Navigation method and system for inspection robot in breeding house

Abstract

The invention discloses a navigation method and system for an inspection robot in a breeding house, and relates to the technical field of intelligent agriculture. The method comprises the following steps: dividing the breeding house into a plurality of areas, and preliminarily planning an inspection path of the inspection robot in combination with a shortest path algorithm and a depth-first search algorithm; environment data and animal data are collected in real time through an internal sensor group and an intelligent ear tag, a health data group is obtained through preprocessing, an environment health state index and an animal health state index are calculated, a comprehensive health index is further obtained, and the comprehensive health index and a preset first comprehensive health threshold value and a preset second comprehensive health threshold value are evaluated. And when path planning is triggered by health assessment, a dynamic path optimization model is adopted to adjust an inspection path, and an area with relatively high health risk is preferentially covered until the health assessment of the inspection task area reaches a good state. According to the method, the breeding environment and animal health monitoring efficiency can be effectively improved, and health management and risk control in the breeding process are ensured.

Description

Technical Field

[0001] The present invention relates to the field of intelligent agricultural technology, and in particular to a navigation method and system for an inspection robot in a breeding house. Background Art

[0002] With the growth of the global population and higher requirements for food safety and quality, the aquaculture industry in particular is facing unprecedented challenges. While traditional aquaculture methods increase production, they often ignore the refined management of animal health and environmental monitoring, resulting in waste of resources, environmental pollution, and frequent animal diseases. In addition, with the rise in labor costs and the increasing complexity of the aquaculture environment, manual inspection and management can no longer meet the needs of efficiency and precision. Therefore, using automation and intelligent technology for aquaculture management, especially environmental and animal health monitoring through inspection robots, has become a key way to solve the problems of low efficiency, poor accuracy, and slow emergency response in the aquaculture industry. Promoting the development of smart agriculture has become an important direction for global agricultural modernization.

[0003] Although the existing inspection robots for farmhouses have improved the efficiency of farming to a certain extent, there are still some problems in practical applications, especially in inspection path planning and health assessment. On the one hand, traditional path planning algorithms, such as the shortest path algorithm, may not be easy to effectively solve the optimization problems of multiple factors such as energy consumption, equipment charging and regional health status in large-scale farmhouses, resulting in the inspection robot failing to cover all key areas due to insufficient power or too long a path. On the other hand, the current health monitoring system often relies too much on a single data input when evaluating the environment and animal health status, and it is difficult to consider the nonlinear relationship between multiple variables, and it is not easy to accurately reflect the complexity of the farming environment. Therefore, although the robot can complete the inspection task, it lacks a real-time health assessment mechanism and dynamic path adjustment capabilities, which makes it difficult for the robot to respond in time when encountering health risk areas, thus affecting the comprehensive management effect of the farming environment and animal health. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a navigation method and system for an inspection robot in a breeding house, which solves the problems in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A navigation method for an inspection robot in a breeding house, comprising the following steps: S1. Divide the large animal breeding house into several areas, deploy several inspection robots, use the shortest path algorithm, construct the path optimization objective function, preliminarily plan the initial inspection path of the inspection robot, and use the depth-first search algorithm to cover the area without duplication; S2, collect environmental data and animal data in real time through the sensor group installed inside the inspection robot and the smart ear tag equipped with each animal, and build a data processing system to pre-process the environmental data and animal data to obtain a health data group; S3, performing summary calculation based on the acquired health data group to obtain the environmental health status index hjz and the animal health status index djk; S4. Summarize and calculate the obtained environmental health status index hjz and animal health status index djk to obtain the comprehensive health index zhj, and perform a comprehensive health assessment with the preset first comprehensive health threshold A and second comprehensive health threshold B to comprehensively analyze the health status of the breeding environment and animals; S5. When the comprehensive health assessment triggers path planning, a dynamic path optimization model is constructed, and the obtained comprehensive health index zhj is input into the dynamic path optimization model to obtain the dynamic path adjustment index ljt. The inspection robot adjusts the inspection path according to the dynamic path adjustment index ljt until the comprehensive health assessment of the inspection task area of ​​the inspection robot is in good condition. At this time, the inspection robot readjusts the inspection path to the initial inspection path.

[0006] Preferably, said S1 includes S11, S12 and S13; S11. Divide the large animal breeding house into several areas according to the animal species and layout structure in the breeding house, deploy several inspection robots, and set inspection tasks for each inspection robot, wherein the inspection tasks include inspecting multiple areas; S12. Obtain all inspection paths in the breeding house according to the three-dimensional drawing of the breeding house. Obtain the distance between each area and other areas according to the inspection area of ​​each inspection robot and the route within the inspection area. Use the shortest path algorithm, combine the location of the charging pile, the inspection task and the energy consumption to plan the shortest inspection path, and construct the path optimization objective function to preliminarily plan the initial inspection path of the inspection robot. The specific path optimization objective function is: , where P represents the node order of the path, jl(i, i+1) represents the distance between region i and region i+1, nl(i, i+1) represents the energy consumption between region i and region i+1, and n represents the total number of regions; S13. During the inspection path planning process, a depth-first search algorithm is used to perform non-repetitive coverage of the area, record the areas that the robot has already planned, and avoid invalid returns to the areas that have already been inspected.

