to the current animal features, the target animal image and the target animal category by the data processing device, and sending the target directional control parameters to a directional control device; and performing directional control on the target invertebrate according to the target directional control parameters by the directional control device. The above scheme improves the accuracy and reliability of animal control.

Description

Technical Field

[0001] This application relates to the fields of computer technology and animal control engineering technology, and particularly to the fields of multimodal perception, target recognition and intelligent control technology. Specifically, it relates to a method, apparatus, device and storage medium for intelligent identification, localization and orientation control of invertebrates. Background Technology

[0002] Control measures for harmful invertebrates mainly include chemical control, animal control, and traditional physical control. However, conventional control methods all have obvious drawbacks. For example, chemical control is effective quickly, but it can easily cause environmental pollution, bioaccumulation in animals, and drug resistance, and may also have adverse effects on human health and animal diversity. Animal control is somewhat eco-friendly, but it has a long time to take effect, is applicable to a limited range of species, and its effectiveness is easily affected by environmental conditions.

[0003] To overcome the shortcomings of conventional prevention and control methods, machine vision-based pest identification technology and laser or acoustic physical control technology have been introduced. However, machine vision-based pest identification technology is mostly used for monitoring and early warning. Its output results are usually only the species information and confidence level of the identified species, or two-dimensional or simple three-dimensional position information, without forming an effective linkage with the subsequent directional control execution system. Laser or acoustic physical control technology mostly uses preset and fixed control parameters, lacks the ability to adapt to different species, body sizes and behavioral states, and the control process is mostly open-loop, making it difficult to avoid accidental injury to non-target animals. Summary of the Invention

[0004] This application provides a method, apparatus, device, and storage medium for the orientation control of invertebrates, in order to improve the accuracy and reliability of orientation control of invertebrates.

[0005] According to one aspect of this application, a method for directional control of invertebrates is provided, which is applied to a directional control system; the directional control system includes a feature acquisition device, an animal identification device, a data processing device, and a directional control device; the feature acquisition device is communicatively connected to the animal identification device and the data processing device respectively; the data processing device is communicatively connected to the animal identification device and the directional control device respectively; the method includes: The feature acquisition device performs multi-dimensional animal feature acquisition and multi-view image acquisition on the target invertebrate in the target area to obtain the current animal features of the target invertebrate and the target animal image sequence from at least two views, and sends the current animal features to the animal recognition device; wherein, the current animal features include morphological features, kinematic features and optical behavioral features; The animal identification device determines the target animal category of the target invertebrate based on the current animal characteristics, and sends the target animal category to the data processing device if the identified target animal category meets the animal management conditions. The data processing device acquires the current animal features and the target animal image sequence from the feature acquisition device, and determines the target orientation control parameters of the target invertebrate based on the current animal features, the target animal image sequence and the target animal category, and sends the target orientation control parameters to the orientation control device. The directional control device performs directional control on the target invertebrate according to the target directional control parameters.

[0006] According to another aspect of this application, an invertebrate orientation control device is provided, the device being configured in an orientation control system; the orientation control system includes a feature acquisition device, an animal identification device, a data processing device, and an orientation control device; the feature acquisition device is communicatively connected to the animal identification device and the data processing device respectively; the data processing device is communicatively connected to the animal identification device and the orientation control device respectively; the device includes: The data acquisition module is used to acquire multi-dimensional animal features and multi-view images of target invertebrates in the target area through the feature acquisition device, obtain the current animal features of the target invertebrates and at least two viewpoint image sequences of the target animals, and send the current animal features to the animal recognition device; wherein, the current animal features include morphological features, kinematic features and optical behavioral features; The category determination module is used to determine the target animal category of the target invertebrate based on the current animal characteristics using the animal identification device, and to send the target animal category to the data processing device if the identified target animal category meets the animal management conditions. The parameter determination module is used to acquire the current animal features and the target animal image sequence from the feature acquisition device through the data processing device, and determine the target orientation control parameters of the target invertebrate based on the current animal features, the target animal image sequence and the target animal category, and send the target orientation control parameters to the orientation control device; The animal control module is used to perform orientation control on the target invertebrate according to the target orientation control parameters through the orientation control device.

[0007] According to another aspect of this application, an electronic device is provided, the electronic device comprising: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement any of the invertebrate orientation control methods provided in the embodiments of this application.

[0008] According to another aspect of this application, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements any of the invertebrate orientation control methods provided in the embodiments of this application.

[0009] According to another aspect of this application, a computer program product is provided, including a computer program that, when executed by a processor, implements any of the invertebrate orientation control methods provided in the embodiments of this application.

