Sampling robot and control method thereof, and medium

Abstract

The present invention discloses a sampling robot, a control method thereof, and a medium. The method includes: determining multiple initial sampling points based on an acquired regional image of an area where an object to be sampled is located, and planning an initial sampling path based on the multiple initial sampling points; monitoring the environmental factors of each initial sampling point one by one while moving from the path starting point of the initial sampling path; determining whether to generate adjustment information for adjusting the currently monitored initial sampling point based on the environmental factors; if the adjustment information is generated, updating the initial sampling point and the initial sampling path based on the adjustment information, and sampling the object to be sampled based on the updated initial sampling point and initial sampling path. The present invention updates the initial sampling point and the initial sampling path in combination with the environmental factors, so that through the update, more samples that can more comprehensively reflect the quality of the object to be sampled are collected, so that the collected samples more comprehensively and accurately reflect the overall quality of the object to be sampled.

Description

Technical Field

[0001] The present invention relates to the field of robotics, and in particular to a sampling robot, a control method thereof, and a medium. Background Art

[0002] With the development of artificial intelligence (AI), mobile robots are playing an increasingly important role in industry, finding applications in manufacturing, electronics assembly, warehousing, and logistics. Sampling robots, a type of mobile robot, are specifically designed for sampling tasks. They can move around in various environments and autonomously collect samples for quality inspection.

[0003] Currently, sampling robots are typically controlled to follow a pre-set route, sampling a certain number of products or at set intervals. This fails to account for the impact of environmental variations on sample performance, resulting in the collected samples not fully and accurately reflecting the overall quality of the products. This is particularly true for products with stringent quality requirements, such as food, pharmaceuticals, feed, and chemicals. Failure to fully and accurately reflect product quality can have serious consequences.

[0004] Therefore, how to control the sampling of the sampling robot so that the collected samples can fully and accurately reflect the overall quality of the product is one of the technical problems that need to be solved urgently. Summary of the Invention

[0005] The main purpose of the present invention is to provide a sampling robot and its control method, and a medium, aiming to solve the technical problem of how to control the sampling of the sampling robot so that the collected samples fully and accurately reflect the overall quality of the product.

[0006] To achieve the above objectives, the present invention provides a control method for a sampling robot, wherein the sampling robot includes a control center, and a moving mechanism, a monitoring sensor, and an actuator that are communicatively connected to the control center. The control method for the sampling robot includes:

[0007] The control center obtains a regional image of the area where the items to be sampled are located, determines a plurality of initial sampling points based on the regional image, and plans an initial sampling path based on the plurality of initial sampling points;

[0008] The control center controls the moving mechanism to start moving from the path starting point of the initial sampling path, and during the movement, controls the monitoring sensor to monitor the environmental factors of each of the initial sampling points one by one;

[0009] The control center receives the environmental factors transmitted back by the monitoring sensor, and determines whether to generate adjustment information for adjusting the initial sampling point currently being monitored according to the environmental factors;

[0010] If the adjustment information is generated, the initial sampling point and the initial sampling path are updated according to the adjustment information, and the actuator is controlled to extend and retract to sample the object to be sampled according to the updated initial sampling point and the initial sampling path.

[0011] Preferably, the step of determining whether to generate adjustment information for adjusting the currently monitored initial sampling point according to the environmental factors includes:

[0012] Obtain the historical ambient temperature and historical ambient humidity in the historical environmental factors corresponding to the initial sampling point of the previous monitoring;

[0013] generating a temperature difference between the ambient temperature in the environmental factor and the historical ambient temperature, and a humidity difference between the ambient humidity in the environmental factor and the historical ambient humidity;

[0014] Determining whether the temperature difference is greater than a preset temperature threshold and whether the humidity difference is greater than a preset humidity threshold;

[0015] If the temperature difference is greater than a preset temperature threshold, and / or the humidity difference is greater than a preset humidity threshold, the adjustment information is generated.

[0016] Preferably, if the temperature difference is greater than a preset temperature threshold, and / or the humidity difference is greater than a preset humidity threshold, the step of generating the adjustment information includes:

[0017] generating a first magnitude relationship between the temperature difference and a preset temperature threshold, and / or generating a second magnitude relationship between the humidity difference and a preset humidity threshold;

[0018] Determining the number of newly added sampling points according to the first size relationship and / or the second size relationship;

[0019] Determining a new position corresponding to each of the newly added sampling points based on a sampling path between the last monitored initial sampling point and the currently monitored initial sampling point;

[0020] The newly added quantity and each of the newly added positions are generated as the adjustment information.

[0021] Preferably, the step of updating the initial sampling point and the initial sampling path according to the adjustment information includes:

[0022] Determine the multiple complete paths formed by connecting all newly added positions to the next initial sampling point with the sampling point position of the currently monitored initial sampling point as the starting point, and calculate the path distance of each complete path. The calculation formula is:

[0023]

[0024] Among them, S i represents the path distance of the i-th complete path, n represents the number of sampling point locations in the complete path, (x ki 、y ki ) represents the coordinate value of the kth sampling point in the i-th complete path in the image coordinate system, (x ki+1 、y ki+1 ) represents the coordinate value of the k+1th sampling point in the i-th complete path in the image coordinate system, n i represents the number of obstacles formed by the items to be sampled in the i-th complete path, D represents the increased straight-line distance corresponding to each obstacle, m i represents the number of obstacle turns in the i-th complete path, θ represents the obstacle turning angle, (e θ *cosθ) represents the distance parameter corresponding to the turning angle, and d represents the increasing turning distance corresponding to each turning angle;

[0025] The minimum value among the path distances is determined, and the initial sampling path and the initial sampling point are updated according to the complete path and the newly added position corresponding to the minimum value.

[0026] Preferably, the step of determining a plurality of initial sampling points according to the regional image comprises:

[0027] Identify whether the imaging of the object to be sampled in the area image is regular imaging, and if so, determine the sampling quantity of the object to be sampled according to the quantity of the object to be sampled and a preset sampling ratio;

[0028] Dividing the regional image into regional sub-images corresponding to the number of samples, determining target object images in the regional sub-images, and using the positions of the to-be-sampled objects corresponding to the target object images as the initial sampling points;

[0029] If the imaging of the object is irregular, the imaging of the object is clustered to generate multiple clusters. For each cluster, the sampling probability of each element in the cluster is calculated according to the position coordinates of each element in the cluster in the image coordinate system. The calculation formula is:

[0030]

[0031] Among them, p j represents the sampling probability of the jth element, x j Indicates the x-coordinate value of the position coordinate of the j-th element in the image coordinate system, y j Indicates the y coordinate value of the position coordinate of the jth element in the image coordinate system, xc Indicates the x-coordinate value of the cluster center in the image coordinate system, y c Indicates the y coordinate value of the cluster center in the image coordinate system, x τ Represents the average x-coordinate of the position coordinates of each element in the cluster in the image coordinate system, y τ Represents the average y-coordinate value of the position coordinates of each element in the cluster in the image coordinate system, v1 represents the center weight value of the cluster center, and v2 represents the average weight value of the mean coordinate corresponding to the position coordinates of each element in the image coordinate system;

[0032] The cluster sampling quantity of each cluster is determined according to the number of elements in the clusters and a preset sampling ratio, and the initial sampling point is determined according to the cluster sampling quantity and each sampling probability.

