Navigation method and system of a breeding house inspection robot

Abstract

The application discloses a kind of navigation method and system of breeding house inside inspection robot, it is related to intelligent agricultural technology field, the method is by dividing breeding house into several regions, in combination with the shortest path algorithm and depth-first search algorithm, the path of preliminary planning of the inspection robot is patrolled, and environment data and animal data are collected in real time using internal sensor group and intelligent ear tag, by preprocessing, obtain health data group, calculate the health state index of environment and the health state index of animal, further obtain comprehensive health index, and preset first comprehensive health threshold and second comprehensive health threshold are evaluated.In health evaluation triggers path planning, dynamic path optimization model is used to adjust the inspection path, and the area with higher health risk is preferentially covered until the health evaluation of the inspection task area reaches a good state.This method can effectively improve the health monitoring efficiency of breeding environment and animals, and ensure health management and risk control during breeding process.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of intelligent agricultural technology, in particular to a navigation method and system of a breeding house inspection robot. BACKGROUND

[0002] With the growth of global population and the higher demand for food safety and quality, especially in the farming industry, it is facing unprecedented challenges. Traditional farming methods often overlook the fine management of animal health and environmental monitoring while improving production, leading to resource waste, environmental pollution and frequent animal diseases. In addition, with the rising labor costs and the increasing complexity of the farming environment, manual inspection and management have been difficult to meet the needs of efficiency and precision. Therefore, with the help of automation and intelligent technology for farming management, especially through the inspection robot for environmental and animal health monitoring, has become the key way to solve the problems of low efficiency, poor precision and slow emergency response in the farming industry, and promoting the development of intelligent agriculture has become an important direction of global agricultural modernization.

[0003] Although the existing breeding house inspection robots have improved the breeding efficiency to some extent, there are still some problems in actual application, especially in the aspects of patrol 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 problem of multiple factors such as energy consumption, device charging and regional health status in large-scale breeding houses, resulting in that the inspection robot may not be able to cover all key areas due to insufficient power or too long path. On the other hand, the current health monitoring system often relies too much on single data input when assessing the environmental 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 breeding environment. Therefore, although the robot can complete the inspection task, it lacks real-time health assessment mechanism and dynamic path adjustment ability, which affects the comprehensive management effect of the breeding environment and animal health when the robot encounters a health risk area. SUMMARY

[0004] In view of the deficiencies of the prior art, the present application provides a navigation method and system of a breeding house inspection robot, which solves the problems in the background art.

[0005] To achieve the above purpose, the present application is realized by the following technical scheme: a navigation method of a breeding house inspection robot, comprising the following steps:

[0006] S1, divide a large animal breeding house into several areas, put in several inspection robots, use the shortest path algorithm to construct a path optimization objective function, preliminarily plan the initial patrol path of the inspection robot, and cover the areas without repetition through the depth-first search algorithm;

[0007] S2, collecting environmental data and animal data in real time through a sensor group installed inside the inspection robot and a smart ear tag equipped with each animal, and constructing a data processing system to preprocess the environmental data and animal data to obtain a health data set;

[0008] S3, performing summary calculation according to the obtained health data set to obtain an environmental health state index hjz and an animal health state index djk;

[0009] S4, performing summary calculation according to the obtained environmental health state index hjz and animal health state index djk to obtain a comprehensive health index zhj, and performing comprehensive health evaluation with a preset first comprehensive health threshold A and a second comprehensive health threshold B to comprehensively analyze the health state of the breeding environment and the animals;

[0010] S5, when the comprehensive health evaluation triggers path planning, constructing a dynamic path optimization model, inputting the obtained comprehensive health index zhj into the dynamic path optimization model to obtain a dynamic path adjustment index ljt, and adjusting the inspection path of the inspection robot according to the dynamic path adjustment index ljt until the comprehensive health evaluation of the inspection task area of the inspection robot is good, and the inspection robot re-adjusts the inspection path to the initial inspection path.

[0011] Preferably, the S1 comprises S11, S12 and S13;

[0012] S11, according to the animal species and layout structure in the large animal breeding house, the breeding house is divided into several areas, several inspection robots are put in, and each inspection robot is set with an inspection task, the inspection task including inspecting multiple areas;

[0013] S12, obtaining all inspection paths in the breeding house according to the three-dimensional drawing of the breeding house, obtaining the distance between each area and other areas according to the inspection area of each inspection robot and the route in the inspection area, planning the shortest inspection path by using the shortest path algorithm in combination with the charging pile position, the inspection task and the energy consumption, and constructing a path optimization objective function to preliminarily plan the initial inspection path of the inspection robot, and the specific path optimization objective function is: wherein P represents the node order of the path, jl(i, i+1) represents the distance between area i and area i+1, nl(i, i+1) represents the energy consumption between area i and area i+1, and n represents the total number of areas;

[0014] S13, in the inspection path planning process, the deep first search algorithm is used for non-repeated coverage of the area, the area that has been planned by the robot is recorded, and the return to the area that has been inspected is avoided.

