Intelligent robot control method applied to hospital scene and intelligent robot

Abstract

The invention relates to the technical field of ship management and control, and discloses an intelligent robot control method applied to a hospital scene and an intelligent robot, and the method comprises the steps: judging whether the intelligent robot meets a next link driving condition or not according to a determined current expected process link and progress and a current actual process link and progress of a target file; if yes, according to the first current position information of the target file, the second current position information of the intelligent robot and the position information of the next link, a driving path scheme of the intelligent robot for transporting the target file is determined; and controlling the intelligent robot to execute corresponding file transportation operation on the target file according to the driving path scheme. Therefore, the control accuracy, reliability, efficiency and convenience of the intelligent robot can be improved, the file transportation accuracy and efficiency of the intelligent robot are improved, unnecessary file transportation blocking conditions are reduced, and the file transportation adjustment timeliness, accuracy and efficiency of the intelligent robot are improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent robot control technology, and in particular to an intelligent robot control method and an intelligent robot applied in a hospital scenario. Background Art

[0002] In the modern medical system, document transportation is an indispensable part of the daily operation of the hospital. Medical documents, reports, specimens and receipts need to be frequently transferred between departments to ensure the smooth progress of the medical process. However, in practical applications, the existing document transportation methods often rely on staff to manually deliver documents; or, staff set a fixed route for the intelligent robot in advance, and then the intelligent robot transports documents according to the fixed route. However, when there are people or objects blocking the intelligent robot's driving route, the intelligent robot cannot continue to drive and transport documents, and the accuracy and efficiency of the intelligent robot's document transportation are low. Therefore, it is particularly important to provide an intelligent robot control method that improves the accuracy and efficiency of the intelligent robot's document transportation. Summary of the invention

[0003] The present invention provides an intelligent robot control method and an intelligent robot applied in hospital scenarios, which can improve the control accuracy and control efficiency of the intelligent robot applied in hospital scenarios, thereby improving the accuracy and efficiency of file transportation of the intelligent robot.

[0004] In order to solve the above technical problems, the first aspect of the present invention discloses a control method of an intelligent robot applied to a hospital scene, wherein the intelligent robot is used to access various information approval systems of the hospital, and the method comprises:

[0005] Determine the current expected process link and progress of the target file according to the process query information for the target file input by the user, and determine the current actual process link and progress of the target file;

[0006] According to the current expected process link and progress, and the current actual process link and progress, determining whether the intelligent robot meets the preset next link driving conditions;

[0007] When it is determined that the intelligent robot meets the driving conditions of the next link, a driving path plan for the intelligent robot to transport the target file is determined according to the determined first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link;

[0008] According to the driving path plan, controlling the intelligent robot to perform corresponding file transportation operations on the target file;

[0009] The process query information of the target file includes one or more of the number of the target file, the applicant, keywords, other information that can determine the target file as a query object, and other information that can determine the required query content about the target file to be queried;

[0010] Among them, the process links corresponding to the current expected process links and progress, and the current actual process links and progress all include one or more of the application approval link, the information submission link, the document stamping link and other document processing links.

[0011] As an optional implementation, in the first aspect of the present invention, determining a driving path plan for the intelligent robot to transport the target file based on the determined first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link includes:

[0012] Determine a basic driving path plan of the intelligent robot according to the determined first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link;

[0013] Determine relevant device information corresponding to the device placed in the hospital scene where the intelligent robot is located, and perform a corresponding first path optimization operation on the basic driving path plan according to the relevant device information to obtain a first optimized driving path plan;

[0014] Determine relevant personnel information corresponding to relevant personnel in the hospital scene, and perform a corresponding second path optimization operation on the first optimized driving path plan according to the relevant personnel information to obtain a second optimized driving path plan;

[0015] According to the second optimized driving path plan, a driving path plan for the intelligent robot to transport the target file is determined.

[0016] As an optional implementation, in the first aspect of the present invention, performing a corresponding first path optimization operation on the basic driving path plan according to the relevant device information to obtain a first optimized driving path plan includes:

[0017] Determine, according to the basic driving path plan, a first driving area corresponding to the intelligent robot, and determine, according to the relevant equipment information, equipment placement information and equipment movement configuration information of regional equipment in the first driving area;

[0018] According to the device placement information and the device movement configuration information, determining whether the intelligent robot meets the preset smooth driving conditions;

[0019] When it is determined that the intelligent robot meets the smooth driving condition, the basic driving path plan is determined as the first optimized driving path plan;

[0020] When it is determined that the intelligent robot does not meet the smooth driving conditions, the target blocking equipment that blocks the smooth driving of the intelligent robot is determined according to the regional channel space information of the first driving area, the equipment placement information and the driving requirement space information of the intelligent robot; a blocking response plan for the target blocking equipment is generated according to the equipment movement configuration information and the equipment placement information; and according to the blocking response plan, a corresponding route update operation is performed on the basic driving path plan to obtain a first optimized driving path plan.