[0033] Preferably, the sampling robot further includes a communication module, and the step of controlling the actuator to extend and retract to sample the object to be sampled includes:

[0034] Transmitting the execution force data of the sampling performed by the actuator to a sampling management platform in communication with the sampling robot based on the communication module, and the sampling management platform evaluating whether the execution force data is data to be corrected based on the environmental factors;

[0035] If the control center receives feedback information indicating that the execution force data is data to be corrected, the control center controls the execution mechanism to resample the object to be sampled according to the correction reference data corresponding to the data to be corrected in the feedback information.

[0036] Preferably, the step of evaluating, by the sampling management platform based on the environmental factors, whether the execution strength data is data to be revised comprises:

[0037] The sampling management platform obtains reference force data corresponding to the object to be sampled, and calculates the force correction coefficient of the object to be sampled under the environmental factors according to the ambient temperature and ambient humidity in the environmental factors. The calculation formula is:

[0038]

[0039] Wherein, s represents the force correction coefficient, k1 represents the preset temperature weight, k2 represents the preset humidity weight, μ represents the density of the sampled object, c represents the specific heat capacity of the sampled object, w represents the temperature coefficient corresponding to the sampled object, t represents the ambient temperature, p0 represents the compressive strength of the sampled object under standard atmospheric pressure, hc represents the saturated humidity, p represents the average compressive strength of the sampled object, and h represents the ambient humidity;

[0040] Correcting the reference force data according to the force correction coefficient to generate corrected force data, and determining whether the execution force data matches the corrected force data; if so, determining that the execution force data is not data to be corrected;

[0041] If the execution force data does not match the correction force data, the execution force data is determined to be data to be corrected, and feedback information indicating that the execution force data is data to be corrected is generated according to the correction force data.

[0042] Preferably, the sampling robot further includes a cleaning component, and the step of controlling the actuator to extend and retract to sample the object to be sampled includes:

[0043] Controlling the actuator to extend and retract to a default position, and controlling the actuator to move to an area to be cleaned corresponding to the cleaning component;

[0044] The actuator is controlled to extend from the area to be cleaned into the cleaning chamber of the cleaning component, and the actuator is controlled to be cleaned in the cleaning chamber.

[0045] Furthermore, to achieve the above-mentioned object, the present invention also provides a sampling robot, comprising a control center, and a moving mechanism, a monitoring sensor, an actuator, a communication module, and a cleaning component that are communicatively connected to the control center;

[0046] The control center includes a memory, a processor, a communication bus, and a control program stored in the memory:

[0047] The communication bus is used to realize the connection and communication between the processor and the memory;

[0048] The processor is used to execute the control program to implement the steps of the control method of the sampling robot as described above.

[0049] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a medium, which is a readable storage medium. A control program is stored on the readable storage medium. When the control program is executed by a processor, the steps of the control method of the sampling robot as described above are implemented.

[0050] The present invention provides a sampling robot, a control method thereof, and a medium. The sampling robot includes a control center, a mobile mechanism, a monitoring sensor, and an actuator in communication with the control center. After obtaining a regional image of the area where the object to be sampled is located, the control center first determines multiple initial sampling points based on the regional image and plans an initial sampling path based on the multiple initial sampling points. The mobile mechanism is then controlled to move from the starting point of the initial sampling path. During the movement, the monitoring sensor is controlled to monitor the environmental factors of each initial sampling point one by one. The control center determines whether it is necessary to generate adjustment information for adjusting the currently monitored initial sampling point based on the environmental factors transmitted back by the monitoring sensor. If it is determined that there is a need to generate such adjustment information, the adjustment information is generated and the initial sampling point and the initial sampling path are updated based on the generated adjustment information. The actuator is then controlled to extend and retract to sample the object to be sampled based on the updated initial sampling point and initial sampling path. In this way, by setting monitoring sensors on the sampling robot, the monitoring sensors monitor the environmental factors of each initial sampling point one by one during the sampling robot's mobile sampling process. Once the monitored environmental factors reflect that the difference in environmental factors may cause changes in sample performance, adjustment information for adjusting the initial sampling point is generated. The initial sampling point and the initial sampling path are updated by the adjustment information. By updating, more samples that can more comprehensively reflect the quality of the items to be sampled are collected, so that the collected samples more comprehensively and accurately reflect the overall quality of the items to be sampled. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a flow chart of a first embodiment of a control method for a sampling robot according to the present invention;

[0052] Figure 2 This is a flow chart of a second embodiment of a control method for a sampling robot according to the present invention;

[0053] Figure 3 This is a flow chart of a third embodiment of a control method for a sampling robot according to the present invention;

[0054] Figure 4 This is a structural diagram of the hardware operating environment involved in an embodiment of the control center of the sampling robot of the present invention.

[0055] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0056] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0057] The present invention provides a control method for a sampling robot, please refer to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the control method of the sampling robot of the present invention.

[0058] The present invention provides an embodiment of a control method for a sampling robot. It should be noted that although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown. Specifically, the control method for the sampling robot in this embodiment includes:

[0059] In step S10, the control center obtains a regional image of the area where the items to be sampled are located, determines a plurality of initial sampling points according to the regional image, and plans an initial sampling path according to the plurality of initial sampling points.

[0060] This embodiment provides a control method for a sampling robot. The sampling robot includes a control center, a mobile mechanism, a monitoring sensor, and an actuator, which are communicatively connected to the control center. The mobile mechanism enables the movement of the sampling robot, the monitoring sensor is used to monitor environmental factors at the location of the mobile robot, including but not limited to ambient temperature and humidity, and the actuator is used to perform sampling.

[0061] When there is a need to sample an item, which can be any of food, medicine, feed, or chemicals, the item to be sampled is designated as the sampled item. The control center acquires an image of the area where the sampled item is located. This can be done by the user requesting the sample to upload the image, or by a sampling robot connected to a camera that captures the image and uploads it to the control center.

[0062] Furthermore, the control center identifies the regional image, identifies the imaging distribution of the items to be sampled in the regional image, and determines multiple sampling points based on the imaging distribution. The imaging distribution of the items to be sampled in the regional image may be a regular distribution, indicating that the images to be sampled are arranged neatly and regularly in the region where they are located, or it may be an irregular distribution, indicating that the images to be sampled are arranged irregularly in the region where they are located. Therefore, in order to ensure that the multiple sampling points determined can accurately and comprehensively reflect the quality of the items to be sampled, it is necessary to distinguish whether the sampling points are regularly distributed when determining the sampling points. Specifically, the step of determining multiple initial sampling points based on the regional image includes:

[0063] Step S11, identifying whether the imaging of the objects to be sampled in the area image is regular imaging, and if so, determining the number of objects to be sampled based on the number of objects to be sampled and a preset sampling ratio;

[0064] Step S12, dividing the regional image into regional sub-images corresponding to the number of samples, determining target object images in the regional sub-images, and using the positions of the to-be-sampled objects corresponding to the target object images as the initial sampling points;

[0065] Step S13: If the imaging of the object is irregular, clustering the imaging of the object to generate a plurality of clusters, and for each cluster, calculating the sampling probability of each element in the cluster according to the position coordinates of each element in the cluster in the image coordinate system;

[0066] Step S14 , determining the cluster sampling quantity of each cluster according to the number of elements in the cluster and a preset sampling ratio, and determining the initial sampling point according to the cluster sampling quantity and each sampling probability.

[0067] Furthermore, the control center identifies the regional image and determines whether the images of the items to be sampled within the regional image exhibit a regular pattern. Regular patterning refers to the regularity of the arrangement of the images of the items, such as intervals in length, width, and height. If regular patterning is determined, the number of items to be sampled is determined based on the number of items to be sampled and a preset sampling ratio. The number of items to be sampled can be uploaded in advance or obtained through image recognition, while the preset sampling ratio is set based on experience or needs. The number of items to be sampled is obtained by multiplying the two.