[0015] Preferably, S2 comprises S21, S22 and S23;

[0016] S21, after the initial patrol path is preliminarily planned by the patrol robot, the patrol robot starts to patrol the task area, and through the sensor group installed in the patrol robot and the intelligent ear tag equipped for each animal, environmental data and animal data are collected in real time;

[0017] The sensor group comprises a temperature sensor, a humidity sensor, a carbon dioxide sensor, an air flow sensor, an illumination intensity sensor and an infrared sensor;

[0018] S22, a data processing system is constructed, the data processing system is communicatively connected with the sensor group and the intelligent ear tag through a wireless network, and the environmental data and the animal data collected by the sensor group and the intelligent ear tag are transmitted to the data processing system in real time.

[0019] Preferably, 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, the pre-processing comprises animal activity amount processing, denoising, missing value processing data correction and dimensionless processing, and a health data group is obtained;

[0020] The animal activity amount processing is based on the intelligent ear tag equipped for each animal, periodically collected animal positioning data, monitoring of the activity track of the animal in the breeding house, recording of the activity path and the residence time of the animal in the house, calculation of the animal activity amount hd, and collection of the animal body temperature dt by the intelligent ear tag;

[0021] The health data group comprises an environmental health data group and an animal health data group;

[0022] The environmental health data group comprises an environmental temperature wd, an environmental humidity sd, a carbon dioxide content CO2, an air flow rate ls and an illumination intensity gz;

[0023] The animal health data group comprises an animal body temperature dt, an animal activity amount hd and an animal density dm.

[0024] Preferably, S3 comprises S31 and S32;

[0025] S31, based on the obtained environmental health data group, an environmental health state index hjz is calculated by summarizing calculation, and the environmental health of each area in the breeding house is analyzed in real time;

[0026] The environmental health state index hjz is calculated by the following formula;

[0027]

[0028] In the formula, wdi actual temperature of the i-th area, wd o optimal temperature value for animals in the breeding house, sd i actual humidity of the i-th area, sd o optimal humidity value for animals in the breeding house, CO 2，i actual carbon dioxide content of the i-th area, CO 2，o peak value of carbon dioxide content allowed to be reached by animals in the breeding house, gz i actual light intensity of the i-th area, gz o optimal light intensity for animals in the breeding house;

[0029] S32, performing summary calculation according to the obtained animal health data set to obtain an animal health status index djk, and monitoring the health status of animals in each area in real time;

[0030] The animal health status index djk is obtained by calculation according to the following formula:

[0031]

[0032] In the formula, m represents the total number of animals in the i-th area, dt j actual body temperature of the j-th animal, dt z normal body temperature of animals, hd j activity amount of the j-th animal, dm i animal density in the i-th area.

[0033] Preferably, the S4 comprises S41 and S42.

[0034] S41, performing summary calculation according to the obtained environmental health status index hjz and animal health status index djk to obtain a comprehensive health index zhj, reflecting the comprehensive influence of environmental health on the health of animals in the breeding house, and the nonlinear relationship between the two.

[0035] The comprehensive health index zhj is obtained by calculation according to the following formula:

[0036]

[0037] In the formula, e represents an exponential function, and a represents an adjustment coefficient.

[0038] Preferably, S42, based on the animal health breeding index, preset a first comprehensive health threshold A and a second comprehensive health threshold B, and perform comprehensive health evaluation with the obtained comprehensive health index zhj, comprehensively analyze the health status of the breeding environment and animals, and according to the evaluation result, set the patrol priority, and adjust the patrol route and patrol frequency, and the specific evaluation scheme is as follows:

[0039] When the comprehensive health index zhj is less than the first comprehensive health threshold A, the area is in a dangerous state, the first warning information is generated and transmitted to the relevant personnel user end through the wireless network, the relevant personnel are reminded to take immediate control measures, and path planning is triggered to re-plan the inspection path;

[0040] When the first comprehensive health threshold A is less than or equal to the comprehensive health index zhj and less than or equal to the second comprehensive health threshold B, the area has unhealthy factors, the second warning information is generated and transmitted to the relevant personnel user end through the wireless network, the relevant personnel are reminded to take immediate control measures, and path planning is triggered to re-plan the inspection path;

[0041] When the comprehensive health index zhj is greater than the second comprehensive health threshold B, the area is in a good state, and normal monitoring is maintained.

[0042] Preferably, the S5 comprises S51 and S52;

[0043] S51, when the comprehensive health assessment triggers path planning, a dynamic path optimization formula is constructed according to the three-dimensional drawing and using a dynamic path planning algorithm, and then the obtained comprehensive health index zhj is input into the dynamic path optimization model to obtain a dynamic path adjustment index ljt;

[0044] The dynamic path optimization formula is as follows:

[0045]

[0046] In the formula, zhj represents the comprehensive health index of the i-th area, t represents time, l represents the dynamic path adjustment index, nl represents the energy loss required for the i-th area to the next area, nl represents the distance between the i-th area and the next area, nl represents the energy loss required for the i-th area to the next area, and n represents the total number of areas. represents the rate of change of the comprehensive health index zhj of the i-th area with time, jl i represents the distance between the i-th area and the next area, jl i represents the energy loss required for the i-th area to the next area, nl max represents the remaining energy of the inspection robot, n represents the total number of areas, and exp represents the exponential function with base e.

