Mutton sheep breeding robot autonomous inspection and operation system
By using multiple sets of mobile detectors and sensing modules in mutton sheep farming and constructing a power signal intensity mapping function, the identification problem caused by the similar body shape of mutton sheep was solved, the identity and movement status of mutton sheep were accurately tracked, and the scientific and intelligent management of mutton sheep farming was improved.
Patent Information
- Application Number
- CN202510935469.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-08
- Publication Date
- 2025-09-26
AI Technical Summary
In the current mutton sheep breeding process, image recognition is mainly used to identify the identity of mutton sheep. However, due to the similar body shapes of mutton sheep, accurate identification is difficult to achieve and the movement status of each mutton sheep cannot be tracked.
Using multiple sets of motion detectors and sensing modules, UHF RFID readers and RFID tags, a power signal strength mapping function is constructed. The positioning and movement trajectory analysis of meat sheep are realized based on signal feedback, and the health status of meat sheep is determined by combining the abnormal analysis module.
The recognition rate of meat sheep has been improved, and the movement status of each meat sheep can be accurately identified and tracked, which improves the inspection effect and ensures that the health status of the meat sheep is accurately identified.
Smart Images
Figure CN120704341A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of breeding inspection, and in particular relates to an autonomous inspection and operation system of a meat sheep breeding robot. Background Art
[0002] Sheep farming robots are a product of modern livestock technology, designed to improve the efficiency and quality of sheep farming. Integrating advanced sensing technology, artificial intelligence algorithms, and precision mechanical design, these robots can automatically perform a range of complex farming tasks, such as feed delivery, health monitoring, and environmental regulation. Through precise data analysis, they ensure optimal feeding conditions for each sheep, while reducing the incidence of disease and improving farming efficiency. Furthermore, the use of farming robots can significantly reduce manual labor, making the farming process more scientific and intelligent. With technological advancements, sheep farming robots are becoming a vital force in the modernization of the livestock industry.
[0003] In the current mutton sheep breeding process, image recognition is mainly used to identify the identity of mutton sheep. However, mutton sheep have similar shapes, making accurate identification difficult and the movement status of each mutton sheep cannot be tracked. Summary of the Invention
[0004] The purpose of the present invention is to provide an autonomous inspection and operation system for mutton breeding robots, aiming to solve the problem that in the existing mutton breeding process, the identity of mutton sheep is mainly identified by image recognition, but the mutton sheep have similar shapes, making it difficult to achieve accurate identification and unable to track the movement status of each mutton sheep.
[0005] The present invention is implemented as follows: a mutton sheep breeding robot autonomous inspection and operation system, the system comprising: A model building module is used to build a three-dimensional model of the breeding area, receive breeding inspection instructions, and start autonomous inspections. The three-dimensional model of the breeding area includes at least a breeding area model and a mobile detection model. The mobile detection models are provided in three groups and arranged in a triangle. The sheep are equipped with a sensing module. A mapping function construction module is used to test the detection distance and detection power of the mobile detector and construct a power signal strength mapping function of the mobile detector based on the test results; A signal detection module is used to determine the power change curve of the motion detector based on the power signal strength mapping function, transmit a detection signal of corresponding power through the motion detector, and receive an induction feedback signal; The abnormality analysis module is used to locate the position of the mutton sheep based on the induction feedback signal, record the movement trajectory points of the mutton sheep, analyze the movement state of the mutton sheep based on the movement trajectory points, and determine whether there is any abnormality.
[0006] Preferably, the mapping function building module includes: The signal detection unit is used to set up multiple test modules in the breeding area, adjust the transmission power of the mobile detector, and detect each test module; A test data recording unit is used to record the transmit power and the feedback signal strength of each test module at the corresponding transmit power during the test process, and to construct a test signal coordinate, where the horizontal axis of the test signal coordinate is the transmit power and the vertical axis is the feedback signal strength; The function fitting unit is used to perform function fitting based on the test signal coordinates, import them into the function fitting tool, and obtain the power signal strength mapping function at different distances.