[0068] Furthermore, the regional image is divided according to the number of samples to be sampled, obtaining multiple regional sub-images containing sampling data. For each regional sub-image, the image of the item to be sampled within it is identified as the target item image. It should be noted that a regional sub-image may contain multiple item images of the item to be sampled. In this case, the image of the item located in the middle of the image images can be identified as the target item image. Alternatively, a regional sub-image may not contain a complete image of the item to be sampled. In this case, the image with the largest image area among the partial images can be identified as the target item image. After the target item image corresponding to each regional sub-image is determined, the item to be sampled corresponding to each target item image is searched, and then the location of each type of item to be sampled within the region is located. The found location is the initial sampling point.

[0069] Furthermore, if the imagery of the items to be sampled in the identified area is not regular, that is, the items to be sampled are not placed in the area according to a certain pattern, for example, a sub-area of ​​the area contains a large number of items to be sampled, while another sub-area contains a small number of items to be sampled. In this case, to ensure sampling uniformity, the item images are clustered to obtain multiple clusters. Through clustering of the item images, items to be sampled that are placed together are divided into the same cluster, while items to be sampled that are not placed together are divided into different clusters. Sampling is performed proportionally based on the number of items to be sampled contained in each cluster, so that the sampling is more uniform and better reflects the overall quality of the items to be sampled.

[0070] Furthermore, for clusters, the images of the objects contained therein form elements in the clusters, and the number of elements contained in each cluster is different. The specific element selected as the element corresponding to the sampled object can be determined by calculating the sampling probability of each element. Among them, the captured regional image has a corresponding image coordinate system, for example, a coordinate system formed by taking the point in the upper left corner of the regional image as the coordinate origin and the width and height directions of the regional image as the horizontal and vertical coordinates respectively. Each pixel in the regional image has its own coordinate value relative to the coordinate origin. For each element in the cluster, each is a contour area formed by the object imaging in the image coordinate system. The center coordinates of the contour area can be determined as the position coordinates of the element in the image coordinate system. Then, the sampling probability of each element is calculated based on the position coordinates. The calculation formula can be seen in the following formula (1).

[0071]

[0072] Among them, p j represents the sampling probability of the jth element, x j Indicates the x-coordinate value of the position coordinate of the j-th element in the image coordinate system, y j Indicates the y coordinate value of the position coordinate of the jth element in the image coordinate system, x c Indicates the x-coordinate value of the cluster center in the image coordinate system, y c Indicates the y coordinate value of the cluster center in the image coordinate system, x τ Represents the average x-coordinate of the position coordinates of each element in the cluster in the image coordinate system, y τrepresents the average y-coordinate value of the position coordinates of each element in the cluster in the image coordinate system, v1 represents the center weight of the cluster center, and v2 represents the average weight value of the mean coordinates corresponding to the position coordinates of each element in the image coordinate system. It should be noted that the cluster center is the center of the cluster generated by clustering; the x-coordinate average and y-coordinate average are generated by averaging the position coordinates of each element and represent the mean coordinates of each element. Specifically, the x-coordinate values ​​of each element's position coordinates in the image coordinate system are averaged to obtain the average x-coordinate value of each element's position coordinates in the image coordinate system; and the y-coordinate values ​​of each element's position coordinates in the image coordinate system are averaged to obtain the average y-coordinate value of each element's position coordinates in the image coordinate system. Furthermore, based on the degree of influence of the cluster center and mean coordinate on sampling during historical sampling, the center weight corresponding to the cluster center and the average weight value corresponding to the mean coordinate are pre-set. By combining the cluster center and mean coordinates, we avoid determining sampling elements based solely on their distance from the cluster center, or simply based on their distance from the mean coordinates. Instead, we ensure that the determined sampling elements are related to both the cluster center and the mean coordinates. Furthermore, by weighting the center weights and the mean weights, we make the determined sampling probability more accurate, which helps to accurately select sampling elements within each cluster.

[0073] Furthermore, the number of elements in each cluster is determined, including both complete and incomplete object images. Based on the number of elements and the preset sampling ratio, the two are multiplied to obtain the sampling data required for sampling in the cluster, i.e., the cluster sampling number. Thereafter, the sampling probabilities of each element in the cluster are arranged in descending order to form a probability sequence. Multiple target sampling probabilities arranged in the front are then screened from the probability sequence, and the data of the screened target sampling probabilities is the same as the sampling number. The target elements that generate each target sampling probability and the objects to be sampled corresponding to each target element are searched. The position of the object to be sampled in the area is the initial sampling point, thereby determining multiple initial sampling points based on the cluster sampling number and each sampling probability.

[0074] Furthermore, after determining multiple initial sampling points, each sampling point corresponds to the location of an object to be sampled within the area. From each initial sampling point, a boundary sampling point located at the boundary is determined. For each boundary sampling point, its surrounding adjacent sampling points are then determined. The boundary sampling point is connected to each adjacent sampling point to form a first-step sampling path. For each adjacent sampling point, its corresponding next-level adjacent sampling point is determined. This adjacent sampling point is connected to each next-level adjacent sampling point to form a second-step sampling path. This cycle continues until all initial sampling points have been determined as adjacent sampling points. By connecting each sampling path, multiple sampling paths corresponding to a particular boundary sampling point are obtained. Each sampling path is then compared to determine the shortest first sampling path. After determining the corresponding first sampling path for each boundary sampling point, the first sampling paths are compared to determine the shortest target sampling path. This target sampling path is the shortest path among all sampling paths, saving sampling time, and is therefore planned as the initial sampling path.

[0075] In step S20 , the control center controls the moving mechanism to start moving from the starting point of the initial sampling path, and controls the monitoring sensors to monitor the environmental factors of each initial sampling point one by one during the movement.

[0076] Furthermore, the control center issues movement instructions to the sampling robot's mobile mechanism, which controls the mobile mechanism to begin moving from the starting point of the initial sampling path. During the movement process, if the robot reaches an initial sampling point in the initial sampling path and sampling is required at that point, the control center issues a monitoring instruction to a monitoring sensor, which controls the monitoring sensor to monitor environmental factors at the initial sampling point. The environmental factors include at least ambient temperature and ambient humidity, reflecting the impact of temperature and humidity on the initial sampling point.

[0077] In step S30 , the control center receives the environmental factors transmitted back by the monitoring sensor, and determines whether to generate adjustment information for adjusting the initial sampling point currently being monitored based on the environmental factors.

[0078] Furthermore, the monitoring sensor acquires the environmental factors at the currently reached initial sampling point and returns them to the control center. Upon receiving this information, the control center determines whether the initial sampling point needs to be adjusted based on the magnitude of the change relative to the other initial sampling points. If adjustment is necessary, adjustment information is generated. Otherwise, sampling continues at the original initial sampling point without generating adjustment information.

[0079] Step S40: If the adjustment information is generated, the initial sampling point and the initial sampling path are updated according to the adjustment information, and the actuator is controlled to extend and retract to sample the object to be sampled according to the updated initial sampling point and the initial sampling path.

[0080] Furthermore, if the control center determines that adjustment information is necessary, the generated adjustment information includes an adjustment plan for the initial sampling points. Furthermore, the adjustment of the initial sampling points will affect the initial sampling path. For example, if an initial sampling point is added, the added initial sampling point needs to be added to the initial sampling path, while if an initial sampling point is reduced, the reduced initial sampling point needs to be deleted from the initial sampling path. The initial sampling points and initial sampling path are then updated based on the adjustment plan included in the adjustment information. After the update, the control center controls the actuator to sample the object to be sampled based on the updated initial sampling points and initial sampling path.