[0047] Preferably, S52, the inspection robot adjusts the path of the area in a dangerous state according to the dynamic path adjustment index ljt, adjusts the inspection path of the area, if multiple areas have health problems at the same time, the robot will re-evaluate and adjust the paths of all related areas, and dynamically adjust the path order and distance according to the real-time comprehensive health index zhj, and preferentially cover the areas in a dangerous state of health risk;

[0048] After the relevant personnel governance, according to the change trend of the comprehensive health index zhj obtained through multiple inspections, the inspection robot adjusts the inspection path through the dynamic path adjustment index ljt again, until the comprehensive health evaluation of the inspection task area of the inspection robot is all in good condition, the inspection robot adjusts the inspection path to the initial inspection path.

[0049] A navigation system of an inspection robot in a breeding house comprises an initial inspection path planning module, an inspection collection module, a health analysis module, a comprehensive health evaluation module and a path adjustment module.

[0050] The initial inspection path planning module is used to divide a large animal breeding house into several areas, release several inspection robots, use a shortest path algorithm to construct a path optimization objective function, preliminarily plan an initial inspection path of the inspection robot, and perform non-repeated coverage of the areas through a depth-first search algorithm.

[0051] The inspection collection module collects environmental data and animal data in real time through a sensor group installed in the inspection robot and an intelligent ear tag equipped with each animal, and constructs a data processing system to preprocess the environmental data and animal data and obtain a health data group.

[0052] The health analysis module is used to aggregate and calculate the obtained health data group to obtain an environmental health state index hjz and an animal health state index djk.

[0053] The comprehensive health evaluation module is used to aggregate and calculate the obtained environmental health state index hjz and animal health state index djk to obtain a comprehensive health index zhj, and perform comprehensive health evaluation with a preset first comprehensive health threshold A and a second comprehensive health threshold B to comprehensively analyze the health state of the breeding environment and animals.

[0054] The path adjustment module is used to construct a dynamic path optimization model when the comprehensive health evaluation triggers path planning, input the obtained comprehensive health index zhj into the dynamic path optimization model to obtain a dynamic path adjustment index ljt, and the inspection robot adjusts the inspection path according to the dynamic path adjustment index ljt until the comprehensive health evaluation of the inspection task area of the inspection robot is all in good condition, and the inspection robot adjusts the inspection path to the initial inspection path.

[0055] The present application provides a navigation method and system of an inspection robot in a breeding house.

[0056] (1) The method divides the large animal breeding house into several inspection areas, and according to the layout of the breeding house and the different types of animals, multiple inspection robots are put in. Each inspection robot plans the inspection path according to the preset task, the shortest path algorithm and the depth first search algorithm, and ensures that the path is not repeated. This strategy not only maximizes the inspection efficiency, but also effectively avoids repeated inspection, ensures that each area is fully monitored, and greatly reduces unnecessary energy consumption and inspection time.

[0057] (2) The method integrates sensor groups and animal intelligent ear tags to collect environmental and animal data in real time, provides accurate health evaluation basis, can monitor the changes of the breeding environment in real time, and at the same time, the animal intelligent ear tag records the activity track and body temperature of each animal and other key health data. Through the preprocessing function of the data processing system, these collected data are denoised, de-missing and dimensionless, and the health data set is obtained and calculated, and finally the environmental health state index hjz and the animal health state index djk are generated. These health data provide accurate data support for subsequent health evaluation and dynamic path optimization, ensuring that the health status of the environment and animals can be monitored and effectively managed in real time during the breeding process.

[0058] (3) The method calculates the comprehensive health index zhj by summarizing the environmental health state index hjz and the animal health state index djk, and conducts comprehensive health evaluation with the preset first comprehensive health threshold A and the second comprehensive health threshold B, and analyzes the health status of the breeding environment and animals. Reflects the influence of the breeding environment on the health of animals and the interaction between them. 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 conditions are preferentially inspected. Through the dynamic path optimization model, the inspection robot can adjust the inspection route according to the real-time changes of the health index, preferentially cover the areas with high health risk, and ensure that the health problems of the breeding environment and animals can be effectively handled in time. After treatment, it can also automatically adjust the inspection path according to the change trend of the health index and the results of multiple inspections, until the health status of all areas reaches a good level, and the inspection robot will adjust the inspection path to the initial inspection path. Through this mechanism, the inspection robot can continuously provide efficient and accurate health monitoring, and ensure the optimal protection of the environment and animal health in the breeding house. BRIEF DESCRIPTION OF DRAWINGS

[0059] Figure 1 It is a navigation method flow diagram of the breeding house inspection robot of the present application;

[0060] Figure 2 It is a navigation system step diagram of the breeding house inspection robot of the present application. DETAILED DESCRIPTION

[0061] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0062] Embodiment 1

[0063] Please refer to Figure 1 The present application provides a navigation method of a breeding house inspection robot. To achieve the above object, the present application is implemented by the following technical solutions: comprising the following steps:

[0064] S1, a large animal breeding house is divided into several areas, and several inspection robots are put in, a shortest path algorithm is used to construct a path optimization objective function, an initial inspection path of the inspection robot is preliminarily planned, and a depth-first search algorithm is used for non-repeated coverage of the area;