[0007] Preferably, S2 includes S21, S22 and S23; S21. After the inspection robot has preliminarily planned the initial inspection route, the inspection robot is started to inspect the task area, and environmental data and animal data are collected in real time through the sensor group installed inside the inspection robot and the smart ear tag equipped with each animal; The sensor group includes a temperature sensor, a humidity sensor, a carbon dioxide sensor, an air flow sensor, a light intensity sensor and an infrared sensor; S22. Build a data processing system, establish a communication connection between the data processing system and the sensor group and the smart ear tag through a wireless network, and transmit the environmental data and animal data collected by the sensor group and the smart ear tag to the data processing system in real time.

[0008] Preferably, S23, the data processing system receives the environmental data and the animal data in real time, and preprocesses the environmental data and the animal data, wherein the preprocessing includes animal activity processing, denoising, missing value processing data correction and dimensionless processing to obtain a health data set; The animal activity volume processing is based on the periodically collected animal positioning data of each animal equipped with a smart ear tag, monitoring its activity trajectory in the breeding house, recording the animal's activity path and residence time in the house, calculating the animal activity volume hd, and then collecting the animal's body temperature dt based on the smart ear tag; The health data set includes an environmental health data set and an animal health data set; The environmental health data set includes environmental temperature wd, environmental humidity sd, carbon dioxide content CO2, air flow rate ls and light intensity gz; The animal health data set includes animal body temperature dt, animal activity hd and animal density dm.

[0009] Preferably, said S3 includes S31 and S32; S31, performing summary calculation based on the acquired environmental health data group, obtaining the environmental health status index hjz, and analyzing the environmental health status of each area in the breeding house in real time; The environmental health status index hjz is calculated and obtained by the following formula: ; Where wd i represents the actual temperature of the ith region, wd o Indicates the suitable temperature value for animals in the breeding house, sd i represents the actual humidity of the ith area, sd o Indicates the suitable humidity value for animals in the breeding house, CO 2，i represents the actual carbon dioxide content in the ith region, CO 2，o Indicates the peak carbon dioxide content allowed for animal health in the breeding house, gz irepresents the actual light intensity of the ith area, gz o It indicates the appropriate light intensity for animals in the breeding house; S32, performing summary calculation based on the obtained animal health data group, obtaining the animal health status index djk, and monitoring the health status of animals in each area in real time; The animal health status index djk is calculated by the following formula: ; Where m represents the total number of animals in the ith region, dt j represents the actual body temperature of the jth animal, dt z Indicates the normal body temperature of animals, hd j represents the activity level of the jth animal, dm i represents the animal density in the i-th area.

[0010] Preferably, said S4 includes S41 and S42; S41. Based on the obtained environmental health status index hjz and animal health status index djk, a comprehensive health index zhj is obtained, which reflects the comprehensive impact of environmental health on animal health in the breeding house, as well as the nonlinear relationship between the two. The comprehensive health index zhj is calculated by the following formula: ; In the formula, e represents the exponential function, Represents the adjustment coefficient.

[0011] Preferably, S42, based on the animal health breeding index, a first comprehensive health threshold A and a second comprehensive health threshold B are preset, and a comprehensive health assessment is performed with the obtained comprehensive health index zhj, the breeding environment and the health status of the animals are comprehensively analyzed, and according to the assessment results, the inspection priority is set, and the inspection route and inspection frequency are adjusted. The specific assessment plan is as follows; When the comprehensive health index zhj is less than the first comprehensive health threshold A, the area is in a dangerous state, and the first warning information is generated and transmitted to the user end of the relevant personnel through the wireless network, reminding the relevant personnel to take governance measures immediately, and triggering the path planning to re-plan the inspection path; When the comprehensive health threshold A≤comprehensive health index zhj≤the second comprehensive health threshold B, there are unhealthy factors in this area, and the second warning information is generated and transmitted to the user end of relevant personnel through the wireless network, reminding relevant personnel to take governance measures immediately, and triggering path planning to re-plan the inspection path; When the comprehensive health index zhj>the second comprehensive health threshold B, this area is in good condition and maintains normal monitoring.

[0012] Preferably, said S5 includes S51 and S52; S51, when the comprehensive health assessment triggers the path planning, a dynamic path optimization formula is constructed based on the three-dimensional drawing and using the dynamic path planning algorithm, and then the obtained comprehensive health index zhj is input into the dynamic path optimization model to obtain the dynamic path adjustment index ljt; The dynamic path optimization formula is as follows: ; In the formula, represents the rate at which the comprehensive health index zhj of the i-th region changes over time, jl i represents the distance between the i-th region and the next region, jl i represents the energy loss required to go from the i-th region to the next region, nl max represents the remaining energy of the inspection robot, n represents the total number of regions, and exp represents the exponential function with the natural logarithm e as the base.

[0013] Preferably, S52, the inspection robot preferentially adjusts the path of the area in a dangerous state according to the dynamic path adjustment index ljt, and adjusts the inspection path of this area. If health problems occur in multiple areas at the same time, the robot will re-evaluate and adjust the paths of all relevant areas, and dynamically adjust the path sequence and distance according to the real-time comprehensive health index zhj, giving priority to covering areas where health risks are in a dangerous state; After management by relevant personnel, the inspection path of the inspection robot is adjusted again based on the changing trend of the comprehensive health index zhj obtained through multiple inspections, and the dynamic path adjustment index ljt is used. When the comprehensive health assessment of the inspection task area of ​​the inspection robot is in good condition, the inspection robot readjusts the inspection path to the initial inspection path.