[0081] It is understandable that the sampling robot needs to sample multiple items to be sampled during the sampling process, and there may be contamination between the items to be sampled. Therefore, in order to avoid cross-contamination between the items to be sampled, a cleaning component can be set for the sampling robot. After the control center controls the actuator to sample the items to be sampled, the cleaning component cleans the actuator to avoid cross-interference between the items to be sampled. Specifically, the sampling robot also includes a cleaning component, and the step of controlling the actuator to retract and extend to sample the items to be sampled includes:

[0082] Step a1, controlling the actuator to extend to a default position, and controlling the actuator to move to an area to be cleaned corresponding to the cleaning component;

[0083] Step a2: controlling the actuator to extend from the area to be cleaned into the cleaning chamber of the cleaning component, and controlling the actuator to be cleaned in the cleaning chamber.

[0084] Furthermore, the actuator is configured as a telescopic mechanism, allowing it to extend further to grasp distant objects to be sampled. Simultaneously, the telescopic structure retracts to grasp nearby objects to be sampled. Furthermore, a default position is set for the actuator. After grasping an object to be sampled, the control center controls the actuator to extend to this default position. After returning to the default position, the actuator is controlled to move to the cleaning area corresponding to the cleaning component. The cleaning component can be a component with a cleaning chamber containing a cleaning medium. The medium used varies depending on the object to be sampled and can, for example, be ultrasonic waves, steam, or hot air. A cleaning inlet is provided above or in front of the cavity. This cleaning inlet serves as the cleaning area. Once the actuator has reached this cleaning area, the control center controls the actuator to extend into the cleaning chamber, where the medium is controlled to clean the actuator. This ensures the cleanliness of the actuator before grasping the next object to be sampled, preventing cross-contamination between objects to be sampled.

[0085] The control method of the sampling robot of this embodiment includes a control center, a mobile mechanism, a monitoring sensor, and an actuator in communication with the control center. After obtaining a regional image of the area where the object to be sampled is located, the control center first determines multiple initial sampling points based on the regional image and plans an initial sampling path based on the multiple initial sampling points. The mobile mechanism is then controlled to move from the starting point of the initial sampling path. During the movement, the monitoring sensor is controlled to monitor the environmental factors of each initial sampling point one by one. The control center determines whether it is necessary to generate adjustment information for adjusting the currently monitored initial sampling point based on the environmental factors returned by the monitoring sensor. If it is determined that such adjustment information is required, the adjustment information is generated and the initial sampling point and initial sampling path are updated based on the generated adjustment information. Then, based on the updated initial sampling point and initial sampling path, the actuator is controlled to extend and retract to sample the object to be sampled. In this way, by setting monitoring sensors on the sampling robot, the monitoring sensors monitor the environmental factors of each initial sampling point one by one during the sampling robot's mobile sampling process. Once the monitored environmental factors reflect that the difference in environmental factors may cause changes in sample performance, adjustment information for adjusting the initial sampling point is generated. The initial sampling point and the initial sampling path are updated by the adjustment information. By updating, more samples that can more comprehensively reflect the quality of the items to be sampled are collected, so that the collected samples more comprehensively and accurately reflect the overall quality of the items to be sampled.

[0086] For further information, please refer to Figure 2 Based on the first embodiment of the control method of the sampling robot of the present invention, a second embodiment of the control method of the sampling robot of the present invention is proposed.

[0087] The second embodiment of the control method for the sampling robot differs from the first embodiment of the control method for the sampling robot in that the step of determining whether to generate adjustment information for adjusting the currently monitored initial sampling point according to the environmental factors comprises:

[0088] Step S31, obtaining the historical environmental temperature and historical environmental humidity in the historical environmental factors corresponding to the initial sampling point of the previous monitoring;

[0089] Step S32, generating a temperature difference between the ambient temperature in the environmental factor and the historical ambient temperature, and a humidity difference between the ambient humidity in the environmental factor and the historical ambient humidity;

[0090] Step S33, determining whether the temperature difference is greater than a preset temperature threshold, and whether the humidity difference is greater than a preset humidity threshold;

[0091] Step S34: If the temperature difference is greater than a preset temperature threshold, and / or the humidity difference is greater than a preset humidity threshold, then the adjustment information is generated.

[0092] Furthermore, whether the current initial sampling point is adjusted depends on the magnitude of the change in its environmental factors compared to the environmental factors at the previous initial sampling point. A significant change indicates that the current initial sampling point is affected differently by environmental factors than the previous initial sampling point. To accurately reflect the performance and quality of the items being sampled at the current initial sampling point, the number of current initial sampling points needs to be increased. Therefore, after receiving the environmental factors collected and transmitted back by the monitoring sensors for the current initial sampling point, the control center uses the environmental factors collected for the previous monitored initial sampling point as historical environmental factors, obtaining the historical ambient temperature and historical ambient humidity contained therein. The difference between the ambient temperature in the environmental factors and the historical ambient temperature is then calculated to obtain the temperature difference. Simultaneously, the difference between the ambient humidity in the environmental factors and the historical ambient humidity is calculated to obtain the humidity difference.

[0093] Furthermore, to indicate the magnitude of the difference between the temperature difference and the humidity difference, corresponding preset temperature thresholds and preset humidity thresholds are pre-set based on historical sampling data. The temperature difference is compared with the preset temperature threshold to determine whether it is greater than the preset temperature threshold; and the humidity difference is compared with the preset humidity threshold to determine whether it is greater than the preset humidity threshold. If the temperature difference is greater than the preset temperature threshold, or the humidity difference is greater than the preset humidity threshold, or if both the temperature difference and the humidity difference are greater than the preset humidity threshold, then the environmental factors at the current initial sampling point have changed significantly relative to those at the previous initial sampling point, and these environmental factors may have a significant impact on the instruction performance of the items to be sampled at the current initial sampling point. At this point, in order to accurately reflect the performance quality of the items to be sampled around the current initial sampling point, the number of items to be sampled corresponding to the current initial sampling point needs to be increased, so the control center generates adjustment information. On the contrary, if the comparison determines that the temperature difference is not greater than the preset temperature threshold and the humidity difference is not greater than the preset temperature threshold, it means that the environmental factors of the current initial sampling point have not changed much compared with the environmental factors of the previous initial sampling point. The current initial sampling point does not need to be adjusted, and the actuator can be directly controlled to perform sampling.

[0094] It is understandable that the generated adjustment information includes at least the number and location of newly added initial sampling points, and whether the location of the current initial sampling point needs to be updated and adjusted. Therefore, if the temperature difference is greater than a preset temperature threshold, and / or the humidity difference is greater than a preset humidity threshold, the step of generating the adjustment information includes:

[0095] Step S341, generating a first magnitude relationship between the temperature difference and a preset temperature threshold, and / or generating a second magnitude relationship between the humidity difference and a preset humidity threshold;

[0096] Step S342: determining the number of newly added sampling points according to the first size relationship and / or the second size relationship;

[0097] Step S343, determining a newly added position corresponding to each newly added sampling point based on a sampling path between the last monitored initial sampling point and the currently monitored initial sampling point;

[0098] Step S344: Generate the newly added quantity and each newly added position as the adjustment information.