[0065] S2, through the sensor group installed in the inspection robot and the intelligent ear tag equipped for each animal, environmental data and animal data are collected in real time, a data processing system is constructed to pre-process the environmental data and animal data, and a health data group is obtained;

[0066] S3, the obtained health data group is summarized and calculated to obtain an environmental health state index hjz and an animal health state index djk;

[0067] S4, the obtained environmental health state index hjz and animal health state index djk are summarized and calculated to obtain a comprehensive health index zhj, and a comprehensive health evaluation is performed with a preset first comprehensive health threshold A and a second comprehensive health threshold B, and a comprehensive analysis of the health state of the breeding environment and the animals is performed;

[0068] S5, when the comprehensive health evaluation triggers path planning, a dynamic path optimization model is constructed, the obtained comprehensive health index zhj is input into the dynamic path optimization model, a dynamic path adjustment index ljt is obtained, the inspection robot adjusts the inspection path according to the dynamic path adjustment index ljt, and until the comprehensive health evaluation of the inspection task area of the inspection robot is good, the inspection robot re-adjusts the inspection path to the initial inspection path.

[0069] In this embodiment, by dividing the breeding house into several areas and deploying multiple inspection robots, a shortest path algorithm is used to construct an optimal path objective function, and a preliminary inspection path is planned, and a depth-first search algorithm is used to realize the non-repetitive coverage of the area. This method can effectively improve the working efficiency of the inspection robot, avoid the omission of inspection caused by repeated path or insufficient coverage in the traditional inspection method, and ensure that each area can be effectively monitored. Compared with the prior art, the method not only considers the distance and time, but also fully integrates the charging pile position, the inspection task and the energy consumption, so as to realize more accurate and optimized path design. By combining the inspection robot with the sensor group and the intelligent ear tag, the method can collect the environmental data and animal data in the breeding house in real time, and preprocess the data through the data processing system to obtain the health data group. Compared with the traditional manual inspection method, the method realizes real-time data collection and automatic processing, improves the efficiency and accuracy of data processing, and avoids the delay and error in manual monitoring. The real-time evaluation of the comprehensive health state can dynamically reflect the changes of the breeding environment and the health of the animals through the calculation of the environmental health state index hjz and the animal health state index djk, and provide more accurate health monitoring and management scheme. On the basis of comprehensive health evaluation, the method calculates the comprehensive health index zhj through the environmental health state index hjz and the animal health state index djk, and carries out comprehensive health evaluation with the first comprehensive health threshold A and the second comprehensive health threshold B, analyzes the health state of the breeding environment and the animals, adjusts the inspection path according to the change of the comprehensive health index zhj, and preferentially covers the areas with high health risk. This innovative measure can make the inspection robot automatically adjust the path according to the environmental change, so as to timely respond to possible health risks and reduce the spread and omission of health problems. Compared with the traditional method which relies on manual inspection and fixed path, the dynamic path adjustment mechanism of the present application greatly improves the flexibility and intelligent level of the inspection. Finally, by continuously optimizing the inspection path and adjusting the inspection frequency, the method can ensure that the comprehensive health evaluation of each area in the breeding house always remains in a good state, significantly improves the health management efficiency of the breeding process and the controllability of the breeding environment, thereby reducing the risk of animal diseases and improving the overall breeding efficiency.

[0070] Embodiment 2

[0071] This embodiment is an explanation and description in embodiment 1, please refer to Figure 1 , in particular: the S1 includes S11, S12 and S13;

[0072] S11, according to the animal species and layout structure in the large animal breeding house, the breeding house is divided into several areas, several inspection robots are put in, and each inspection robot is set with a patrol task, the patrol task includes patrolling multiple areas;

[0073] S12, all patrol paths in the breeding house are obtained according to the three-dimensional drawing of the breeding house, the distance between each area and other areas is obtained according to the inspection area of each inspection robot and the route in the inspection area, the shortest path algorithm is used, the shortest patrol path is planned combined with the charging pile position, the patrol task and the energy consumption, and the path optimization objective function is constructed, the initial patrol path of the inspection robot is preliminarily planned, and the specific path optimization objective function is: Wherein, P represents the node order of the path, jl(i, i+1) represents the distance between area i and area i+1, nl(i, i+1) represents the energy consumption between area i and area i+1, and n represents the total number of areas;

[0074] S13, in the inspection path planning process, the deep first search algorithm is used for repeated coverage of the area, the area that has been planned by the robot is recorded, and the return to the area that has been inspected is avoided.

[0075] In this embodiment, according to the needs of different animal species and layout structure, the area is reasonably divided and multiple inspection robots are put in, each robot undertakes the patrol task of multiple areas, this regional allocation not only optimizes the resource utilization, but also ensures that each area can be timely inspected and monitored. By combining the three-dimensional drawing of the breeding house, the distance between each area is accurately calculated, and the shortest path algorithm is used to consider the charging pile position, the patrol task and the energy consumption, and the optimal patrol path is planned, which significantly improves the efficiency and accuracy of path planning, avoids unnecessary energy waste and time waste. This path optimization not only reduces the empty running of the robot in the inspection process, but also provides stable guarantee for the smooth completion of the task. Finally, the deep first search algorithm ensures that each area is effectively covered, and the invalid return of the robot in the inspected area is avoided, which effectively improves the inspection efficiency and avoids resource waste, providing comprehensive support for the intelligent inspection of the breeding house. These measures comprehensively improve the comprehensiveness and efficiency of the inspection, and at the same time of guaranteeing the optimal allocation of energy and time resources, avoid repeated work, and significantly improve the operation benefit of the whole system.