[0014] A navigation system for an inspection robot in a breeding house, comprising an initial inspection path planning module, an inspection collection module, a health analysis module, a comprehensive health assessment module and a path adjustment module; The initial inspection path planning module is used to divide the large animal breeding house into several areas, deploy several inspection robots, use the shortest path algorithm, construct the path optimization objective function, preliminarily plan the initial inspection path of the inspection robot, and use the depth-first search algorithm to cover the area without duplication; The inspection and collection module collects environmental data and animal data in real time through the sensor group installed inside the inspection robot and the smart ear tag equipped with each animal, and constructs a data processing system to pre-process the environmental data and animal data to obtain a health data group; The health analysis module is used to perform summary calculations based on the acquired health data group to obtain the environmental health status index hjz and the animal health status index djk; The comprehensive health assessment module is used to perform summary calculation based on the obtained environmental health status index hjz and animal health status index djk, obtain the comprehensive health index zhj, and perform comprehensive health assessment with the preset first comprehensive health threshold A and second comprehensive health threshold B, and comprehensively analyze the health status of the breeding environment and animals; The path adjustment module is used to build a dynamic path optimization model when the comprehensive health assessment triggers path planning, and then input the obtained comprehensive health index zhj into the dynamic path optimization model to obtain the dynamic path adjustment index ljt. The inspection robot adjusts the inspection path according to the dynamic path adjustment index ljt until the comprehensive health assessment of the inspection task area of ​​the inspection robot is in good condition. The inspection robot readjusts the inspection path to the initial inspection path.

[0015] The present invention provides a navigation method and system for a patrol robot in a breeding house. It has the following beneficial effects: (1) This method divides large animal farms into several inspection areas and deploys multiple inspection robots according to the layout of the farms and the types of animals. Each inspection robot plans the inspection path according to the preset tasks, the shortest path algorithm and the depth-first search algorithm, and ensures that the path is not covered repeatedly. This strategy not only maximizes the inspection efficiency, but also effectively avoids repeated inspections, ensuring that each area is fully monitored, thereby significantly reducing unnecessary energy consumption and inspection time.

[0016] (2) This method integrates the sensor group and the animal smart ear tag to collect environmental and animal data in real time, providing an accurate basis for health assessment and being able to monitor changes in the breeding environment in real time. At the same time, the animal smart ear tag records key health data such as the activity trajectory and body temperature of each animal. Through the preprocessing function of the data processing system, these collected data are denoised, missing values ​​are removed, and dimensionless processing is performed to obtain the health data group, which is then summarized and calculated to finally generate the environmental health status index hjz and the animal health status index djk. These health data provide accurate data support for subsequent health assessment and dynamic path optimization, ensuring that the health status of the environment and animals can be monitored in real time and effectively managed during the breeding process.

[0017] (3) This method calculates the environmental health status index hjz and the animal health status index djk by summarizing and calculating, obtains the comprehensive health index zhj, and performs a comprehensive health assessment with the preset first comprehensive health threshold A and second comprehensive health threshold B, and comprehensively analyzes the health status of the breeding environment and animals. It reflects the impact of the breeding environment on animal health and the interaction between the two. When the comprehensive health index djk is lower than the second comprehensive health threshold B, the path adjustment is automatically triggered, and the areas with poor health status are inspected first. Through the dynamic path optimization model, the inspection robot can adjust the inspection route according to the real-time changes of the health index, give priority to covering areas with higher health risks, and ensure that the health problems of the breeding environment and animals can be effectively dealt with in a timely manner. After treatment, the inspection path can be automatically readjusted according to the results of multiple inspections and the changing trend of the health index until the health status of all areas reaches a good level, and the inspection robot readjusts the inspection path to the initial inspection path. Through this mechanism, the inspection robot can continuously provide efficient and accurate health monitoring to ensure that the environment and animal health of the breeding house are optimally protected. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flowchart of a navigation method for a patrol robot in a breeding house according to the present invention; Figure 2 The present invention is a schematic diagram of the steps of a navigation system of a patrol robot in a breeding house. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Example 1 See also Figure 1 The present invention provides a navigation method for a patrol robot in a breeding house. To achieve the above purpose, the present invention is implemented through the following technical scheme: comprising the following steps: S1. Divide the large animal breeding house into several areas, deploy several inspection robots, use the shortest path algorithm, construct the path optimization objective function, preliminarily plan the initial inspection path of the inspection robot, and use the depth-first search algorithm to cover the area without duplication; S2, collect environmental data and animal data in real time through the sensor group installed inside the inspection robot and the smart ear tag equipped with each animal, and build a data processing system to pre-process the environmental data and animal data to obtain a health data group; S3, performing summary calculation based on the acquired health data group to obtain the environmental health status index hjz and the animal health status index djk; S4. Summarize and calculate the obtained environmental health status index hjz and animal health status index djk to obtain the comprehensive health index zhj, and perform a comprehensive health assessment with the preset first comprehensive health threshold A and second comprehensive health threshold B to comprehensively analyze the health status of the breeding environment and animals; S5. When the comprehensive health assessment triggers path planning, a dynamic path optimization model is constructed, and the obtained comprehensive health index zhj is input into the dynamic path optimization model to obtain the dynamic path adjustment index ljt. The inspection robot adjusts the inspection path according to the dynamic path adjustment index ljt until the comprehensive health assessment of the inspection task area of ​​the inspection robot is in good condition. At this time, the inspection robot readjusts the inspection path to the initial inspection path.