[0099] Furthermore, the number of newly added initial sampling points is related to the magnitude of the change in environmental factors between the current initial sampling point and the previous initial sampling point. The greater the magnitude of the change, the greater the number of newly added points. Therefore, a first magnitude relationship is generated between the temperature difference and a preset temperature threshold, and / or a second magnitude relationship is generated between the humidity difference and a preset humidity threshold. At the same time, corresponding relationships between temperature, humidity, and newly added numbers are pre-set, including a first magnitude relationship between temperature intervals and newly added numbers, a second magnitude relationship between humidity intervals and newly added numbers, and a third magnitude relationship between both temperature intervals and newly added numbers. If only one of the first magnitude relationship and the second magnitude relationship exists, the corresponding magnitude relationship is searched based on the type of the existing item. For example, if the first magnitude relationship is of the temperature type, the first magnitude relationship is searched to determine the temperature interval within which the first magnitude relationship exists, and then the corresponding magnitude of newly added points is searched. If both the first magnitude relationship and the second magnitude relationship exist, the corresponding temperature interval and humidity interval, as well as the corresponding magnitude of newly added points, are searched from the third magnitude relationship. The magnitude of newly added points determined by this search is the newly added number of newly added sampling points.

[0100] Furthermore, after determining the number of newly added sampling points, the location of each newly added sampling point must be determined. Specifically, the path between the previously monitored initial sampling point and the currently monitored initial sampling point is determined. This path represents the sampling robot's movement path between the two initial sampling points. Based on this path, the newly added location of each newly added sampling point is then determined. Specifically, a correspondence between position distance and newly added number can be established, centered around the currently monitored initial sampling point. For example, within a certain range of sampling points, each of the newly added sampling points is located on a circle with a certain distance as a radius, centered around the currently monitored initial sampling point. Each newly added sampling point can be evenly distributed along the circle, but a new sampling point must be located at the intersection of the path and the circle. This ensures uniform sampling while shortening the sampling path. For larger ranges of sampling points, two circles with different radii, centered around the currently monitored initial sampling point, can be established to achieve more uniform sampling and more accurately and comprehensively reflect the quality and performance of the sampled items.

[0101] Furthermore, after determining each newly added location, each newly added location and the newly added quantity can be generated as adjustment information, so that the control center can update the initial sampling points and the initial sampling path based on the newly added data and each newly added location in the adjustment information. Specifically, the step of updating the initial sampling points and the initial sampling path based on the adjustment information includes:

[0102] Step S41, determining multiple complete paths formed by connecting all newly added positions in series through different paths starting from the sampling point position of the currently monitored initial sampling point to the next initial sampling point, and calculating the path distance of each complete path;

[0103] Step S42 : determining the minimum value among the path distances, and updating the initial sampling path and the initial sampling point according to the complete path and the newly added position corresponding to the minimum value.

[0104] It is understandable that the sampling robot is at the position of the currently monitored initial sampling point. When the control center updates the initial sampling point and the initial sampling path based on the adjustment information, it needs to use the currently monitored initial sampling point as the basis. Specifically, the sampling point position of the currently monitored initial sampling point is used as the starting point to determine the first-level path between the starting point and each newly added position; then each newly added position is used as a new starting point, and the other newly added positions are connected one by one to obtain multiple second-level paths; for the last newly added position, it is connected to the next initial sampling point to form a third-level path. Finally, the first-level path, the second-level path, and the third-level path are used to realize the multiple complete paths formed by taking the sampling point position of the currently monitored initial sampling point as the starting point and connecting all the newly added positions through different paths to the next initial sampling point. For example, if the starting point is A and the newly added positions include B, C, and D, then the first-level paths are AB, AC, and AD. Afterwards, multiple second-level paths are formed, using B, C, and D as new starting points. For B, the second-level paths from B to C and then to D, as well as the second-level paths from B to D and then to C, are connected one by one. The third-level paths include those from D to the next initial sampling point and from C to the next initial sampling point. C and D are processed in the same manner as B. Finally, the three first-level paths, six second-level paths, and six third-level paths are connected in series to form multiple complete paths.

[0105] Furthermore, in order to determine the shortest path from a plurality of complete paths, a preset calculation formula is provided in advance, and the path distance of each complete path is calculated by the preset calculation formula. The preset calculation formula can be referred to as the following formula (2).

[0106]

[0107] Among them, S i represents the path distance of the i-th complete path, n represents the number of sampling point locations in the complete path, (x ki 、y ki ) represents the coordinate value of the kth sampling point in the i-th complete path in the image coordinate system, (x ki+1 、y ki+1) represents the coordinate value of the k+1th sampling point in the i-th complete path in the image coordinate system, n i represents the number of obstacles formed by the items to be sampled in the i-th complete path, D represents the increased straight-line distance corresponding to each obstacle, m i represents the number of obstacle turns in the i-th complete path, θ represents the obstacle turning angle, (e θ *cosθ) represents the distance parameter corresponding to the corner angle, and d represents the incremental corner distance associated with each corner turn. The sampling point locations in a complete path include the sampling point location of the initial sampling point, each newly added location, and the sampling point location where the next initial sampling point is located. The total number of sampling point locations is the sum of the number of such locations. Each such location has a corresponding pixel coordinate value in the image coordinate system. The straight-line distance between two adjacent sampling point locations is calculated based on their respective coordinate values ​​in the image coordinate system. This straight-line distance forms the shortest path between the two adjacent sampling points. However, this path may contain objects to be sampled that are not sampling points, requiring the sampling robot to circumvent them. These objects constitute obstacles. The sampling robot's circumvention of such obstacles involves two methods: passing in a straight line and circumventing corners around them. However, not every obstacle requires a corner, such as passing two obstacles side by side before turning a corner. Therefore, the number of obstacles and the number of corners are not consistent. Therefore, we count the number of obstacles formed by the sampled items in the i-th complete path, as well as the number of turns formed by each sampled obstacle. We then use the pre-set distance added by a straight line passing through an obstacle and the distance added by a turn to correct the calculated shortest distance, making the final calculated path distance more accurate.

[0108] After calculating each complete distance to obtain its own path distance, the path distances are compared to determine the minimum. The complete path corresponding to this minimum value is the path that minimizes the robot's travel time. Therefore, the complete path corresponding to the minimum value is found. Based on the positions of the first and last sampling points in this complete path within the original initial sampling path, this complete path is added to the initial sampling path, thereby updating the initial sampling path. After the initial sampling path is updated, the newly added sampling points in it represent the updated initial sampling points.

[0109] In this embodiment, when the environmental factors of the currently monitored initial sampling point change significantly compared to the historical environmental factors of the previous initial sampling point, adjustment information for adjusting the initial sampling point is generated. The initial sampling points and the initial sampling path are then updated based on the number and positions of the newly added sampling points in the adjustment information. This ensures that the collected samples better reflect the impact of the environment and more accurately and comprehensively reflect the quality of the items while having an optimal sampling path, the sampling robot's movement path is the shortest, and sampling efficiency is high.

[0110] For further information, please refer to Figure 3 Based on the first and second embodiments of the control method of the sampling robot of the present invention, a third embodiment of the control method of the sampling robot of the present invention is proposed.