[0076] Embodiment 3

[0077] This embodiment is an explanation and description in embodiment 2, please refer to Figure 1 , specifically: the S2 includes S21, S22 and S23;

[0078] S21, when the inspection robot preliminarily plans the initial inspection path, the inspection robot starts to inspect the task area, and through the sensor group installed in the inspection robot and the intelligent ear tag equipped with each animal, the environmental data and animal data are collected in real time;

[0079] The sensor group includes a temperature sensor, a humidity sensor, a carbon dioxide sensor, an air flow sensor, an illumination intensity sensor and an infrared sensor;

[0080] S22, a data processing system is constructed, the data processing system is connected with the sensor group and the intelligent ear tag through wireless network, and the environmental data and animal data collected by the sensor group and the intelligent ear tag are transmitted to the data processing system in real time.

[0081] S23, the data processing system receives the environmental data and animal data in real time, and pre-processes the environmental data and animal data, the pre-processing includes animal activity amount processing, denoising, missing value processing data correction and dimensionless processing, and a health data group is obtained;

[0082] The animal activity amount processing is based on the intelligent ear tag equipped with each animal, the periodic animal positioning data is collected, the activity track of the animal in the breeding house is monitored, the activity path and the residence time of the animal in the house are recorded, the animal activity amount hd is calculated, and then the animal body temperature dt is collected by the intelligent ear tag;

[0083] The health data group includes an environmental health data group and an animal health data group;

[0084] The environmental health data group includes environmental temperature wd, environmental humidity sd, carbon dioxide content CO2, air flow rate ls and illumination intensity gz;

[0085] The animal health data group includes animal body temperature dt, animal activity amount hd and animal density dm.

[0086] In this embodiment, the inspection robot can continuously monitor the environmental data and animal data through the cooperative work of the sensor group and the intelligent ear tag, and after real-time transmission to the data processing system through the wireless network, the health data is obtained through the pre-processing steps of denoising, missing value processing and dimensionless processing, which ensures the high quality and accuracy of the data, and provides a solid foundation for subsequent health evaluation and path optimization. The health data group after pre-processing can not only accurately reflect the environmental changes in the breeding house, but also can monitor the health status of the animals in real time, and further help the 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 realize fine and real-time health management, greatly improve the stability of the breeding environment and the guarantee of animal health, and provide strong support for the intelligent management of the breeding industry.

[0087] Embodiment 4

[0088] This embodiment is an explanation and illustration in embodiment 3, please refer to Figure 1 Specifically, the S3 comprises S31 and S32;

[0089] S31, according to the acquired environmental health data set, the environmental health state index hjz is obtained by summarizing calculation, and the environmental health of each area in the breeding house is analyzed in real time;

[0090] The environmental health state index hjz is calculated by the following formula;

[0091]

[0092] In the formula, wd i represents the actual temperature of the i-th area, wd o represents the animal suitable temperature value in the breeding house, sd i represents the actual humidity of the i-th area, sd o represents the animal suitable humidity value in the breeding house, CO 2，i represents the actual carbon dioxide content of the i-th area, CO 2，o represents the carbon dioxide content peak value that the animal health can reach in the breeding house, gz i represents the actual light intensity of the i-th area, gz o represents the animal suitable light intensity in the breeding house;

[0093] S32, according to the acquired animal health data set, the animal health state index djk is obtained by summarizing calculation, and the health state of the animal in each area is monitored in real time;

[0094] The animal health state index djk is calculated by the following formula;

[0095]

[0096] In the formula, m represents the total number of animals in the i-th area, dt j represents the actual body temperature of the j-th animal, dt z represents the normal body temperature of the animal, hd j represents the activity of the j-th animal, dm i represents the animal density in the i-th area.

[0097] In this embodiment, first, the calculation of the environmental health status index hjz takes into account key factors such as temperature wd, humidity sd, carbon dioxide content CO2, and light intensity gz, and can reflect in real time whether the environment in each area meets the needs of animal health, thereby providing timely environmental adjustment basis for breeders and preventing adverse effects on animal health due to environmental problems. Second, the animal health status index djk is based on animal body temperature dt, activity amount hd, and animal density dm, and accurately assesses the health status of each animal and monitors its activity and health level in real time. The combination of these two indexes not only provides comprehensive quantitative data for environmental and animal health, but also efficiently identifies potential health risks, takes timely measures, and avoids the spread of disease or environmental deterioration. Through this comprehensive evaluation mechanism, the environmental optimization and animal health management of the breeding house become more intelligent and real-time, greatly improving breeding efficiency and animal welfare.