[0010] This application utilizes a feature acquisition device to collect multi-dimensional animal features and multi-view images of target invertebrates in a target area, obtaining the current animal features and at least two image sequences of the target invertebrates from different perspectives. The current animal features are then sent to an animal identification device. These current animal features include morphological features, kinematic features, and optical behavioral features. Based on the current animal features, the animal identification device determines the target animal category of the invertebrate. If the identified target animal category meets the animal management conditions, the target animal category is sent to a data processing device. The data processing device retrieves the current animal features and the target animal image sequence from the feature acquisition device, and based on these features, the target animal image sequence, and the target animal category, determines the target orientation control parameters for the invertebrate. These parameters are then sent to an orientation control device. The orientation control device then performs orientation control on the target invertebrate based on these parameters. This scheme, based on the multimodal features of invertebrates, performs category identification and orientation control parameter decision-making, which helps improve the accuracy and reliability of invertebrate identification. Attached Figure Description

[0011] Figure 1 This is a flowchart of a method for directional control of invertebrates according to Embodiment 1 of this application; Figure 2 This is a flowchart of a method for directional control of invertebrates according to Embodiment 2 of this application; Figure 3 This is a schematic diagram of the structure of an invertebrate orientation control device according to Embodiment 3 of this application; Figure 4 This is a schematic diagram of the structure of an electronic device that implements the invertebrate orientation control method of Embodiment 4 of this application. Detailed Implementation

[0012] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0013] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0014] Furthermore, it should be noted that the collection, storage, use, processing, transmission, provision, and disclosure of relevant data such as current animal characteristics and target animal image sequences involved in the technical solution of this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0015] Example 1 Figure 1 This is a flowchart of an invertebrate orientation control method according to Embodiment 1 of this application. This embodiment is applicable to situations involving animal identification and orientation control of invertebrates, and can be executed by an invertebrate orientation control device. This device can be implemented in hardware and / or software and can be configured in a computer device, such as an orientation control system. The orientation control system includes a feature acquisition device, an animal identification device, a data processing device, and an orientation control device. The feature acquisition device is communicatively connected to both the animal identification device and the data processing device. The data processing device is also communicatively connected to both the animal identification device and the orientation control device. Figure 1 As shown, the method includes: S110. Using a feature acquisition device, multi-dimensional animal feature acquisition and multi-view image acquisition are performed on the target invertebrate in the target area to obtain the current animal features of the target invertebrate and the target animal image sequence from at least two views, and the current animal features are sent to the animal recognition device; wherein, the current animal features include morphological features, kinematic features and optical behavioral features.

[0016] Feature acquisition equipment refers to tools in a directional control system used to collect, record, and analyze the characteristics of invertebrates. These can include cameras, sensors, laser scanners, etc., capable of capturing multiple characteristic information of invertebrates under different conditions. The target area refers to the geographical location or environment where invertebrates are observed and recorded. Target invertebrates are animals without a spine, typically including insects, mollusks, and crustaceans. Multidimensional animal characteristics refer to the features that describe and analyze an animal from multiple aspects, including its morphology, behavior, and physiological characteristics. Current animal characteristics refer to the characteristics of an animal recorded at a specific time or under specific conditions; these characteristics can be static (e.g., morphological features) or dynamic (e.g., kinematic features and optical behavioral features), used for real-time monitoring and analysis of the target animal's state. Morphological features refer to the shape, structure, and appearance characteristics of an animal, including size, proportion, color, and texture. Kinematic features refer to the behavior and patterns of an animal during movement, including speed, direction, and mode of movement. Optical behavioral features are the characteristics of scattered light signals caused by the flapping of wings or movement of invertebrates. Animal identification equipment refers to tools used to identify and classify animals.

[0017] Optionally, the feature acquisition device includes a multi-view image acquisition component and an optical scattering signal acquisition component; correspondingly, the multi-view image acquisition component acquires images of the target invertebrate in the target area from different perspectives to obtain at least two perspective image sequences of the target invertebrate, and determines the morphological and kinematic features of the target invertebrate based on the image sequences; the optical scattering signal acquisition component acquires scattered light from the target invertebrate in the target area to obtain the optical behavioral features of the target invertebrate.

[0018] Among them, a multi-view image acquisition component refers to a device specifically designed to capture images of a target animal from multiple angles; this component typically consists of multiple cameras that can simultaneously or sequentially capture images of the target animal, thereby obtaining a sequence of images from different perspectives. An optical scattering signal acquisition component refers to a device used to capture the scattered light signals generated when an animal interacts with light; these signals can reveal the animal's structural characteristics and optical behavior.

[0019] S120. Based on the current animal characteristics, determine the target animal category of the target invertebrate using animal identification equipment, and if the identified target animal category meets the animal management conditions, send the target animal category to the data processing equipment.