[0111] The third embodiment of the control method of the sampling robot differs from the first and second embodiments of the control method of the sampling robot in that the sampling robot further includes a communication module, and after the step of controlling the actuator to extend and retract to sample the object to be sampled, the method further includes:

[0112] Step S50, transmitting the execution force data of the sampling performed by the actuator to a sampling management platform in communication with the sampling robot based on the communication module, and the sampling management platform evaluating whether the execution force data is data to be corrected based on the environmental factors;

[0113] Understandably, the sampling robot's actuator exerts a certain gripping force when grasping an object to be sampled. Different types of objects require different gripping forces. Even for the same type of object, the gripping force it can withstand varies depending on the environment and location. For example, an object in a humid location can withstand a lower gripping force. Therefore, to mitigate the impact of the actuator's gripping force on the object to be sampled, this embodiment incorporates a mechanism for feedback and correction of gripping force data after the actuator has sampled the object.

[0114] Specifically, in order to conduct a unified and accurate analysis of the grabbing force data, a sampling management platform is provided. The sampling management platform can connect to multiple sampling robots. Each sampling robot is provided with a communication module, which is communicated with the sampling management platform through the communication module. In the process of the sampling robot controlling the extension and retraction of its actuator to sample the sampled items, the actuator records the force data used for this sampling grabbing operation as execution force data. After the sampling operation is completed, the execution force data is transmitted to the sampling management platform through the communication module. The sampling management platform evaluates the execution force data based on environmental factors to determine whether the sampling force represented by the execution force data is too large or too small, and whether correction is required. That is, evaluate whether the execution force data is data to be corrected. Specifically, the step of evaluating whether the execution force data is data to be corrected based on the environmental factors by the sampling management platform includes:

[0115] Step S51, the sampling management platform obtains reference force data corresponding to the object to be sampled, and calculates a force correction coefficient of the object to be sampled under the environmental factors according to the ambient temperature and ambient humidity in the environmental factors;

[0116] Step S52, correcting the reference force data according to the force correction coefficient to generate corrected force data, and determining whether the execution force data matches the corrected force data; if so, determining that the execution force data is not data to be corrected;

[0117] Step S53 : If the execution force data does not match the correction force data, the execution force data is determined to be data to be corrected, and feedback information indicating that the execution force data is data to be corrected is generated according to the correction force data.

[0118] Furthermore, reference force data corresponding to each type of sampled item is pre-set. The reference force data is the minimum force required to grasp the sampled item. For the currently sampled sampled item, the sampling management platform searches for the reference force data corresponding to the sampled item. At the same time, the influence of environmental factors on the grasping force of the sampled item is considered. The force correction coefficient of the sampled item under these environmental factors is calculated using the ambient temperature and humidity. The calculation formula for calculating the force correction coefficient can be found in the following formula (3).

[0119]

[0120] Where s represents the force correction coefficient, k1 represents the preset temperature weight, k2 represents the preset humidity weight, μ represents the density of the sampled item, c represents the specific heat capacity of the sampled item, w represents the temperature coefficient corresponding to the sampled item, t represents the ambient temperature, p0 represents the compressive strength of the sampled item at standard atmospheric pressure, hc represents the saturated humidity, p represents the average compressive strength of the sampled item, and h represents the ambient humidity. By combining the ambient temperature and humidity of the environment in which the sampled item is located, the force correction coefficient is calculated to reflect the change in grasping force caused by the environmental influences on the sampled item.

[0121] Furthermore, the force correction coefficient obtained by calculation is used to correct the reference force data of the sampled item to generate corrected force data. The corrected force data reflects the minimum gripping force of the sampled item that changes due to environmental factors. The execution force data of the actuator gripping the sampled item is then compared with the corrected force data to determine whether the execution force data and the corrected force data match. The matching can be determined by setting a data interval. That is, it is determined whether the difference between the execution force data and the corrected force data is within the data interval. If it is within the data interval, it means that the difference between the execution force data and the corrected force data is small, and the two are determined to match. On the contrary, if the difference between the two exceeds the data interval, it means that the difference between the execution force data and the corrected force data is large, and the two are determined to be mismatched.

[0122] Furthermore, if it is determined that the execution force data matches the corrected force data, it indicates that the force used by the actuator to grasp the object to be sampled is appropriate and will not affect the quality and performance of the object to be sampled. There is no need to correct the force used by the actuator to grasp the object to be sampled, and therefore the execution force data is determined not to be data to be corrected. In any case, if it is determined that the execution force data does not match the corrected force data, it indicates that the force used by the actuator to grasp the object to be sampled is inappropriate and may affect the quality and performance of the object to be sampled. Therefore, it is necessary to correct the force used by the actuator to grasp the object to be sampled, and in this case, the execution force data is determined to be data to be corrected. Feedback information indicating that the execution force data is data to be corrected is then generated based on the corrected force data, and this generated feedback information is transmitted to the sampling robot, so that the sampling robot can control the actuator's grasping force to adjust to the corrected force data based on this feedback information, and grasp the object to be sampled with a more appropriate grasping force.

[0123] Step S60: If the control center receives feedback information indicating that the execution force data is data to be corrected, the execution mechanism is controlled to resample the object to be sampled according to correction reference data corresponding to the data to be corrected in the feedback information.

[0124] Furthermore, upon receiving feedback indicating that the execution force data corresponds to the data to be corrected, the control center reads the corrected force data from the feedback information as correction reference data corresponding to the data to be corrected. The control center then controls the actuator based on the corrected reference data, causing the actuator to resample the sampled item using the corrected reference data. The resampled item is located adjacent to the location of the item previously sampled by the actuator. By selecting adjacent items for resampling using the corrected reference data, the performance of the sampled item is prevented from being affected by inappropriate sampling force, while also preventing performance differences between items at different locations. This ensures that the original performance of the sampled item is not affected by the actuator's sampling force.

[0125] This embodiment obtains the execution force data of the execution mechanism for sampling, and evaluates whether it needs to be corrected in combination with the influence of environmental factors, so that the corrected execution force can grab the sampled items but will not affect the performance quality of the sampled items, thereby ensuring the originality of the sampled items and facilitating the accurate reflection of the overall performance quality of the items through the collected samples.

[0126] In addition, an embodiment of the present invention further provides a sampling robot. The sampling robot includes a control center, a mobile mechanism connected to the control center for communication, a monitoring sensor, an actuator, a communication module, and a cleaning component. Figure 4 , Figure 4 This is a structural diagram of the equipment hardware operating environment involved in the control center embodiment of the sampling robot of the present invention.

[0127] like Figure 4 As shown, the control center of the sampling robot may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 may be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0128] Those skilled in the art will understand that Figure 4The hardware structure of the control center of the sampling robot shown in the figure does not constitute a limitation of the control center of the sampling robot, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0129] like Figure 4 As shown, the memory 1005 as a medium may include an operating system, a network communication module, a user interface module, and a control program. The operating system is a program that manages and controls the control center and software resources of the sampling robot, and supports the operation of the network communication module, the user interface module, the control program, and other programs or software. The network communication module is used to manage and control the network interface 1004; the user interface module is used to manage and control the user interface 1003.

[0130] exist Figure 4 In the hardware structure of the control center of the sampling robot shown, the network interface 1004 is mainly used to connect to the system server and communicate data with the system server; the user interface 1003 is mainly used to connect to the client (user end) and communicate data with the client; the processor 1001 can call the control program stored in the memory 1005 and perform the following operations:

[0131] The control center obtains a regional image of the area where the items to be sampled are located, determines a plurality of initial sampling points based on the regional image, and plans an initial sampling path based on the plurality of initial sampling points;

[0132] The control center controls the moving mechanism to start moving from the path starting point of the initial sampling path, and during the movement, controls the monitoring sensor to monitor the environmental factors of each of the initial sampling points one by one;

[0133] The control center receives the environmental factors transmitted back by the monitoring sensor, and determines whether to generate adjustment information for adjusting the initial sampling point currently being monitored according to the environmental factors;

[0134] If the adjustment information is generated, the initial sampling point and the initial sampling path are updated according to the adjustment information, and the actuator is controlled to extend and retract to sample the object to be sampled according to the updated initial sampling point and the initial sampling path.