[0098] Embodiment 5

[0099] This embodiment is an explanation and description in Embodiment 4, please refer to Figure 1 , specifically: the S4 includes S41 and S42;

[0100] S41, according to the acquired environmental health status index hjz and animal health status index djk, the comprehensive health index zhj is obtained by summarizing and calculating, which reflects the comprehensive influence of environmental health on the health of animals in the breeding house, as well as the nonlinear relationship between the two;

[0101] The comprehensive health index zhj is calculated by the following formula:

[0102]

[0103] In the formula, e represents the exponential function, and a represents the adjustment coefficient.

[0104] 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 evaluation is performed with the acquired comprehensive health index zhj, the health status of the breeding environment and the animals is comprehensively analyzed, and according to the evaluation result, the patrol priority is set, and the patrol route and patrol frequency are adjusted, and the specific evaluation scheme is as follows:

[0105] When the comprehensive health index zhj is less than the first comprehensive health threshold A, the area is in a dangerous state, a first warning information is generated and transmitted to the related personnel user end through the wireless network, reminding the related personnel to take immediate control measures, and triggering path planning to re-plan the patrol path;

[0106] When the first comprehensive health threshold A ≤ comprehensive health index zhj ≤ second comprehensive health threshold B, there are unhealthy factors in this area. A second early warning message is generated and transmitted to the relevant personnel's user terminal via wireless network, reminding the relevant personnel to take immediate remedial measures and triggering path planning to re-plan the inspection path.

[0107] When the comprehensive health index zhj > the second comprehensive health threshold B, the condition of this area is good and should be monitored normally.

[0108] In this embodiment, a comprehensive health index zhj is obtained by summarizing the acquired environmental health status index hjz and animal health status index djk. This method reflects the non-linear relationship between environmental health and animal health, comprehensively assesses the impact of the breeding environment, and dynamically adjusts the index in conjunction with animal health status. When the comprehensive health index zhj falls below a preset second comprehensive health threshold B, an early warning is automatically triggered, generating corresponding warning information and notifying relevant personnel via a wireless network to take timely remedial measures. This mechanism not only effectively prevents potential health risks during the breeding process but also optimizes inspection routes and frequencies through intelligent path adjustment, ensuring priority coverage of health risk areas and thus improving the targeting and efficiency of inspections. Ultimately, it provides continuous and accurate health monitoring in a dynamically changing breeding environment, ensuring that the breeding environment and animal safety and health management are in optimal condition, significantly improving the level of refined management and operational efficiency of the farm.

[0109] Example 6

[0110] This embodiment is an explanation based on Embodiment 5. Please refer to it. Figure 1 Specifically: S5 includes S51 and S52;

[0111] S51. When the comprehensive health assessment triggers path planning, based on the three-dimensional drawings, a dynamic path optimization formula is constructed using a dynamic path planning algorithm. Then, the obtained comprehensive health index zhj is input into the dynamic path optimization model to obtain the dynamic path adjustment index ljt.

[0112] The dynamic path optimization formula is as follows;

[0113]

[0114] In the formula, The rate of change of the comprehensive health index zhj of the i-th region over time is represented by jl. i jl represents the distance between the i-th region and the next region. i nl represents the energy loss required to move from region i to the next region. maxrepresents the remaining energy of the inspection robot, n represents the total number of regions, and exp represents the exponential function with base e.

[0115] In S52, the inspection robot adjusts the path in the region part in the dangerous state according to the dynamic path adjustment index ljt, adjusts the inspection path of this region, and if multiple regions simultaneously have health problems, the robot re-evaluates and adjusts the paths of all related regions, and dynamically adjusts the path order and distance according to the real-time comprehensive health index zhj, and preferentially covers the regions in the dangerous state with high health risks.

[0116] After the relevant personnel governance, the inspection path of the inspection robot is adjusted again by the dynamic path adjustment index ljt according to the change trend of the comprehensive health index zhj obtained through multiple inspections, until the comprehensive health evaluation of the inspection task area of the inspection robot is good, the inspection path of the inspection robot is re-adjusted to the initial inspection path.

[0117] In this embodiment, the dynamic path optimization algorithm adjusts the inspection path in real time according to the change of the comprehensive health index zhj, ensuring that the inspection robot can preferentially cover regions with high health risks, especially regions in the dangerous state. This dynamic path adjustment mechanism can intelligently adjust the inspection order and path according to the health status of different regions, avoiding the fixed inspection mode commonly seen in traditional methods and improving the accuracy and pertinence of inspection. Secondly, when multiple regions simultaneously have health problems, the inspection robot re-evaluates the health status of all related regions and optimizes 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, ensuring that health problems are completely solved, and the inspection robot will re-adjust the inspection path to the initial inspection path when all regions return to a good health state. Through this series of dynamic adjustment, the system can continuously optimize the inspection path, provide efficient and fine health management, and ensure that the environment and animal health in the breeding house are optimally protected.

[0118] Embodiment 7

[0119] Please refer to Figure 2 A navigation system of 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 evaluation module, and a path adjustment module.

[0120] The initial patrol path planning module is used for dividing the large animal breeding house into a plurality of regions, launching a plurality of inspection robots, constructing a path optimization objective function by using a shortest path algorithm, initially planning an initial patrol path of the inspection robots, and performing non-repeated coverage of the regions by using a depth-first search algorithm.