[0020] The target animal category refers to the specific classification of invertebrates identified by animal identification equipment, such as a particular insect, mollusc, or other invertebrate. Animal management conditions are used to determine whether an animal is endangered or requires protection; if not, the conditions are met to prevent accidental harm to endangered invertebrates or disruption of the ecological balance. Data processing equipment refers to devices used to receive, store, and analyze invertebrate-related information.

[0021] Optionally, the animal identification device determines the candidate animal category and the category confidence of the target invertebrate based on the morphological and kinematic characteristics of the current animal characteristics; and when the animal identification device identifies a candidate animal category that meets the animal identification conditions, the candidate animal category is determined as the target animal category of the target invertebrate.

[0022] Here, candidate animal categories refer to possible invertebrate classifications initially identified by animal identification equipment. Category confidence is a numerical value representing the probability or degree of certainty that a candidate animal category will be confirmed. Animal identification criteria refer to the standards that must be met to confirm a candidate animal category as the target animal category. These criteria are established through extensive experimentation and are pre-set based on actual conditions or experience; for example, the category confidence might be greater than or equal to a preset confidence threshold.

[0023] In one optional implementation, when the confidence level of the identified category does not meet the animal identification conditions, the animal identification device extracts feature vectors from morphological features, kinematic features, and optical behavioral features respectively to obtain morphological feature vectors, kinematic feature vectors, and optical behavioral feature vectors. The animal identification device then concatenates the morphological feature vectors, kinematic feature vectors, and optical behavioral feature vectors to obtain the multimodal animal features of the target invertebrate. Based on the multimodal animal features, the animal identification device determines the target animal category of the target invertebrate.

[0024] Among them, morphological feature vectors are vectors formed by extracting morphological features of the target invertebrate, usually composed of multiple values ​​representing different morphological attributes. Kinematic feature vectors are vectors formed by extracting the movement features of the target invertebrate, containing values ​​of multiple indicators related to animal movement. Optical behavior feature vectors are vectors formed by extracting the optical behavior features of the target invertebrate, containing values ​​related to light response. Multimodal animal features are comprehensive features formed by splicing multiple feature vectors, encompassing information on morphology, movement, and optical behavior.

[0025] For example, the animal identification device first identifies the target invertebrate based on kinematic and morphological features, outputting candidate animal categories and their corresponding category confidence scores. When the animal identification device detects that the category confidence score is below a preset threshold or that features such as high-speed movement, severe occlusion, or small size are detected in the kinematic and morphological features, optical behavioral features are further introduced as auxiliary discrimination information. The animal identification device extracts corresponding feature vectors from the kinematic, morphological, and optical behavioral features, and performs joint representation or splicing processing on the feature vectors to obtain fused multi-dimensional features. The animal identification device then identifies and determines the target animal category based on the multi-dimensional features, thus obtaining the target invertebrate's target animal category.

[0026] S130. The current animal features and target animal image sequence are obtained from the feature acquisition device through the data processing device, and the target orientation control parameters of the target invertebrate are determined based on the current animal features, target animal image sequence and target animal category, and the target orientation control parameters are sent to the orientation control device.

[0027] Target orientation control parameters refer to the specific settings for operating the orientation control device, determined based on the current animal characteristics, the target animal image, and its category. These parameters may include the intensity, wavelength, and emission time of the laser or sound waves, used to achieve precise control of the target animal. The orientation control device is a device used to receive control parameters from data processing equipment and output laser or sound waves for orientation control of the animal based on these parameters.

[0028] Optionally, the data processing device includes a spatial positioning component and a parameter decision component; correspondingly, the spatial positioning component determines the target three-dimensional spatial coordinates and target movement trajectory of the target invertebrate based on the current animal characteristics and the target animal image sequence; the parameter decision component determines the target orientation control parameters of the target invertebrate based on the target three-dimensional spatial coordinates, target movement trajectory, and target animal category.

[0029] The spatial positioning component is a core module in the data processing equipment, primarily responsible for analyzing the target animal's three-dimensional coordinate sequence and predicting its movement trajectory to achieve precise location and prediction of the animal's position and movement trajectory. The parameter decision component is another core module in the data processing equipment, responsible for receiving and analyzing relevant data from the target invertebrate and generating corresponding control parameters or action plans to guide further processing or intervention of the target invertebrate. The target's three-dimensional spatial coordinates refer to the specific numerical representation of the target invertebrate's position in three-dimensional space; these coordinates help to accurately locate the target animal's position. The target's movement trajectory refers to the target invertebrate's movement path in three-dimensional space that changes over time; by analyzing its movement trajectory, its behavioral patterns can be understood, thereby better predicting future movement direction and position.