[0135] Furthermore, the step of determining whether to generate adjustment information for adjusting the currently monitored initial sampling point according to the environmental factors includes:

[0136] Obtain the historical ambient temperature and historical ambient humidity in the historical environmental factors corresponding to the initial sampling point of the previous monitoring;

[0137] generating a temperature difference between the ambient temperature in the environmental factor and the historical ambient temperature, and a humidity difference between the ambient humidity in the environmental factor and the historical ambient humidity;

[0138] Determining whether the temperature difference is greater than a preset temperature threshold and whether the humidity difference is greater than a preset humidity threshold;

[0139] If the temperature difference is greater than a preset temperature threshold, and / or the humidity difference is greater than a preset humidity threshold, the adjustment information is generated.

[0140] Furthermore, if the temperature difference is greater than a preset temperature threshold, and / or the humidity difference is greater than a preset humidity threshold, the step of generating the adjustment information includes:

[0141] generating a first magnitude relationship between the temperature difference and a preset temperature threshold, and / or generating a second magnitude relationship between the humidity difference and a preset humidity threshold;

[0142] Determining the number of newly added sampling points according to the first size relationship and / or the second size relationship;

[0143] Determining a new position corresponding to each of the newly added sampling points based on a sampling path between the last monitored initial sampling point and the currently monitored initial sampling point;

[0144] The newly added quantity and each of the newly added positions are generated as the adjustment information.

[0145] Furthermore, the step of updating the initial sampling point and the initial sampling path according to the adjustment information includes:

[0146] Determine the multiple complete paths formed by connecting all newly added positions to the next initial sampling point with the sampling point position of the currently monitored initial sampling point as the starting point, and calculate the path distance of each complete path. The calculation formula is:

[0147]

[0148] Among them, S i represents the path distance of the i-th complete path, n represents the number of sampling point locations in the complete path, (x ki 、y ki ) represents the coordinate value of the kth sampling point in the i-th complete path in the image coordinate system, (x ki+1 、y ki+1 ) represents the coordinate value of the k+1th sampling point in the i-th complete path in the image coordinate system, n irepresents the number of obstacles formed by the items to be sampled in the i-th complete path, D represents the increased straight-line distance corresponding to each obstacle, m i represents the number of obstacle turns in the i-th complete path, θ represents the obstacle turning angle, (e θ *cosθ) represents the distance parameter corresponding to the turning angle, and d represents the increasing turning distance corresponding to each turning angle;

[0149] The minimum value among the path distances is determined, and the initial sampling path and the initial sampling point are updated according to the complete path and the newly added position corresponding to the minimum value.

[0150] Furthermore, the step of determining a plurality of initial sampling points according to the regional image includes:

[0151] Identify whether the imaging of the object to be sampled in the area image is regular imaging, and if so, determine the sampling quantity of the object to be sampled according to the quantity of the object to be sampled and a preset sampling ratio;

[0152] Dividing the regional image into regional sub-images corresponding to the number of samples, determining target object images in the regional sub-images, and using the positions of the to-be-sampled objects corresponding to the target object images as the initial sampling points;

[0153] If the imaging of the object is irregular, the imaging of the object is clustered to generate multiple clusters. For each cluster, the sampling probability of each element in the cluster is calculated according to the position coordinates of each element in the cluster in the image coordinate system. The calculation formula is:

[0154]

[0155] Among them, p j represents the sampling probability of the jth element, x j Indicates the x-coordinate value of the position coordinate of the j-th element in the image coordinate system, y j Indicates the y coordinate value of the position coordinate of the jth element in the image coordinate system, x c Indicates the x-coordinate value of the cluster center in the image coordinate system, y c Indicates the y coordinate value of the cluster center in the image coordinate system, x τ Represents the average x-coordinate of the position coordinates of each element in the cluster in the image coordinate system, y τ Represents the average y-coordinate value of the position coordinates of each element in the cluster in the image coordinate system, v1 represents the center weight value of the cluster center, and v2 represents the average weight value of the mean coordinate corresponding to the position coordinates of each element in the image coordinate system;

[0156] The number of cluster samples of each cluster is determined according to the number of elements in the clusters and a preset sampling ratio, and the initial sampling point is determined according to the number of cluster samples and each sampling probability.

[0157] Furthermore, the sampling robot further includes a communication module. After the step of controlling the actuator to extend and retract to sample the object to be sampled, the processor 1001 may call the control program stored in the memory 1005 and perform the following operations:

[0158] Transmitting the execution force data of the sampling performed by the actuator to a sampling management platform in communication with the sampling robot based on the communication module, and the sampling management platform evaluating whether the execution force data is data to be corrected based on the environmental factors;

[0159] If the control center receives feedback information indicating that the execution force data is data to be corrected, the control center controls the execution mechanism to resample the object to be sampled according to the correction reference data corresponding to the data to be corrected in the feedback information.

[0160] Furthermore, the step of evaluating, by the sampling management platform based on the environmental factors, whether the execution strength data is data to be corrected includes:

[0161] The sampling management platform obtains reference force data corresponding to the object to be sampled, and calculates the force correction coefficient of the object to be sampled under the environmental factors according to the ambient temperature and ambient humidity in the environmental factors. The calculation formula is:

[0162]

[0163] Wherein, s represents the force correction coefficient, k1 represents the preset temperature weight, k2 represents the preset humidity weight, μ represents the density of the sampled object, c represents the specific heat capacity of the sampled object, w represents the temperature coefficient corresponding to the sampled object, t represents the ambient temperature, p0 represents the compressive strength of the sampled object under standard atmospheric pressure, hc represents the saturated humidity, p represents the average compressive strength of the sampled object, and h represents the ambient humidity;

[0164] Correcting the reference force data according to the force correction coefficient to generate corrected force data, and determining whether the execution force data matches the corrected force data; if so, determining that the execution force data is not data to be corrected;

[0165] If the execution force data does not match the correction force data, the execution force data is determined to be data to be corrected, and feedback information indicating that the execution force data is data to be corrected is generated according to the correction force data.

[0166] Furthermore, the sampling robot further includes a cleaning component. After the step of controlling the actuator to extend and retract to sample the object to be sampled, the processor 1001 may call the control program stored in the memory 1005 and perform the following operations:

[0167] Controlling the actuator to extend and retract to a default position, and controlling the actuator to move to an area to be cleaned corresponding to the cleaning component;

[0168] The actuator is controlled to extend from the area to be cleaned into the cleaning chamber of the cleaning component, and the actuator is controlled to be cleaned in the cleaning chamber.

[0169] The specific implementation of the control center of the sampling robot of the present invention is basically the same as the various embodiments of the control method of the sampling robot described above, and will not be repeated here.

[0170] An embodiment of the present invention further provides a medium, which is a readable storage medium having a control program stored thereon, and which, when executed by a processor, implements the steps of the control method for the sampling robot described above.

[0171] The storage medium of the present invention may be a computer-readable storage medium, and its implementation is substantially the same as that of the above-mentioned control method of the sampling robot, and will not be described in detail here.

[0172] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims. Any equivalent structure or equivalent process transformation made using the contents of the description and drawings of the present invention, or directly or indirectly used in other related technical fields, all fall within the protection of the present invention.