[0021] In this embodiment, by dividing the breeding house into several areas and deploying multiple inspection robots, the shortest path algorithm is used to construct the path optimization objective function, the inspection path is preliminarily planned, and the depth-first search algorithm is combined to achieve non-repetitive coverage of the area. This method can effectively improve the working efficiency of the inspection robot, avoid inspection omissions caused by path duplication or insufficient coverage in traditional inspection methods, and ensure that each area can be effectively monitored. Compared with the prior art, this method not only considers distance and time in path planning, but also fully integrates factors such as charging pile location, inspection tasks and energy consumption, thereby achieving a more accurate and optimized path design. By combining the inspection robot with a sensor group and an intelligent ear tag, this method can collect environmental data and animal data in the breeding house in real time, and pre-process the data through a data processing system to obtain a health data group. Compared with the traditional manual inspection method, this method realizes real-time data collection and automatic processing, improves the efficiency and accuracy of data processing, and avoids delays and errors in manual monitoring. The real-time assessment of the comprehensive health status can dynamically reflect the changes in the breeding environment and animal health through the calculation of the environmental health status index hjz and the animal health status index djk, and provide a more accurate health monitoring and management solution. On the basis of the comprehensive health assessment, this method uses a dynamic path optimization model to summarize and calculate the environmental health status index hjz and the animal health status index djk to obtain the comprehensive health index zhj, and conduct a comprehensive health assessment with the preset first comprehensive health threshold A and second comprehensive health threshold B, comprehensively analyze the breeding environment and the health status of the animals, adjust the inspection path according to the changes in the comprehensive health index zhj, and give priority to covering areas with higher health risks. This innovative measure enables the inspection robot to automatically adjust the path according to environmental changes, thereby responding to possible health risks in a timely manner and reducing the spread and omission of health problems. Compared with the traditional method that relies on manual inspections and fixed paths, the dynamic path adjustment mechanism of the present invention greatly improves the flexibility and intelligence level of inspections. Ultimately, by continuously optimizing inspection routes and adjusting inspection frequencies, this method can ensure that the comprehensive health assessment of each area in the breeding house is always maintained in a good state, significantly improving the health management efficiency of the breeding process and the controllability of the breeding environment, thereby reducing the risk of animal diseases and improving overall breeding efficiency.

[0022] Example 2 This embodiment is explained in Example 1, please refer to Figure 1 , specifically: the S1 includes S11, S12 and S13; S11. Divide the large animal breeding house into several areas according to the animal species and layout structure in the breeding house, deploy several inspection robots, and set inspection tasks for each inspection robot, wherein the inspection tasks include inspecting multiple areas; S12. Obtain all inspection paths in the breeding house according to the three-dimensional drawing of the breeding house. Obtain the distance between each area and other areas according to the inspection area of ​​each inspection robot and the route within the inspection area. Use the shortest path algorithm, combine the location of the charging pile, the inspection task and the energy consumption to plan the shortest inspection path, and construct the path optimization objective function to preliminarily plan the initial inspection path of the inspection robot. The specific path optimization objective function is: , where P represents the node order of the path, jl(i, i+1) represents the distance between region i and region i+1, nl(i, i+1) represents the energy consumption between region i and region i+1, and n represents the total number of regions; S13. During the inspection path planning process, a depth-first search algorithm is used to perform non-repetitive coverage of the area, record the areas that the robot has already planned, and avoid invalid returns to the areas that have already been inspected.

[0023] In this embodiment, according to the needs of different animal species and layout structures, the area is reasonably divided and multiple inspection robots are deployed. Each robot undertakes the inspection tasks of multiple areas. This regional allocation not only optimizes resource utilization, but also ensures that each area can be inspected and monitored in a timely manner. By combining the three-dimensional drawings of the breeding house, the distance between each area is accurately calculated, and the shortest path algorithm is used to comprehensively consider the location of the charging pile, the inspection task and the energy consumption, and the optimal inspection path is planned, which significantly improves the efficiency and accuracy of the path planning and avoids unnecessary energy waste and time waste. This path optimization not only reduces the empty running during the robot inspection process, but also provides a stable guarantee for the smooth completion of the task. Finally, the depth-first search algorithm ensures that each area is effectively covered, avoiding the invalid return of the robot in the inspected area. This strategy effectively improves the inspection efficiency, avoids resource waste, and provides all-round support for the intelligent inspection of the breeding house. These measures combined not only improve the comprehensiveness and efficiency of the inspection, but also avoid duplication of work while ensuring the optimal allocation of energy and time resources, and significantly improve the operating efficiency of the overall system.