[0030] S140. Orientation control of the target invertebrate is performed using directional control equipment according to the target orientation control parameters.

[0031] For example, a directional control device can be used to configure parameters such as the working mode, energy output, and intervention duration of a laser or directional acoustic device according to the target directional control parameters, so as to perform directional control on the target invertebrate.

[0032] This application embodiment uses a feature acquisition device to collect multi-dimensional animal features and multi-view images of target invertebrates in a target area, obtaining the current animal features of the target invertebrates and image sequences from at least two viewpoints. The current animal features are then sent to an animal identification device. These current animal features include morphological features, kinematic features, and optical behavioral features. Based on the current animal features, the animal identification device determines the target animal category of the target invertebrate. If the identified target animal category meets the animal management conditions, the target animal category is sent to a data processing device. The data processing device retrieves the current animal features and target animal image sequences from the feature acquisition device, and determines the target orientation control parameters of the target invertebrate based on the current animal features, target animal images, and target animal category. These target orientation control parameters are then sent to an orientation control device. The orientation control device performs orientation control on the target invertebrate based on the target orientation control parameters. This scheme, based on the multimodal features of invertebrates, performs category identification and orientation control parameter decision-making, which helps improve the accuracy and reliability of invertebrate identification.

[0033] Example 2 Figure 2This is a flowchart of an invertebrate orientation control method according to Embodiment 2 of this application. Based on the technical solutions of the above embodiments, this embodiment refines the process of "determining the target orientation control parameters of the target invertebrate based on current animal characteristics, target animal image sequence, and target animal category using a data processing device" to "determining the target three-dimensional coordinate sequence of the target invertebrate relative to the image acquisition component using a spatial positioning component based on the target animal image sequence; predicting the movement trajectory of the target invertebrate within a preset time period using the spatial positioning component based on the target three-dimensional coordinate sequence and kinematic features in the current animal characteristics, obtaining predicted movement trajectory data of the target invertebrate, and sending the predicted movement trajectory data to a parameter decision component; and determining the target orientation control parameters of the target invertebrate based on the predicted movement trajectory data, target animal category, and current animal characteristics using the parameter decision component." It should be noted that for parts not detailed in this embodiment, please refer to the relevant descriptions in other embodiments. Figure 2 As shown, the method includes: S210. Using a feature acquisition device, multi-dimensional animal feature acquisition and multi-view image acquisition are performed on the target invertebrate in the target area to obtain the current animal features of the target invertebrate and at least two target animal image sequences from different perspectives, and the current animal features are sent to the animal recognition device.

[0034] S220. Based on the current animal characteristics, determine the target animal category of the target invertebrate using animal identification equipment, and if the identified target animal category meets the animal management conditions, send the target animal category to the data processing equipment.

[0035] S230. Obtain the current animal features and target animal image sequence from the feature acquisition device through the data processing device.

[0036] S240. Based on the target animal image sequence, the spatial positioning component determines the target invertebrate's three-dimensional coordinate sequence relative to the image acquisition component.

[0037] Among them, the target three-dimensional coordinate sequence refers to a series of coordinate points generated by the spatial positioning component, which represent the trajectory of the target invertebrate's position in three-dimensional space over time.

[0038] Optionally, the spatial positioning component extracts features from the target animal image sequence at each viewpoint to obtain key feature sequences of the target invertebrate under different viewpoints; the key feature sequences include edge feature sequences and corner feature sequences; the spatial positioning component determines candidate two-dimensional coordinate sequences of the target invertebrate under different viewpoints based on the key feature sequences; the spatial positioning component determines the depth data sequence of the target invertebrate based on stereo vision technology and at least two viewpoints of the target animal image sequence; the spatial positioning component integrates the candidate two-dimensional coordinate sequences and the depth data sequences to obtain candidate three-dimensional coordinate sequences of the target invertebrate, and converts the candidate three-dimensional coordinate sequences into target three-dimensional coordinate sequences relative to the coordinate system of the image acquisition component.

[0039] The key feature sequence refers to the set of important features extracted from the image sequence of the target invertebrate, including information such as shape, edges, and corners; these features help to accurately identify and locate the target animal. The edge feature sequence is a sequence of information containing the animal's outer contour and shape changes, extracted through image processing techniques; edge features are crucial for recognizing the animal's contour and morphological features and are the foundation for precise localization. The corner feature sequence refers to the corner information identified in the image; these corners are usually obvious points of change or feature points in the image; corner features help to better capture the details of the animal in the image and enhance recognition accuracy. The candidate 2D coordinate sequence is generated based on the key feature sequence and represents a set of 2D coordinates representing the possible positions of the target invertebrate from different viewpoints. The depth data sequence is obtained through stereo vision techniques and is data related to the depth (i.e., z-axis coordinate) of the target invertebrate in 3D space. This data usually comes from images from at least two viewpoints, and the distance between the target animal and the observer is obtained through comparison and calculation. The candidate 3D coordinate sequence is generated by integrating 2D coordinate and depth data and represents the estimated position of the target invertebrate in 3D space.