[0121] The patrol collection module collects environmental data and animal data in real time by using a sensor group installed in the inspection robot and an intelligent ear tag equipped for each animal, and constructs a data processing system to preprocess the environmental data and the animal data and obtain a health data group.

[0122] The health analysis module is used for performing summary calculation on the obtained health data group, obtaining an environmental health state index hjz and an animal health state index djk.

[0123] The comprehensive health evaluation module is used for performing summary calculation on the obtained environmental health state index hjz and the animal health state index djk, obtaining a comprehensive health index zhj, and performing comprehensive health evaluation on the comprehensive health index zhj and a preset first comprehensive health threshold A and a second comprehensive health threshold B, and comprehensively analyzing the health state of the breeding environment and the animals.

[0124] The path adjustment module is used for constructing a dynamic path optimization model when the comprehensive health evaluation triggers path planning, inputting the obtained comprehensive health index zhj into the dynamic path optimization model, obtaining a dynamic path adjustment index ljt, and adjusting the patrol path of the inspection robot according to the dynamic path adjustment index ljt until the comprehensive health evaluation of the patrol task region of the inspection robot is all in a good state, and then the inspection robot re-adjusts the patrol path to the initial patrol path.

[0125] Although the embodiments of the present application have been shown and described, it can be understood by those skilled in the art that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and spirits of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for navigation of a robot for inspection in a farm, characterized in that: The method comprises the following steps: S1, dividing a large animal breeding house into several areas, putting several inspection robots, using the shortest path algorithm to construct the path optimization objective function, initially planning the initial inspection path of the inspection robot, and performing non-repeated coverage of the area through the depth-first search algorithm; S2, collecting environmental data and animal data in real time through the sensor group installed inside the inspection robot and the intelligent ear tag equipped with each animal, and constructing a data processing system to preprocess the environmental data and animal data to obtain a health data set; S3, performing summary calculation according to the obtained health data set to obtain an environmental health state index hjz and an animal health state index djk; S4, performing summary calculation according to the obtained environmental health state index hjz and animal health state index djk to obtain a comprehensive health index zhj, and performing comprehensive health evaluation with a preset first comprehensive health threshold A and a second comprehensive health threshold B to comprehensively analyze the health state of the breeding environment and the animals; S5, when the comprehensive health evaluation triggers path planning, constructing a dynamic path optimization model, inputting the obtained comprehensive health index zhj into the dynamic path optimization model to obtain a dynamic path adjustment index ljt, and adjusting the inspection path of the inspection robot according to the dynamic path adjustment index ljt until the comprehensive health evaluation of the inspection task area of the inspection robot is good, and the inspection robot re-adjusts the inspection path to the initial inspection path; The S1 comprises S11, S12 and S13; S11, according to the animal species and layout structure in the large animal breeding house, dividing the breeding house into several areas, putting several inspection robots, and setting a patrol task for each inspection robot, wherein the patrol task comprises patrolling multiple areas; S12, all the inspection paths in the breeding house are obtained according to the three-dimensional drawing of the breeding house, the distance between each area and other areas is obtained according to the inspection area of each inspection robot and the route in the inspection area, the shortest inspection path is planned by using the shortest path algorithm, combined with the charging pile position, the inspection task and the energy consumption, and the path optimization objective function is constructed, the initial inspection path of the inspection robot is preliminarily planned, and the path optimization objective function is specifically: Wherein, P represents the node order of the path, jl(i, i+1) represents the distance between area i and area i+1, nl(i, i+1) represents the energy consumption between area i and area i+1, and n represents the total number of areas. S13, in the inspection path planning process, performing non-repeated coverage of the area through the depth-first search algorithm, recording the area that has been planned by the robot, and avoiding returning to the area that has been inspected; The S2 comprises S21, S22 and S23; S21, after the inspection robot initially plans the initial inspection path, starting the inspection robot to patrol the task area, and collecting environmental data and animal data in real time through the sensor group installed inside the inspection robot and the intelligent ear tag equipped with each animal; The sensor group comprises a temperature sensor, a humidity sensor, a carbon dioxide sensor, an air flow sensor, an illumination intensity sensor and an infrared sensor; S22, constructing a data processing system, establishing a communication connection between the data processing system and the sensor group and the intelligent ear tag through a wireless network, and transmitting the environmental data and animal data collected by the sensor group and the intelligent ear tag to the data processing system in real time; S23, the data processing system receives the environmental data and animal data in real time, and preprocesses the environmental data and animal data, wherein the preprocessing comprises animal activity amount processing, denoising, missing value processing data correction and dimensionless processing, and a health data set is obtained; The animal activity amount processing is based on the intelligent ear tag equipped for each animal, the periodically collected animal positioning data, the monitoring of the activity track of the animal in the breeding house, the recording of the activity path and the stay time of the animal in the house, the calculation of the animal activity amount hd, and the collection of the animal body temperature dt based on the intelligent ear tag; The health data set includes an environmental health data set and an animal health data set; The environmental health data set includes an environmental temperature wd, an environmental humidity sd, a carbon dioxide content CO2, an air flow rate ls, and an illumination intensity gz; The animal health data set includes an animal body temperature dt, an animal activity amount hd, and an animal density dm; The S3 includes S31 and S32; S31, based on the acquired environmental health data set, an environmental health state index hjz is obtained by summary calculation, and the environmental health in each area in the breeding house is analyzed in real time; The environmental health state index hjz is obtained by calculation according to the following formula: wherein, wd i represents the actual temperature of the i-th zone, wd o represents the suitable temperature value for the animals inside the breeding house, sd i represents the actual humidity of the i-th zone, sd o represents the suitable humidity value for the animals inside the breeding house, CO 2，i represents the actual carbon dioxide content of the i-th zone, CO 2，o represents the peak value of the carbon dioxide content that the animals inside the breeding house are allowed to reach for their health, gz i represents the actual light intensity of the i-th zone, gz o represents the suitable light intensity for the animals inside the breeding house; S32, based on the acquired animal health data set, an animal health state index djk is obtained by summary calculation, and the health state of the animal in each area is monitored in real time; The animal health state index djk is obtained by calculation according to 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 represents the normal body temperature of the animal, hd j represents the activity level of the jth animal, dm i represents the density of animals in the ith region; The S4 includes S41 and S42; S41, based on the acquired environmental health state index hjz and animal health state index djk, a comprehensive health index zhj is obtained by summary calculation, which reflects the comprehensive influence of environmental health on the health of animals in the breeding house, and the nonlinear relationship between the two; The comprehensive health index zhj is obtained by calculation according to the following formula: In the formula, e represents an exponential function, and a represents an adjustment coefficient; 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 evaluation is performed on the acquired comprehensive health index zhj, the health state of the breeding environment and the animal is comprehensively analyzed, and according to the evaluation result, a patrol priority is set, and a patrol route and a patrol frequency are adjusted, and the specific evaluation scheme 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, a first warning information is generated and transmitted to the related personnel user end through a wireless network, the related personnel are reminded to take control measures immediately, and path planning is triggered to re-plan the patrol path; When the comprehensive health threshold A is less than or equal to the comprehensive health index zhj and is less than or equal to the second comprehensive health threshold B, the area exists unhealthy factors, a second warning information is generated and transmitted to the related personnel user end through a wireless network, the related personnel are reminded to take control measures immediately, and path planning is triggered to re-plan the patrol path; When the comprehensive health index zhj is greater than the second comprehensive health threshold B, the area state is good, and normal monitoring is maintained; The S5 includes S51 and S52; S51, when the comprehensive health evaluation triggers the path planning, a dynamic path optimization formula is constructed based on the three-dimensional drawing and using a dynamic path planning algorithm, the acquired comprehensive health index zhj is input into the dynamic path optimization model, and a dynamic path adjustment index ljt is obtained; The dynamic path optimization formula is as follows: In the formula, represents the rate of change of the comprehensive health index zhj of the i-th region with time, jl i represents the distance between the i-th region and the next region, jl i represents the energy loss required for 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 base e. S52, the inspection robot adjusts the path in the dangerous state area according to the dynamic path adjustment index ljt, adjusts the inspection path of the area, if multiple areas have health problems at the same time, the robot will re-evaluate and adjust the path of all related areas, and dynamically adjust the path order and distance according to the real-time comprehensive health index zhj, and preferentially cover the areas with health risks in the dangerous state; After the relevant personnel management, according to the change trend of the comprehensive health index zhj obtained by multiple inspections, the inspection path of the inspection robot is adjusted again through the dynamic path adjustment index ljt, until the comprehensive health evaluation of the inspection task area of the inspection robot is good, the inspection path of the inspection robot is adjusted to the initial inspection path.