[0007] Preferably, the mapping function building module includes: The signal detection unit is used to set up multiple test modules in the breeding area, adjust the transmission power of the mobile detector, and detect each test module; A test data recording unit is used to record the transmit power and the feedback signal strength of each test module at the corresponding transmit power during the test process, and to construct a test signal coordinate, where the horizontal axis of the test signal coordinate is the transmit power and the vertical axis is the feedback signal strength; The function fitting unit is used to perform function fitting based on the test signal coordinates, import them into the function fitting tool, and obtain the power signal strength mapping function at different distances.
[0008] Preferably, the abnormality analysis module includes: Construct the measured signal coordinates based on the induction feedback signal, calculate the matching relationship between the measured signal coordinates and each power signal strength mapping function, and obtain the matching degree calculation result; The position between the sensing module and the motion detector is determined based on the matching calculation result, and the position of the mutton sheep is determined according to the distance value between the sensing module and each motion detector, and the movement trajectory of the mutton sheep is generated; Statistics are collected on the behavior of the mutton sheep according to their movement trajectories, and it is determined whether there are any abnormalities based on the statistical results. If there are any abnormalities, a determination result is generated.
[0009] Preferably, the motion detector adopts a UHF RFID reader / writer, and the sensing module is an RFID tag.
[0010] Preferably, a track is provided in the breeding area, and the motion detector is installed on the track.
[0011] Preferably, the growth status information of each mutton sheep is updated regularly.
[0012] The present invention provides an autonomous inspection and operation system for a mutton breeding robot. By setting up multiple groups of mobile detectors, the system can locate the mutton sheep based on the signal feedback of the sensing module. Compared with image recognition, the recognition rate of the mutton sheep is greatly improved. By analyzing the motion trajectory, the system can identify the movement status of each mutton sheep, improve the inspection effect, and accurately identify the health status of the mutton sheep. BRIEF DESCRIPTION OF THE DRAWINGS
[0013] Figure 1 This is an architectural diagram of an autonomous inspection and operation system for a mutton sheep farming robot provided by an embodiment of the present invention; Figure 2 An architectural diagram of a mapping function building module provided by an embodiment of the present invention; Figure 3 An architectural diagram of a signal detection module provided in an embodiment of the present invention; Figure 4 This is an architectural diagram of an anomaly analysis module provided in an embodiment of the present invention. DETAILED DESCRIPTION
[0014] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.
[0015] like Figure 1 FIG. 1 is an architecture diagram of an autonomous inspection and operation system for a mutton sheep breeding robot provided by an embodiment of the present invention, wherein the system includes: The model construction module 100 is used to construct a three-dimensional model of the breeding area, receive breeding inspection instructions, and start autonomous inspections. The three-dimensional model of the breeding area includes at least a breeding area model and a mobile detection model. The mobile detection model is set in three groups and arranged in a triangle. The meat sheep are equipped with sensing modules.
[0016] In this system, the model construction module 100 constructs a three-dimensional model of the breeding area. The three-dimensional model of the breeding area is constructed based on the breeding site and is modeled at a one-to-one ratio. The coverage of the breeding area is recorded, and a corresponding track is set in the breeding area. The track can be in the form of a hanging track. A patrol robot is installed on the track. The patrol robot is equipped with three groups of mobile detectors. A mobile detection model is constructed according to the position of the track and the position of the patrol robot and the mobile detector. The distance between the mobile detection models is known. The three groups of mobile detection models are arranged in a triangular manner, that is, the three groups of mobile detection models are not collinear. The mobile detector is a UHF RFID reader. In order to identify the identity of the meat sheep, an RFID tag is attached to each sheep. The UHF RFID reader can read and write all RFID tags within the reading and writing range. The transmission power of the UHF RFID reader can be changed.
[0017] The mapping function construction module 200 is used to test the detection distance and detection power of the motion detector and construct a power signal strength mapping function of the motion detector based on the test results.
[0018] In this system, the mapping function construction module 200 performs a power test. In order to determine the reading performance of the UHF RFID reader for the RFID tag, the position of the mobile detector is fixed, and an RFID tag is set within its detection range. The mobile detector is controlled to read the RFID tag with different transmission powers, and the feedback signal strength returned from the RFID tag is recorded to determine the feedback signal strength generated by the RFID tag at different transmission powers at the distance, thereby constructing a power signal strength mapping function at the distance. The power signal strength mapping function is used to record the feedback signal strength generated by the RFID tag at different transmission powers at the corresponding distance, and then change the distance between the RFID tag and the mobile detector to determine the power signal strength mapping function at each distance.