[0040] S250. Based on the target's three-dimensional coordinate sequence and the kinematic characteristics in the current animal features, the spatial positioning component predicts the movement trajectory of the target invertebrate within a preset time period, obtains the predicted movement trajectory data of the target invertebrate, and sends the predicted movement trajectory data to the parameter decision component.

[0041] Among them, the predicted movement trajectory data refers to the estimation results of the animal's future movement path through an algorithm model based on the target's three-dimensional coordinate sequence and kinematic characteristics; these data provide information on the animal's possible location and dynamics within a preset time period.

[0042] S260. Based on the predicted motion trajectory data, the target animal category, and the current animal characteristics, the parameter decision component determines the target orientation control parameters of the target invertebrate and sends the target orientation control parameters to the orientation control device.

[0043] Optionally, the parameter decision component determines the current motion state of the target invertebrate based on the predicted motion trajectory data and the target animal category; the parameter decision component determines candidate orientation control parameters from a pre-set orientation control parameter library based on the target animal category, current motion state, and morphological features of the current animal characteristics; the parameter decision component adjusts the candidate orientation control parameters based on the predicted motion trajectory data to obtain the target orientation control parameters for the target invertebrate.

[0044] The current kinetic state refers to the current activity state of the target invertebrate, which can be a normal activity state, a restricted activity state, or an injured state. The orientation control parameter library is a pre-set database containing orientation control parameters for different animal categories and kinetic states. Candidate orientation control parameters are a set of parameters selected from the orientation control parameter library based on the target animal category, current kinetic state, and morphological characteristics.

[0045] In one alternative implementation, the current environmental data of the target invertebrate is obtained from the feature acquisition device through the parameter decision component, and the candidate orientation control parameters are adjusted according to the current environmental data and the predicted movement trajectory data to obtain the target orientation control parameters of the target invertebrate.

[0046] The current environmental data refers to the relevant data used to describe the target area where the target invertebrate is currently located, which may include environmental lighting conditions, spatial structure of the target area, and spatial relationship between the target invertebrate and surrounding objects.

[0047] In another alternative implementation, the directional control parameter library of this application is a pre-constructed parameter library for different target invertebrates; the system can use different types of directional control devices (including but not limited to lasers with continuous or pulsed output and directional acoustic devices) to act on the target animal under controlled conditions based on at least one candidate experimental variable; the system simultaneously collects the target animal's behavioral response, survival status, feeding refusal rate and other indicators characterizing the control effect during the experiment, and associates and stores the experimental results with the corresponding parameter combinations, thereby forming a directional control parameter library for a specified species.

[0048] Optionally, candidate experimental variables may include at least one or more of the following combinations: type of control means (laser, directional sound waves or a combination thereof); energy or acoustic parameters (power, frequency, duty cycle, etc.); duration of intervention and pathway of action; site of action (e.g., different areas of the body surface); distance of the intervention device from the target; developmental stage or age of the target animal; behavioral or physiological state of the target animal (normal activity, injury, restricted activity, etc.).

[0049] S270. Orientation control of the target invertebrate is performed using directional control equipment according to the target orientation control parameters.

[0050] This application embodiment uses a feature acquisition device to perform multi-dimensional animal feature acquisition and multi-view image acquisition of target invertebrates in a target area, obtaining the current animal features of the target invertebrates and target animal image sequences from at least two views, and then sending the current animal features to an animal identification device; the animal identification device determines the target animal category of the target invertebrates based on the current animal features, and if the identified target animal category meets the animal management conditions, the target animal category is sent to a data processing device; the data processing device obtains the current animal features and target animal image sequences from the feature acquisition device; and the spatial positioning component determines the target animal category based on the target animal image sequences. The method involves identifying the target invertebrate's three-dimensional coordinate sequence relative to the image acquisition component. A spatial positioning component predicts the invertebrate's trajectory within a preset time period based on the target's three-dimensional coordinate sequence and kinematic features of the current animal characteristics, obtaining predicted trajectory data. This predicted trajectory data is then sent to a parameter decision component. The parameter decision component determines the target invertebrate's orientation control parameters based on the predicted trajectory data, the target animal category, and current animal characteristics, and sends these parameters to an orientation control device. The orientation control device then performs orientation control on the target invertebrate according to these parameters. This approach, based on the multimodal characteristics of invertebrates, performs category identification and orientation control parameter decision-making, which helps improve the accuracy and reliability of invertebrate identification.