Claims

1. A control method for a sampling robot, characterized in that: The sampling robot includes a control center, and a moving mechanism, a monitoring sensor, and an actuator that are communicatively connected to the control center. The control method of the sampling robot includes: The control center obtains a regional image of the area where the items to be sampled are located, determines a plurality of initial sampling points based on the regional image, and plans an initial sampling path based on the plurality of initial sampling points; The control center controls the moving mechanism to start moving from the path starting point of the initial sampling path, and during the movement, controls the monitoring sensor to monitor the environmental factors of each of the initial sampling points one by one; The control center receives the environmental factors transmitted back by the monitoring sensor, and determines whether to generate adjustment information for adjusting the initial sampling point currently being monitored according to the environmental factors; If the adjustment information is generated, the initial sampling point and the initial sampling path are updated according to the adjustment information, and the actuator is controlled to extend and retract to sample the object to be sampled according to the updated initial sampling point and the initial sampling path; The step of determining whether to generate adjustment information for adjusting the currently monitored initial sampling point according to the environmental factors includes: Obtain the historical ambient temperature and historical ambient humidity in the historical environmental factors corresponding to the initial sampling point of the previous monitoring; generating a temperature difference between the ambient temperature in the environmental factor and the historical ambient temperature, and a humidity difference between the ambient humidity in the environmental factor and the historical ambient humidity; Determining whether the temperature difference is greater than a preset temperature threshold and whether the humidity difference is greater than a preset humidity threshold; If the temperature difference is greater than a preset temperature threshold, and / or the humidity difference is greater than a preset humidity threshold, generating the adjustment information; If the temperature difference is greater than a preset temperature threshold, and / or the humidity difference is greater than a preset humidity threshold, the step of generating the adjustment information includes: generating a first magnitude relationship between the temperature difference and a preset temperature threshold, and / or generating a second magnitude relationship between the humidity difference and a preset humidity threshold; Determining the number of newly added sampling points according to the first size relationship and / or the second size relationship; Determining a new position corresponding to each of the newly added sampling points based on a sampling path between the last monitored initial sampling point and the currently monitored initial sampling point; generating the newly added quantity and each newly added position as the adjustment information; The step of updating the initial sampling point and the initial sampling path according to the adjustment information includes: Determine the multiple complete paths formed by connecting all newly added positions to the next initial sampling point with the sampling point position of the currently monitored initial sampling point as the starting point, and calculate the path distance of each complete path. The calculation formula is: ； in, represents the path distance of the i-th complete path, n represents the number of sampling point locations in the complete path, Represents the coordinate value of the kth sampling point in the i-th complete path in the image coordinate system, Indicates the coordinate value of the k+1th sampling point in the i-th complete path in the image coordinate system, represents the number of obstacles formed by the items to be sampled in the i-th complete path, D represents the increased straight-line distance corresponding to each obstacle, represents the number of obstacle corners in the i-th complete path, Indicates the obstacle turning angle, It represents the distance parameter corresponding to the turning angle, and d represents the increasing turning distance corresponding to each turning angle; The minimum value among the path distances is determined, and the initial sampling path and the initial sampling point are updated according to the complete path and the newly added position corresponding to the minimum value.

2. The control method of the sampling robot according to claim 1, characterized in that: The step of determining a plurality of initial sampling points according to the regional image comprises: Identify whether the imaging of the object to be sampled in the area image is regular imaging, and if so, determine the sampling quantity of the object to be sampled according to the quantity of the object to be sampled and a preset sampling ratio; Dividing the regional image into regional sub-images corresponding to the number of samples, determining target object images in the regional sub-images, and using the positions of the to-be-sampled objects corresponding to the target object images as the initial sampling points; If the imaging of the object is irregular, the imaging of the object is clustered to generate multiple clusters. For each cluster, the sampling probability of each element in the cluster is calculated according to the position coordinates of each element in the cluster in the image coordinate system. The calculation formula is: in, represents the sampling probability of the jth element, Indicates the x-coordinate value of the position coordinate of the j-th element in the image coordinate system, Indicates the y-coordinate value of the position coordinate of the j-th element in the image coordinate system, Indicates the x-coordinate value of the cluster center in the image coordinate system, Indicates the y-coordinate value of the cluster center in the image coordinate system, Represents the average x-coordinate of the position coordinates of each element in the cluster in the image coordinate system, Represents the average y-coordinate of the position coordinates of each element in the cluster in the image coordinate system, represents the center weight value of the cluster center, Represents the average weight value of the mean coordinate corresponding to the position coordinate of each element in the image coordinate system; The cluster sampling quantity of each cluster is determined according to the number of elements in the clusters and a preset sampling ratio, and the initial sampling point is determined according to the cluster sampling quantity and each sampling probability.

3. The control method of the sampling robot according to any one of claims 1 to 2, characterized in that: The sampling robot further includes a communication module, and after the step of controlling the actuator to extend and retract to sample the object to be sampled, the following steps are performed: Transmitting the execution force data of the sampling performed by the actuator to a sampling management platform in communication with the sampling robot based on the communication module, and the sampling management platform evaluating whether the execution force data is data to be corrected based on the environmental factors; If the control center receives feedback information indicating that the execution force data is data to be corrected, the control center controls the execution mechanism to resample the object to be sampled according to the correction reference data corresponding to the data to be corrected in the feedback information.

4. The control method of the sampling robot according to claim 3, characterized in that: The step of evaluating, by the sampling management platform based on the environmental factors, whether the execution strength data is data to be revised comprises: The sampling management platform obtains reference force data corresponding to the object to be sampled, and calculates the force correction coefficient of the object to be sampled under the environmental factors according to the ambient temperature and ambient humidity in the environmental factors. The calculation formula is: Where s represents the force correction coefficient, k1 represents the preset temperature weight, and k2 represents the preset humidity weight. represents the density of the items to be sampled, represents the specific heat capacity of the sampled item, w represents the temperature coefficient corresponding to the sampled item, t represents the ambient temperature, represents the compressive strength of the object to be sampled under standard atmospheric pressure, hc represents the saturated humidity, p represents the average compressive strength of the object to be sampled, and h represents the ambient humidity; the reference force data is corrected according to the force correction coefficient to generate corrected force data, and it is determined whether the execution force data matches the corrected force data; if so, it is determined that the execution force data is not data to be corrected; If the execution force data does not match the correction force data, the execution force data is determined to be data to be corrected, and feedback information indicating that the execution force data is data to be corrected is generated according to the correction force data.

5. The control method of the sampling robot according to any one of claims 1 to 2, characterized in that: The sampling robot further includes a cleaning component, and after the step of controlling the actuator to extend and retract to sample the object to be sampled, the following steps are performed: Controlling the actuator to extend and retract to a default position, and controlling the actuator to move to an area to be cleaned corresponding to the cleaning component; The actuator is controlled to extend from the area to be cleaned into the cleaning chamber of the cleaning component, and the actuator is controlled to be cleaned in the cleaning chamber.

6. A sampling robot, characterized in that: The sampling robot includes a control center, and a moving mechanism, a monitoring sensor, an actuator, a communication module and a cleaning component that are communicatively connected to the control center; The control center includes a memory, a processor, a communication bus, and a control program stored in the memory: The communication bus is used to realize the connection and communication between the processor and the memory; The processor is configured to execute the control program to implement the steps of the control method for the sampling robot according to any one of claims 1 to 5.

7. A medium, characterized in that The medium is a readable storage medium having a control program stored thereon. When the control program is executed by a processor, the steps of the control method for the sampling robot according to any one of claims 1 to 5 are implemented.

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