2. A navigation system of a farming house inspection robot, comprising the navigation method of the farming house inspection robot according to claim 1, characterized in that: It comprises an initial inspection path planning module, an inspection collection module, a health analysis module, a comprehensive health evaluation module and a path adjustment module. The initial inspection path planning module is used to divide a large animal breeding house into several areas, put several inspection robots, use the shortest path algorithm to construct a path optimization objective function, preliminarily plan the initial inspection path of the inspection robot, and perform non-repeated coverage of the area through a depth-first search algorithm. The inspection collection module collects environmental data and animal data in real time through a sensor group installed in the inspection robot and an intelligent ear tag equipped with each animal, and constructs a data processing system to preprocess the environmental data and animal data to obtain a health data set. The health analysis module is used to aggregate and calculate the obtained health data set to obtain an environmental health state index hjz and an animal health state index djk. The comprehensive health evaluation module is used to aggregate and calculate the obtained environmental health state index hjz and animal health state index djk to obtain a comprehensive health index zhj, and perform comprehensive health evaluation with a preset first comprehensive health threshold A and a second comprehensive health threshold B, and comprehensively analyze the health status of the breeding environment and animals. The path adjustment module is used to construct a dynamic path optimization model when the comprehensive health evaluation triggers path planning, input the obtained comprehensive health index zhj into the dynamic path optimization model to obtain a dynamic path adjustment index ljt, and the inspection robot adjusts the inspection path according to the dynamic path adjustment index ljt, until the comprehensive health evaluation of the inspection task area of the inspection robot is good, the inspection path of the inspection robot is adjusted to the initial inspection path.

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