[0051] Example 3 Figure 3This is a schematic diagram of an invertebrate orientation control device according to Embodiment 3 of this application. It is applicable to situations involving animal identification and orientation control of invertebrates. This invertebrate orientation control device can be implemented in hardware and / or software and can be configured in a computer device, such as an orientation control system. The orientation control system includes a feature acquisition device, an animal identification device, a data processing device, and an orientation control device. The feature acquisition device is communicatively connected to both the animal identification device and the data processing device. The data processing device is also communicatively connected to both the animal identification device and the orientation control device. Figure 3 As shown, the device includes: The data acquisition module 310 is used to acquire multi-dimensional animal features and multi-view images of the target invertebrate in the target area through the feature acquisition device, obtain the current animal features of the target invertebrate and the target animal image sequence from at least two views, and send the current animal features to the animal recognition device; wherein, the current animal features include morphological features, kinematic features and optical behavioral features; The category determination module 320 is used to determine the target animal category of the target invertebrate based on the current animal characteristics through the animal identification device, and send the target animal category to the data processing device if the identified target animal category meets the animal management conditions; The parameter determination module 330 is used to acquire the current animal features and the target animal image sequence from the feature acquisition device through the data processing device, and determine the target orientation control parameters of the target invertebrate based on the current animal features, the target animal image sequence and the target animal category, and send the target orientation control parameters to the orientation control device. Animal control module 340 is used to perform directional control on a target invertebrate according to the target directional control parameters through a directional control device.

[0052] This application embodiment uses a feature acquisition device to collect multi-dimensional animal features and multi-view images of target invertebrates in a target area, obtaining the current animal features of the target invertebrates and image sequences from at least two viewpoints. The current animal features are then sent to an animal identification device. These current animal features include morphological features, kinematic features, and optical behavioral features. Based on the current animal features, the animal identification device determines the target animal category of the target invertebrate. If the identified target animal category meets the animal management conditions, the target animal category is sent to a data processing device. The data processing device retrieves the current animal features and target animal image sequences from the feature acquisition device, and determines the target orientation control parameters of the target invertebrate based on these features, the target animal image sequences, and the target animal category. These target orientation control parameters are then sent to an orientation control device. The orientation control device performs orientation control on the target invertebrate based on these target orientation control parameters. This scheme, based on the multimodal features of invertebrates, performs category identification and orientation control parameter decision-making, which helps improve the accuracy and reliability of invertebrate identification.

[0053] Optionally, the feature acquisition device includes a multi-view image acquisition component; the data processing device includes a spatial positioning component and a parameter decision component; correspondingly, the parameter determination module 330 includes: The coordinate sequence determination unit is used to determine the target three-dimensional coordinate sequence of the target invertebrate relative to the image acquisition component based on the target animal image sequence using the spatial positioning component; The motion trajectory prediction unit is used to predict the motion trajectory of the target invertebrate within a preset time period based on the target's three-dimensional coordinate sequence and the kinematic features in the current animal characteristics through the spatial positioning component, obtain the predicted motion trajectory data of the target invertebrate, and send the predicted motion trajectory data to the parameter decision component. The parameter determination unit is used to determine the target orientation control parameters of the target invertebrate based on the predicted motion trajectory data, the target animal category, and the current animal characteristics through the parameter decision component.

[0054] Optional, parameter determination unit, specifically used for: The current motion state of the target invertebrate is determined by the parametric decision component based on the predicted motion trajectory data and the target animal category. The parameter decision component determines candidate orientation control parameters from a pre-set orientation control parameter library based on the target animal category, current movement state, and morphological features of the current animal characteristics. The parameter decision component adjusts the candidate orientation control parameters based on the predicted motion trajectory data to obtain the target orientation control parameters for the target invertebrate.

[0055] Optional, coordinate sequence determination unit, specifically used for: By using a spatial localization component to extract features from the target animal image sequence from each viewpoint, key feature sequences of the target invertebrate under different viewpoints are obtained; among them, key feature sequences include edge feature sequences and corner feature sequences; Based on key feature sequences, the spatial localization component determines the candidate two-dimensional coordinate sequences of the target invertebrate under different perspectives; Using a spatial positioning component based on stereo vision technology, the depth data sequence of a target invertebrate is determined based on a target animal image sequence from at least two perspectives. By integrating the candidate two-dimensional coordinate sequence and the depth data sequence through the spatial positioning component, a candidate three-dimensional coordinate sequence of the target invertebrate is obtained, and the candidate three-dimensional coordinate sequence is converted into a target three-dimensional coordinate sequence relative to the coordinate system of the image acquisition component.