[0019] The signal detection module 300 is used to determine the power variation curve of the motion detector based on the power signal strength mapping function, transmit a detection signal of corresponding power through the motion detector, and receive an induction feedback signal.
[0020] In this system, the signal detection module 300 determines the distance range between the mobile detector at the current position and the meat sheep based on the three-dimensional model of the breeding area, and adjusts the range of the mobile detector's transmission power based on the distance range. The larger the distance range between the mobile detector and the meat sheep, the larger the range of the corresponding mobile detector's transmission power. Therefore, different transmission power intervals are used at different detection positions, and the change of the transmission power of the mobile detector at the corresponding position is controlled by generating a power change curve, so that the RFID tag can be read and written using detection signals of different intensities. During the reading and writing process, the intensity of the inductive feedback signal from the RFID tag is recorded.
[0021] The abnormality analysis module 400 is used to locate the position of the mutton sheep based on the induction feedback signal, record the movement trajectory points of the mutton sheep, analyze the movement state of the mutton sheep based on the movement trajectory points, and determine whether there is an abnormality.
[0022] In this system, the abnormality analysis module 400 constructs the measured signal coordinates based on the recorded transmission power and the corresponding induction feedback signal strength, calculates the fit rate between the measured signal coordinates and the curve determined by the power signal strength mapping function, determines the power signal strength mapping function to which the measured signal coordinates of the current batch belong, and thus determines the distance between the current RFID tag and each mobile detector. The specific position of the mutton can be determined by three sets of distance values, thereby recording a group of movement trajectory points of the mutton, connecting the movement trajectory points of the mutton, and obtaining the movement trajectory of the mutton. The analysis is performed based on the preset behavior analysis model to determine whether the mutton has abnormalities and generate corresponding judgment results.
[0023] like Figure 2 As shown, as a preferred embodiment of the present invention, the mapping function construction module 200 includes: The signal detection unit 201 is used to set up multiple test modules at the location of the breeding area, adjust the transmission power of the mobile detector, and detect each test module.
[0024] In this system, the signal detection unit 201 is used to determine the arrangement interval of the test modules according to the required detection accuracy by emitting detection signals and receiving signals returned from the test modules. For example, the spacing between the test modules is 3CM. The smaller the arrangement interval, the higher the subsequent detection accuracy. Multiple test modules are set around the mobile detector. Specifically, in order to reduce the number of test modules, a small number of test modules can be set each time. After the test is completed, they are moved to a new test position, that is, batch testing. After the test modules are arranged, the mobile detector is controlled to perform detection with different transmission powers to achieve detection of each test module.
[0025] The test data recording unit 202 is used to record the transmission power and the feedback signal strength of each test module under the corresponding transmission power during the test process, and construct a test signal coordinate, where the horizontal axis of the test signal coordinate is the transmission power and the vertical axis is the feedback signal strength.
[0026] In this system, the test data recording unit 202 is used to record the detection power P of the detection signal emitted by each motion detector and the feedback signal strength from each test module. For a specific test module, by changing the detection power multiple times, the feedback signal strength M from the test module to the motion detector is also different, so as to construct the test signal coordinate (P i , M i ), where P i is the transmission power of the detection signal transmitted for the i-th time, M i The feedback signal strength returned by the detection module for the i-th time.
[0027] The function fitting unit 203 is used to perform function fitting based on the test signal coordinates, import them into the function fitting tool, and obtain power signal strength mapping functions at different distances.
[0028] In this system, the function fitting unit 203 performs function fitting based on the test signal coordinates, calls a preset function fitting tool, such as a matlab data tool, and imports all the test signal coordinates belonging to the same test module into the matlab data tool, thereby fitting the corresponding fitting function, and records the distance L between the current test module and the mobile detector, and the power signal strength mapping function corresponding to the distance L, that is, when the test module is at a distance L, the feedback of detection signals of different powers satisfies the power signal strength mapping function.
[0029] like Figure 3 As shown, as a preferred embodiment of the present invention, the signal detection module 300 includes: The detection range identification unit 301 is used to determine the distance range interval between the mobile detector and the sheep according to the three-dimensional model of the breeding area, and determine the transmission power range based on the distance range interval.