[0024] Example 3 This embodiment is explained in Example 2. Please refer to Figure 1 Specifically: S2 includes S21, S22 and S23; S21. After the inspection robot has preliminarily planned the initial inspection route, the inspection robot is started to inspect the task area, and environmental data and animal data are collected in real time through the sensor group installed inside the inspection robot and the smart ear tag equipped with each animal; The sensor group includes a temperature sensor, a humidity sensor, a carbon dioxide sensor, an air flow sensor, a light intensity sensor and an infrared sensor; S22. Build a data processing system, establish a communication connection between the data processing system and the sensor group and the smart ear tag through a wireless network, and transmit the environmental data and animal data collected by the sensor group and the smart ear tag to the data processing system in real time.

[0025] S23, the data processing system receives the environmental data and the animal data in real time, and pre-processes the environmental data and the animal data, wherein the pre-processing includes animal activity processing, denoising, missing value processing data correction and dimensionless processing, to obtain a health data set; The animal activity volume processing is based on the periodically collected animal positioning data of each animal equipped with a smart ear tag, monitoring its activity trajectory in the breeding house, recording the animal's activity path and residence time in the house, calculating the animal activity volume hd, and then collecting the animal's body temperature dt based on the smart ear tag; The health data set includes an environmental health data set and an animal health data set; The environmental health data set includes environmental temperature wd, environmental humidity sd, carbon dioxide content CO2, air flow rate ls and light intensity gz; The animal health data set includes animal body temperature dt, animal activity hd and animal density dm.

[0026] In this embodiment, the inspection robot can continuously monitor environmental data and animal data through the collaborative work of the sensor group and the smart ear tag, and after transmitting it to the data processing system in real time through the wireless network, it obtains health data through preprocessing steps such as denoising, missing value processing and dimensionless conversion, ensuring the high quality and accuracy of the data, and providing a solid foundation for subsequent health assessment and path optimization. The preprocessed health data group can not only accurately reflect the environmental changes in the breeding house, but also monitor the health status of animals in real time, thereby helping breeding managers to quickly identify potential problems and take effective intervention measures. Through this systematic health monitoring and data processing process, the breeding house can achieve refined and real-time health management, greatly improving the stability of the breeding environment and the protection of animal health, and providing strong support for the intelligent management of the breeding industry.

[0027] Example 4 This embodiment is explained in Example 3, please refer to Figure 1 , specifically: S3 includes S31 and S32; S31, performing summary calculation based on the acquired environmental health data group, obtaining the environmental health status index hjz, and analyzing the environmental health status of each area in the breeding house in real time; The environmental health status index hjz is calculated and obtained by the following formula: ; Where wd i represents the actual temperature of the ith region, wd o Indicates the suitable temperature value for animals in the breeding house, sd i represents the actual humidity of the ith area, sd o Indicates the suitable humidity value for animals in the breeding house, CO 2，i represents the actual carbon dioxide content in the ith region, CO 2，o Indicates the peak carbon dioxide content allowed for animal health in the breeding house, gz i Indicates the actual light intensity of the ith area, gz o It indicates the appropriate light intensity for animals in the breeding house; S32, performing summary calculation based on the obtained animal health data group, obtaining the animal health status index djk, and monitoring the health status of animals in each area in real time; The animal health status index djk is calculated by the following formula: ; Where m represents the total number of animals in the ith region, dt j represents the actual body temperature of the jth animal, dt z Indicates the normal body temperature of animals, hd j represents the activity level of the jth animal, dm i represents the animal density in the i-th area.

[0028] In this embodiment, first, the calculation of the environmental health status index hjz integrates the temperature wd, humidity sd, carbon dioxide content CO 2 and light intensity gz, can reflect in real time whether the environment of each area meets the needs of animal health, thereby providing timely environmental adjustment basis for breeding managers to prevent adverse effects on animal health due to environmental problems. Secondly, the animal health status index djk accurately evaluates the health status of each animal based on indicators such as animal body temperature dt, activity hd and animal density dm, and monitors its activity and health level in real time. The combination of these two indexes not only provides comprehensive quantitative data for the environment and animal health, but also can efficiently identify potential health risks and take timely measures to avoid the spread of diseases or environmental deterioration. Through this comprehensive evaluation mechanism, the environmental optimization and animal health management of breeding houses have become more intelligent and real-time, greatly improving breeding efficiency and animal welfare.

[0029] Example 5 This embodiment is explained in Example 4. Please refer to Figure 1 , specifically: the S4 includes S41 and S42; S41. Based on the obtained environmental health status index hjz and animal health status index djk, a comprehensive health index zhj is obtained, which reflects the comprehensive impact of environmental health on animal health in the breeding house, as well as the nonlinear relationship between the two. The comprehensive health index zhj is calculated by the following formula: ; In the formula, e represents the exponential function, Represents the adjustment coefficient.

[0030] S42, based on the animal health breeding index, preset the first comprehensive health threshold A and the second comprehensive health threshold B, and conduct a comprehensive health assessment with the obtained comprehensive health index zhj, comprehensively analyze the breeding environment and the health status of the animals, and set the inspection priority according to the assessment results, and adjust the inspection route and inspection frequency. The specific assessment plan is as follows; When the comprehensive health index zhj is less than the first comprehensive health threshold A, the area is in a dangerous state, and the first warning information is generated and transmitted to the user end of the relevant personnel through the wireless network, reminding the relevant personnel to take governance measures immediately, and triggering the path planning to re-plan the inspection path; When the comprehensive health threshold A≤comprehensive health index zhj≤the second comprehensive health threshold B, there are unhealthy factors in this area, and the second warning information is generated and transmitted to the user end of relevant personnel through the wireless network, reminding relevant personnel to take governance measures immediately, and triggering path planning to re-plan the inspection path; When the comprehensive health index zhj>the second comprehensive health threshold B, this area is in good condition and maintains normal monitoring.