[0056] Optional, the category determination module 320 is specifically used for: Based on the morphological and kinematic characteristics of the current animal features, the animal identification device determines the candidate animal category and the category confidence of the candidate animal category of the target invertebrate. When an animal identification device identifies a candidate animal category that meets the animal identification criteria with sufficient confidence level, the candidate animal category is determined as the target animal category for the target invertebrate.

[0057] Optionally, the category determination module 320 is also specifically used for: When an animal identification device identifies a category whose confidence level does not meet the animal identification criteria, feature vectors are extracted from morphological features, kinematic features, and optical behavioral features to obtain morphological feature vectors, kinematic feature vectors, and optical behavioral feature vectors, respectively. By splicing morphological feature vectors, kinematic feature vectors, and optical behavioral feature vectors using animal identification equipment, multimodal animal features of the target invertebrate are obtained. Animal identification equipment determines the target animal category of a target invertebrate based on multimodal animal characteristics.

[0058] The invertebrate orientation control device provided in this application can execute the invertebrate orientation control method provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects for executing each invertebrate orientation control method.

[0059] According to embodiments of this application, this application also provides an electronic device, a readable storage medium, and a computer program product.

[0060] Example 4 Figure 4 This is a schematic diagram of the structure of an electronic device 410 implementing the invertebrate orientation control method of the embodiments of this application. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present application described and / or claimed herein.

[0061] like Figure 4 As shown, the electronic device 410 includes at least one processor 411 and a memory, such as a read-only memory (ROM) 412 or a random access memory (RAM) 413, communicatively connected to the at least one processor 411. The memory stores computer programs executable by the at least one processor. The processor 411 can perform various appropriate actions and processes based on the computer program stored in the ROM 412 or loaded from storage unit 418 into the RAM 413. The RAM 413 may also store various programs and data required for the operation of the electronic device 410. The processor 411, ROM 412, and RAM 413 are interconnected via a bus 414. An input / output (I / O) interface 415 is also connected to the bus 414.

[0062] Multiple components in electronic device 410 are connected to I / O interface 415, including: input unit 416, such as keyboard, mouse, etc.; output unit 417, such as various types of displays, speakers, etc.; storage unit 418, such as disk, optical disk, etc.; and communication unit 419, such as network card, modem, wireless transceiver, etc. Communication unit 419 allows electronic device 410 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0063] Processor 411 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 411 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 411 performs the various methods and processes described above, such as invertebrate orientation control methods.

[0064] In some embodiments, the invertebrate orientation control method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 418. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 410 via ROM 412 and / or communication unit 419. When the computer program is loaded into RAM 413 and executed by processor 411, one or more steps of the invertebrate orientation control method described above may be performed. Alternatively, in other embodiments, processor 411 may be configured as the invertebrate orientation control method by any other suitable means (e.g., by means of firmware).

[0065] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0066] Computer programs used to implement the methods of this application may be written in any combination of one or more programming languages. These computer programs may be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable invertebrate orientation control device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0067] In the context of this application, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0068] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0069] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0070] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0071] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this application can be achieved, and this is not limited herein.

[0072] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for directional control of invertebrates, characterized in that, An application is made in a orientation control system; the orientation control system includes a feature acquisition device, an animal identification device, a data processing device, and an orientation control device; the feature acquisition device is communicatively connected to the animal identification device and the data processing device respectively; the data processing device is communicatively connected to the animal identification device and the orientation control device respectively; the method includes: The feature acquisition device performs multi-dimensional animal feature acquisition and multi-view image acquisition on the target invertebrate in the target area to obtain the current animal features of the target invertebrate and the target animal image sequence from at least two views, and sends the current animal features to the animal recognition device; wherein, the current animal features include morphological features, kinematic features and optical behavioral features; The animal identification device determines the target animal category of the target invertebrate based on the current animal characteristics, and sends the target animal category to the data processing device if the identified target animal category meets the animal management conditions. The data processing device acquires the current animal features and the target animal image sequence from the feature acquisition device, and determines the target orientation control parameters of the target invertebrate based on the current animal features, the target animal image sequence and the target animal category, and sends the target orientation control parameters to the orientation control device. The directional control device performs directional control on the target invertebrate according to the target directional control parameters.