[0030] In this module, the detection range identification unit 301 determines the distance range between the mobile detector and the mutton sheep based on the three-dimensional model of the breeding area, obtains the current position of the inspection robot, and determines the distance between the corresponding mobile detector and the ground of the breeding area based on the three-dimensional model of the breeding area and the position of the inspection robot. The minimum distance between the mutton sheep and the mobile detector can be determined according to the height range of the mutton sheep, and the maximum distance is determined according to the preset maximum detection distance of the mobile detector, such as 3m. The distance range corresponding to the current position of the inspection robot is determined accordingly. For areas less than the minimum distance, the mutton sheep do not move within this range and no detection is required. For positions exceeding the maximum distance, the detection accuracy of the mobile detector will be reduced. Therefore, a suitable range can be determined for detection. The detection distance under different transmission powers is controlled according to the detection parameters of the mobile detector, and the transmission power range under the distance range is reversed according to the distance range. For example, when the power is P1, the detection distance is 1M while ensuring the detection accuracy.
[0031] The power control unit 302 is configured to construct a power variation curve based on the transmission power range, and record the transmission power at each moment in the power variation curve.
[0032] In this module, the power control unit 302 constructs a power change curve based on the transmission power range. Specifically, a preset power change duration is obtained. For example, when the inspection robot moves to a certain position, its residence time is 1 second, and the power change duration is 1 second. The power change curve can adopt a preset function type, whose independent variable is the time value and the dependent variable is the transmission power. Within the power change duration interval, the transmission power needs to cover the entire transmission power range.
[0033] The feedback signal recording unit 303 is used to control the motion detector to transmit a detection signal of corresponding power at each moment based on the power variation curve, and to record the sensing feedback signal returned from the sensing module, where the sensing feedback signal includes signal strength.
[0034] In this module, when the mobile detector detects with different transmission powers according to the power change curve, the feedback signal recording unit 303 activates the RFID tags on each mutton sheep, thereby returning a feedback signal to the mobile detector. The mobile detector identifies the identity of the RFID tag based on the feedback signal, thereby confirming the identity of the mutton sheep and recording the strength of the feedback signal.
[0035] like Figure 4 As shown, as a preferred embodiment of the present invention, the abnormality analysis module 400 includes: The function matching unit 401 is used to construct the measured signal coordinates according to the sensing feedback signal, calculate the matching relationship between the measured signal coordinates and each power signal strength mapping function, and obtain a matching degree calculation result.
[0036] In this module, the function matching unit 401 constructs the measured signal coordinates based on all the inductive feedback signals corresponding to each RFID tag. The mobile detector samples the power change curve at a preset time interval and sends the detection signal based on the transmission power obtained by the sampling. Each transmission obtains a set of corresponding inductive feedback signals, thereby obtaining multiple sets of measured signal coordinates. The horizontal coordinates of the measured signal coordinates are substituted into each power signal strength mapping function to obtain a calculated value. The calculated value is compared with the vertical coordinate of the measured signal coordinates. If the difference is less than the preset value, it is determined that the measured signal coordinates match the power signal strength mapping function, and the power signal strength mapping function that best matches the measured signal coordinates corresponding to the current RFID tag is determined. The distance value corresponding to the power signal strength mapping function is used as the distance between the current RFID and the mobile detector.
[0037] The trajectory recording unit 402 is used to determine the distance between the sensing module and the mobile detector based on the matching degree calculation result, determine the position of the mutton sheep according to the distance value between the sensing module and each mobile detector, and generate the movement trajectory of the mutton sheep.
[0038] In this module, the trajectory recording unit 402 obtains the distance between the RFID tag and each mobile detector, and constructs a spherical area in the three-dimensional model of the breeding area with the mobile detector as the center and the distance between the RFID tag and each mobile detector as the radius. The midpoint of the overlapping area of the three groups of spherical areas is determined as the position of the meat sheep, and the position of the meat sheep at the current moment is recorded. During the movement of the inspection robot, multiple trajectory points will be generated. The trajectory points are connected to obtain the movement trajectory of the meat sheep.
[0039] The trajectory analysis unit 403 is used to collect statistics on the behavior of the mutton sheep according to the movement trajectory of the mutton sheep, determine whether there is an abnormality based on the statistical results, and generate a determination result if there is an abnormality.