[0031] In this embodiment, the comprehensive health index zhj is obtained by summarizing and calculating the obtained environmental health status index hjz and the animal health status index djk. This method can reflect the nonlinear relationship between environmental health and animal health, comprehensively evaluate the impact of the breeding environment, and dynamically adjust it in combination with the health status of the animals. When the comprehensive health index zhj is lower than the preset second comprehensive health threshold B, an early warning is automatically triggered, corresponding early warning information is generated, and relevant personnel are notified through the wireless network to take timely governance measures. This mechanism not only effectively prevents health risks that may occur during the breeding process, but also optimizes the inspection route and inspection frequency through intelligent path adjustment, ensuring priority coverage of health risk areas, thereby improving the pertinence and efficiency of inspections. Ultimately, it can provide continuous and accurate health monitoring in a dynamically changing breeding environment, ensure that the safety and health management of the breeding environment and animals is in the best state, and significantly improve the refined management level and operational efficiency of the farm.

[0032] Example 6 This embodiment is explained in Example 5. Please refer to Figure 1 , specifically: the S5 includes S51 and S52; S51, when the comprehensive health assessment triggers the path planning, a dynamic path optimization formula is constructed based on the three-dimensional drawing and using the dynamic path planning algorithm, and then the obtained comprehensive health index zhj is input into the dynamic path optimization model to obtain the dynamic path adjustment index ljt; The dynamic path optimization formula is as follows: ; In the formula, represents the rate at which the comprehensive health index zhj of the i-th region changes over time, jl i represents the distance between the i-th region and the next region, jl i represents the energy loss required to go from the i-th region to the next region, nl max represents the remaining energy of the inspection robot, n represents the total number of regions, and exp represents the exponential function with the natural logarithm e as the base.

[0033] S52. The inspection robot adjusts the path of the dangerous area in priority according to the dynamic path adjustment index ljt, and adjusts the inspection path of this area. If health problems occur in multiple areas at the same time, the robot will re-evaluate and adjust the paths of all relevant areas, and dynamically adjust the path sequence and distance according to the real-time comprehensive health index zhj, giving priority to covering areas where health risks are in a dangerous state; After management by relevant personnel, the inspection path of the inspection robot is adjusted again based on the changing trend of the comprehensive health index zhj obtained through multiple inspections, and the dynamic path adjustment index ljt is used. When the comprehensive health assessment of the inspection task area of ​​the inspection robot is in good condition, the inspection robot readjusts the inspection path to the initial inspection path.

[0034] In this embodiment, the dynamic path optimization algorithm adjusts the inspection path in real time according to the changes in the comprehensive health index zhj, ensuring that the inspection robot can give priority to covering areas with higher health risks, especially areas in dangerous conditions. This dynamic path adjustment mechanism can intelligently adjust the inspection order and path according to the health status of different areas, avoiding the fixed inspection mode commonly seen in traditional methods, and improving the accuracy and pertinence of the inspection. Secondly, when health problems occur in multiple areas at the same time, the inspection robot will re-evaluate the health status of all relevant areas and optimize the path according to the dynamic path adjustment index ljt and the change trend. This adaptive path adjustment method not only improves the flexibility of the inspection robot, but also enhances the emergency response capability of the system, ensuring that health hazards can be discovered and handled in the shortest time. Finally, after multiple inspections, the path is adjusted again according to the gradient of the health index change to ensure that the health problem is completely resolved until all areas return to a good health state, and the inspection robot readjusts the inspection path to the initial inspection path. Through this series of dynamic adjustments, the system can continuously optimize the inspection path, provide efficient and sophisticated health management, and ensure that the environment and animal health of the breeding house are best protected.

[0035] Example 7 Please refer to Figure 2 , a navigation system for an inspection robot in a breeding house, including an initial inspection path planning module, an inspection collection module, a health analysis module, a comprehensive health assessment module and a path adjustment module; The initial inspection path planning module is used to divide the large animal breeding house into several areas, deploy several inspection robots, use the shortest path algorithm, construct the path optimization objective function, preliminarily plan the initial inspection path of the inspection robot, and use the depth-first search algorithm to cover the area without duplication; The inspection and collection module collects environmental data and animal data in real time through the sensor group installed inside the inspection robot and the smart ear tag equipped with each animal, and constructs a data processing system to pre-process the environmental data and animal data to obtain a health data group; The health analysis module is used to perform summary calculations based on the acquired health data group to obtain the environmental health status index hjz and the animal health status index djk; The comprehensive health assessment module is used to perform summary calculation based on the obtained environmental health status index hjz and animal health status index djk, obtain the comprehensive health index zhj, and perform comprehensive health assessment with the preset first comprehensive health threshold A and second comprehensive health threshold B, and comprehensively analyze the health status of the breeding environment and animals; The path adjustment module is used to build a dynamic path optimization model when the comprehensive health assessment triggers path planning, and then input the obtained comprehensive health index zhj into the dynamic path optimization model to obtain the dynamic path adjustment index ljt. The inspection robot adjusts the inspection path according to the dynamic path adjustment index ljt until the comprehensive health assessment of the inspection task area of ​​the inspection robot is in good condition. The inspection robot readjusts the inspection path to the initial inspection path.