2. The method according to claim 1, characterized in that, The feature acquisition device includes a multi-view image acquisition component; the data processing device includes a spatial positioning component and a parameter decision component; correspondingly, the data processing device determines the target orientation control parameters of the target invertebrate based on the current animal features, the target animal image sequence, and the target animal category, including: The spatial positioning component determines the target invertebrate's three-dimensional coordinate sequence relative to the image acquisition component based on the target animal image sequence. The spatial positioning component predicts the movement trajectory of the target invertebrate within a preset time period based on the target's three-dimensional coordinate sequence and the kinematic features in the current animal characteristics, thereby obtaining the predicted movement trajectory data of the target invertebrate, and then sends the predicted movement trajectory data to the parameter decision component. The parameter decision component determines the target orientation control parameters of the target invertebrate based on the predicted motion trajectory data, the target animal category, and the current animal characteristics.

3. The method according to claim 2, characterized in that, The step of determining the target orientation control parameters of the target invertebrate using the parameter decision component based on the predicted motion trajectory data, the target animal category, and the current animal characteristics includes: The parameter decision component determines the current motion state of the target invertebrate based on the predicted motion trajectory data and the target animal category. The parameter decision component determines candidate orientation control parameters from a preset orientation control parameter library based on the target animal category, the current movement state, and the morphological features of the current animal characteristics. The parameter decision component adjusts the candidate orientation control parameters based on the predicted motion trajectory data to obtain the target orientation control parameters for the target invertebrate.

4. The method according to claim 2, characterized in that, The step of determining the target invertebrate's target three-dimensional coordinate sequence relative to the image acquisition component based on the target animal image sequence using the spatial positioning component includes: The spatial positioning component extracts features from the target animal image sequence from each viewpoint to obtain key feature sequences of the target invertebrate under different viewpoints; wherein, the key feature sequences include edge feature sequences and corner feature sequences; The spatial positioning component determines the candidate two-dimensional coordinate sequence of the target invertebrate from different perspectives based on the key feature sequence. The spatial positioning component, based on stereo vision technology, determines the depth data sequence of the target invertebrate according to the target animal image sequence from at least two perspectives. The spatial positioning component integrates the candidate two-dimensional coordinate sequence and the depth data sequence to obtain the candidate three-dimensional coordinate sequence of the target invertebrate, and then converts the candidate three-dimensional coordinate sequence into the target three-dimensional coordinate sequence relative to the coordinate system of the image acquisition component.

5. The method according to claim 1, characterized in that, The animal identification device determines the target animal category of the target invertebrate based on the current animal characteristics, including: The animal identification device determines the candidate animal category and the category confidence level of the target invertebrate based on the morphological and kinematic features of the current animal characteristics. When the animal identification device identifies a category whose confidence level meets the animal identification criteria, it determines the candidate animal category as the target animal category for the target invertebrate.

6. The method according to claim 5, characterized in that, The method further includes: When the animal identification device detects that the confidence level of the category does not meet the animal identification conditions, it extracts feature vectors from the morphological features, kinematic features, and optical behavioral features to obtain morphological feature vectors, kinematic feature vectors, and optical behavioral feature vectors, respectively. The animal identification device concatenates the morphological feature vector, the kinematic feature vector, and the optical behavioral feature vector to obtain the multimodal animal features of the target invertebrate. The animal identification device determines the target animal category of the target invertebrate based on the multimodal animal characteristics.

7. A directional control device for invertebrates, characterized in that, Configured in a orientation control system; the orientation control system includes a feature acquisition device, an animal identification device, a data processing device, and an orientation control device; the feature acquisition device is communicatively connected to the animal identification device and the data processing device respectively; the data processing device is communicatively connected to the animal identification device and the orientation control device respectively; the device includes: The data acquisition module is used to acquire multi-dimensional animal features and multi-view images of target invertebrates in the target area through the feature acquisition device, obtain the current animal features of the target invertebrates and at least two viewpoint image sequences of the target animals, and send the current animal features to the animal recognition device; wherein, the current animal features include morphological features, kinematic features and optical behavioral features; The category determination module is used to determine the target animal category of the target invertebrate based on the current animal characteristics using the animal identification device, and to send the target animal category to the data processing device if the identified target animal category meets the animal management conditions. The parameter determination module is used to acquire the current animal features and the target animal image sequence from the feature acquisition device through the data processing device, and determine the target orientation control parameters of the target invertebrate based on the current animal features, the target animal image sequence and the target animal category, and send the target orientation control parameters to the orientation control device; The animal control module is used to perform orientation control on the target invertebrate according to the target orientation control parameters through the orientation control device.

8. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the invertebrate orientation control method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the invertebrate orientation control method as described in any one of claims 1-6.

10. A computer program product comprising a computer program that, when executed by a processor, implements the invertebrate orientation control method according to any one of claims 1-6.

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