[0040] In this module, the trajectory analysis unit 403 collects statistics on the behavior of the mutton sheep based on its movement trajectory. When the mutton sheep approaches the eating area, it is judged that it is eating, and the activity type of the mutton sheep in the breeding area is determined based on this. The behavior of the mutton sheep is evaluated according to its movement status at each moment, and it is determined whether there is any abnormal behavior, such as circling, long-term stillness, and long-term non-eating. According to the judgment result, the management personnel are notified to intervene; in this process, the growth status information of each mutton sheep is regularly updated to facilitate the determination of whether the mutton sheep is in a kneeling or standing position. For example, at a certain time, the height of a mutton sheep grows to H, and the height of the corresponding RFID tag is h. If the distance between the RFID tag and the ground is detected to be more than 0.9h, the mutton sheep is judged to be standing, otherwise it is kneeling.
[0041] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.
Claims
1. A meat sheep breeding robot autonomous inspection and operation system, characterized in that: The system comprises: A model building module is used to build a three-dimensional model of the breeding area, receive breeding inspection instructions, and start autonomous inspections. The three-dimensional model of the breeding area includes at least a breeding area model and a mobile detection model. The mobile detection models are provided in three groups and arranged in a triangle. The sheep are equipped with a sensing module. A mapping function construction module is used to test the detection distance and detection power of the mobile detector and construct a power signal strength mapping function of the mobile detector based on the test results; A signal detection module is used to determine the power change curve of the motion detector based on the power signal strength mapping function, transmit a detection signal of corresponding power through the motion detector, and receive an induction feedback signal; The abnormality analysis module is used to locate the position of the mutton sheep based on the induction feedback signal, record the movement trajectory points of the mutton sheep, analyze the movement state of the mutton sheep based on the movement trajectory points, and determine whether there is any abnormality.
2. The mutton breeding robot autonomous inspection and operation system according to claim 1 is characterized in that: The mapping function building block includes: The signal detection unit is used to set up multiple test modules in the breeding area, adjust the transmission power of the mobile detector, and detect each test module; A test data recording unit is used to record the transmit power and the feedback signal strength of each test module at the corresponding transmit power during the test process, and to construct a test signal coordinate, where the horizontal axis of the test signal coordinate is the transmit power and the vertical axis is the feedback signal strength; The function fitting unit is used to perform function fitting based on the test signal coordinates, import them into the function fitting tool, and obtain the power signal strength mapping function at different distances.
3. The mutton breeding robot autonomous inspection and operation system according to claim 1 is characterized in that: The signal detection module includes: A detection range identification unit is used to determine the distance range between the mobile detector and the sheep based on the three-dimensional model of the breeding area, and determine the transmission power range based on the distance range; A power control unit is used to construct a power variation curve based on the transmit power range and record the transmit power at each moment in the power variation curve; The feedback signal recording unit is used to control the motion detector to transmit a detection signal of corresponding power at each moment based on the power change curve, and to record the sensing feedback signal returned from the sensing module, where the sensing feedback signal includes signal strength.
4. The mutton breeding robot autonomous inspection and operation system according to claim 1 is characterized in that: The abnormality analysis module includes: The function matching unit is used to construct the measured signal coordinates according to the sensing feedback signal, calculate the matching relationship between the measured signal coordinates and each power signal strength mapping function, and obtain the matching degree calculation result; A trajectory recording unit is used to determine the distance between the sensing module and the motion detector based on the matching calculation result, determine the position of the mutton sheep according to the distance value between the sensing module and each motion detector, and generate the movement trajectory of the mutton sheep; The trajectory analysis unit is used to collect statistics on the behavior of the mutton sheep according to their movement trajectory, and to determine whether there is an abnormality based on the statistical results. If there is an abnormality, a determination result is generated.
5. The mutton breeding robot autonomous inspection and operation system according to claim 1 is characterized in that: The motion detector adopts a UHF RFID reader / writer, and the sensing module is an RFID tag.
6. The mutton breeding robot autonomous inspection and operation system according to claim 1, characterized in that: Tracks are provided in the breeding area, and motion detectors are installed on the tracks.
7. The mutton breeding robot autonomous inspection and operation system according to claim 1 is characterized in that: Regularly update the growth status information of each meat sheep.