[0036] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A navigation method for an inspection robot in a breeding house, characterized in that: The following steps are involved: S1. Divide the large animal breeding house into several areas, deploy several inspection robots, use the shortest path algorithm, construct the path optimization objective function, preliminarily plan the initial inspection path of the inspection robot, and use the depth-first search algorithm to cover the area without duplication; S2, collect environmental data and animal data in real time through the sensor group installed inside the inspection robot and the smart ear tag equipped with each animal, and build a data processing system to pre-process the environmental data and animal data to obtain a health data group; S3, performing summary calculation based on the acquired health data group to obtain the environmental health status index hjz and the animal health status index djk; S4. Summarize and calculate the obtained environmental health status index hjz and animal health status index djk to obtain the comprehensive health index zhj, and perform a comprehensive health assessment with the preset first comprehensive health threshold A and second comprehensive health threshold B to comprehensively analyze the health status of the breeding environment and animals; S5. When the comprehensive health assessment triggers path planning, a dynamic path optimization model is constructed, and the obtained comprehensive health index zhj is input into the dynamic path optimization model to obtain the dynamic path adjustment index ljt. The inspection robot adjusts the inspection path according to the dynamic path adjustment index ljt until the comprehensive health assessment of the inspection task area of ​​the inspection robot is in good condition. At this time, the inspection robot readjusts the inspection path to the initial inspection path.

2. The navigation method of a patrol robot in a breeding house according to claim 1, characterized in that: Said S1 includes S11, S12 and S13; S11. Divide the large animal breeding house into several areas according to the animal species and layout structure in the breeding house, deploy several inspection robots, and set inspection tasks for each inspection robot, wherein the inspection tasks include inspecting multiple areas; S12. Obtain all inspection paths in the breeding house according to the three-dimensional drawing of the breeding house. Obtain the distance between each area and other areas according to the inspection area of ​​each inspection robot and the route within the inspection area. Use the shortest path algorithm, combine the location of the charging pile, the inspection task and the energy consumption to plan the shortest inspection path, and construct the path optimization objective function to preliminarily plan the initial inspection path of the inspection robot. The specific path optimization objective function is: , where P represents the node order of the path, jl(i, i+1) represents the distance between region i and region i+1, nl(i, i+1) represents the energy consumption between region i and region i+1, and n represents the total number of regions; S13. During the inspection path planning process, the depth-first search algorithm is used to perform non-repetitive coverage of the area, record the areas that the robot has already planned, and avoid invalid returns to the areas that have already been inspected.

3. The navigation method of a patrol robot in a breeding house according to claim 2, characterized in that: The S2 includes S21, S22 and S23; S21. After the inspection robot has preliminarily planned the initial inspection route, the inspection robot is started to inspect the task area, and environmental data and animal data are collected in real time through the sensor group installed inside the inspection robot and the smart ear tag equipped with each animal; The sensor group includes a temperature sensor, a humidity sensor, a carbon dioxide sensor, an air flow sensor, a light intensity sensor and an infrared sensor; S22. Build a data processing system, establish a communication connection between the data processing system and the sensor group and the smart ear tag through a wireless network, and transmit the environmental data and animal data collected by the sensor group and the smart ear tag to the data processing system in real time.

4. The navigation method of a patrol robot in a breeding house according to claim 3, characterized in that: S23, the data processing system receives the environmental data and the animal data in real time, and pre-processes the environmental data and the animal data, wherein the pre-processing includes animal activity processing, denoising, missing value processing data correction and dimensionless processing, to obtain a health data set; The animal activity volume processing is based on the periodically collected animal positioning data of each animal equipped with a smart ear tag, monitoring its activity trajectory in the breeding house, recording the animal's activity path and residence time in the house, calculating the animal activity volume hd, and then collecting the animal's body temperature dt based on the smart ear tag; The health data set includes an environmental health data set and an animal health data set; The environmental health data set includes environmental temperature wd, environmental humidity sd, carbon dioxide content CO2, air flow rate ls and light intensity gz; The animal health data set includes animal body temperature dt, animal activity hd and animal density dm.

5. The navigation method of a patrol robot in a breeding house according to claim 4, characterized in that: The S3 includes S31 and S32; S31, performing summary calculation based on the acquired environmental health data group, obtaining the environmental health status index hjz, and analyzing the environmental health status of each area in the breeding house in real time; The environmental health status index hjz is calculated and obtained by the following formula: ； Where wd i represents the actual temperature of the ith region, wd o Indicates the suitable temperature value for animals in the breeding house, sd i represents the actual humidity of the ith area, sd o Indicates the suitable humidity value for animals in the breeding house, CO 2，i represents the actual carbon dioxide content in the ith region, CO 2，o Indicates the peak carbon dioxide content allowed for animal health in the breeding house, gz i Indicates the actual light intensity of the ith area, gz o It indicates the appropriate light intensity for animals in the breeding house; S32, performing summary calculation based on the obtained animal health data group, obtaining the animal health status index djk, and monitoring the health status of animals in each area in real time; The animal health status index djk is calculated by the following formula: ； Where m represents the total number of animals in the ith region, dt j represents the actual body temperature of the jth animal, dt z Indicates the normal body temperature of animals, hd j represents the activity level of the jth animal, dm i represents the animal density in the i-th area.

6. The navigation method of a patrol robot in a breeding house according to claim 5, characterized in that: The S4 includes S41 and S42; S41. Based on the obtained environmental health status index hjz and animal health status index djk, a comprehensive health index zhj is obtained, which reflects the comprehensive impact of environmental health on animal health in the breeding house, as well as the nonlinear relationship between the two. The comprehensive health index zhj is calculated by the following formula: ； In the formula, e represents the exponential function, Represents the adjustment coefficient.

7. The navigation method of a patrol robot in a breeding house according to claim 6, characterized in that: S42, based on the animal health breeding index, preset the first comprehensive health threshold A and the second comprehensive health threshold B, and conduct a comprehensive health assessment with the obtained comprehensive health index zhj, comprehensively analyze the breeding environment and the health status of the animals, and set the inspection priority according to the assessment results, and adjust the inspection route and inspection frequency. The specific assessment plan is as follows; When the comprehensive health index zhj is less than the first comprehensive health threshold A, the area is in a dangerous state, and the first warning information is generated and transmitted to the user end of the relevant personnel through the wireless network, reminding the relevant personnel to take governance measures immediately, and triggering the path planning to re-plan the inspection path; When the comprehensive health threshold A≤comprehensive health index zhj≤the second comprehensive health threshold B, there are unhealthy factors in this area, and the second warning information is generated and transmitted to the user end of relevant personnel through the wireless network, reminding relevant personnel to take governance measures immediately, and triggering path planning to re-plan the inspection path; When the comprehensive health index zhj>the second comprehensive health threshold B, this area is in good condition and maintains normal monitoring.

8. The navigation method of a patrol robot in a breeding house according to claim 7, characterized in that: The S5 includes S51 and S52; S51, when the comprehensive health assessment triggers the path planning, a dynamic path optimization formula is constructed based on the three-dimensional drawing and using the dynamic path planning algorithm, and then the obtained comprehensive health index zhj is input into the dynamic path optimization model to obtain the dynamic path adjustment index ljt; The dynamic path optimization formula is as follows: ； In the formula, represents the rate at which the comprehensive health index zhj of the i-th region changes over time, jl i represents the distance between the i-th region and the next region, jl i represents the energy loss required to go from the i-th region to the next region, nl max represents the remaining energy of the inspection robot, n represents the total number of regions, and exp represents the exponential function with the natural logarithm e as the base.

9. The navigation method of a patrol robot in a breeding house according to claim 8, characterized in that: S52. The inspection robot adjusts the path of the dangerous area in priority according to the dynamic path adjustment index ljt, and adjusts the inspection path of this area. If health problems occur in multiple areas at the same time, the robot will re-evaluate and adjust the paths of all relevant areas, and dynamically adjust the path sequence and distance according to the real-time comprehensive health index zhj, giving priority to covering areas where health risks are dangerous; After management by relevant personnel, the inspection path of the inspection robot is adjusted again based on the changing trend of the comprehensive health index zhj obtained through multiple inspections, and the dynamic path adjustment index ljt is used. When the comprehensive health assessment of the inspection task area of ​​the inspection robot is in good condition, the inspection robot readjusts the inspection path to the initial inspection path.

10. A navigation system for a patrol robot in a breeding house, comprising a navigation method for a patrol robot in a breeding house according to any one of claims 1 to 9, characterized in that: It includes initial inspection route planning module, inspection collection module, health analysis module, comprehensive health assessment module and route adjustment module; The initial inspection path planning module is used to divide the large animal breeding house into several areas, deploy several inspection robots, use the shortest path algorithm, construct the path optimization objective function, preliminarily plan the initial inspection path of the inspection robot, and use the depth-first search algorithm to cover the area without duplication; The inspection and collection module collects environmental data and animal data in real time through the sensor group installed inside the inspection robot and the smart ear tag equipped with each animal, and constructs a data processing system to pre-process the environmental data and animal data to obtain a health data group; The health analysis module is used to perform summary calculations based on the acquired health data group to obtain the environmental health status index hjz and the animal health status index djk; The comprehensive health assessment module is used to perform summary calculation based on the obtained environmental health status index hjz and animal health status index djk, obtain the comprehensive health index zhj, and perform comprehensive health assessment with the preset first comprehensive health threshold A and second comprehensive health threshold B, and comprehensively analyze the health status of the breeding environment and animals; The path adjustment module is used to build a dynamic path optimization model when the comprehensive health assessment triggers path planning, and then input the obtained comprehensive health index zhj into the dynamic path optimization model to obtain the dynamic path adjustment index ljt. The inspection robot adjusts the inspection path according to the dynamic path adjustment index ljt until the comprehensive health assessment of the inspection task area of ​​the inspection robot is in good condition. The inspection robot then readjusts the inspection path to the initial inspection path.

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