[0021] As an optional implementation, in the first aspect of the present invention, performing a corresponding second path optimization operation on the first optimized driving path plan according to the relevant personnel information to obtain a second optimized driving path plan includes:

[0022] Determine, according to the first optimized driving path plan, a second driving area corresponding to the intelligent robot, and determine, according to the relevant personnel information, the real-time personnel location and distribution information of the regional personnel in the second driving area, and the personnel responsible event information;

[0023] According to the real-time personnel location and distribution information, the personnel in the area are divided into one or more personnel distribution groups, and the density of each of the personnel distribution groups is determined;

[0024] According to the event information of the personnel in charge, determine the responsibility of the personnel in each area and the nature of the event operation, and analyze the degree of need for maintaining the position of the personnel in each area according to the responsibility of the personnel in each area and the nature of the event operation;

[0025] Determine the required position change mode of each personnel in the area according to the personnel responsible event information;

[0026] Determine the predicted avoidance efficiency of each of the distributed groups of personnel with respect to the intelligent robot according to the density of each of the distributed groups of personnel, the degree of position maintenance requirements of the personnel in each of the distributed groups of personnel, and the position change requirements;

[0027] Determine the emergency priority of the personnel responsible event and the target file transportation event according to the personnel responsible event information, the determined file nature of the target file and the content of the communication event;

[0028] According to the density of each of the personnel distribution groups, the predicted avoidance efficiency, and the emergency priority situation, a corresponding second path optimization operation is performed on the first optimized driving path plan to obtain a second optimized driving path plan.

[0029] As an optional implementation, in the first aspect of the present invention, the corresponding second path optimization operation is performed on the first optimized driving path plan according to the density of each of the personnel distribution groups and the predicted avoidance efficiency and the emergency priority situation to obtain the second optimized driving path plan, including:

[0030] According to the density of each of the personnel distribution groups, the predicted avoidance efficiency, and the emergency priority, all of the personnel distribution groups are divided into a first personnel group that meets the preset robot active avoidance conditions and / or a second personnel group that meets the preset robot no-avoidance conditions;

[0031] When all the personnel distribution groups include the first personnel group, determining the target driving section area where the intelligent robot needs to change its route according to the first personnel group; generating a first optimal detour plan for the intelligent robot for the target driving section area according to the target driving section area and the real-time personnel position and distribution information; performing corresponding route update operations on the first optimized driving path plan according to the first optimal detour plan to obtain a second optimized driving path plan;

[0032] When all the population distribution groups do not include the first population group, the first optimized driving route plan is determined as the second optimized driving route plan.

[0033] As an optional implementation manner, in the first aspect of the present invention, generating a blocking response plan for the target blocking device according to the device movement configuration information and the device placement information includes:

[0034] Determining the device movement property and device movement requirement of the target blocking device according to the device movement configuration information;

[0035] According to the equipment movement properties and equipment movement execution requirements of the target blocking equipment, and the determined transportation travel priority characteristics corresponding to the intelligent robot and / or the target file, the target blocking equipment is divided into a first blocking equipment that meets a preset execution avoidance condition and / or a second blocking equipment that meets a preset non-execution avoidance condition;

[0036] When the target blocking device includes the second blocking device, generating a second optimal detour route for the intelligent robot for the second blocking device according to the current placement position of the second blocking device;

[0037] When the target blocking device includes the first blocking device, generating an optimal avoidance plan of the first blocking device for the intelligent robot according to the current placement position of the first blocking device and the first driving area;

[0038] A blocking response plan for the target blocking device is determined according to the second optimal detour route and / or the optimal avoidance plan.

[0039] As an optional implementation, in the first aspect of the present invention, after controlling the intelligent robot to perform a corresponding file transportation operation on the target file according to the driving path plan, the method further includes:

[0040] Collecting current position path information of the intelligent robot;

[0041] Determine the position path deviation of the intelligent robot according to the current position path information and the driving path plan, and determine the current environmental complexity of the hospital scene according to the determined relevant equipment information and relevant personnel information of the hospital scene where the intelligent robot is located;

[0042] According to the position path deviation and the current environmental complexity, determining whether the intelligent robot meets the preset driving abnormality condition;

[0043] When it is determined that the intelligent robot meets the abnormal driving condition, a path deviation warning instruction corresponding to the intelligent robot is generated, and / or a corresponding driving path update operation is performed on the intelligent robot.

[0044] As an optional implementation, in the first aspect of the present invention, judging whether the intelligent robot meets the preset abnormal driving condition according to the position path deviation and the current environmental complexity includes:

[0045] Determine the rationality of the deviation of the intelligent robot according to the position path deviation, the relevant equipment information and the relevant personnel information;

[0046] According to the complexity of the current environment, determining a reasonableness threshold of the deviation of the intelligent robot for the hospital scene;

[0047] Determine whether the deviation rationality is greater than or equal to a preset deviation rationality threshold;

[0048] When it is determined that the deviation rationality is greater than or equal to the deviation rationality threshold, it is determined that the intelligent robot does not meet the preset abnormal driving condition;

[0049] When it is determined that the deviation rationality is less than the deviation rationality threshold, it is determined that the intelligent robot meets the preset abnormal driving condition.

[0050] As an optional implementation, in the first aspect of the present invention, judging whether the intelligent robot meets the preset smooth driving conditions according to the device placement information and the device movement configuration information includes:

[0051] According to the regional channel space information of the first driving area and the driving requirement space information of the intelligent robot, it is determined whether the first driving area meets the preset basic space feasibility conditions;

[0052] When it is determined that the first driving area meets the basic space feasibility condition, judging whether the first driving area meets a preset no-equipment-blocking condition according to the equipment placement information;

[0053] When it is determined that the first driving-related area meets the no-equipment-blocking condition, determining that the intelligent robot meets a preset smooth driving condition;

[0054] When it is determined that the first driving area does not meet the no-equipment-blocking condition, judging whether the first driving area meets a preset no-equipment-blocking condition according to the regional channel space information, the driving demand space information and the equipment placement information;

[0055] When it is determined that the first driving-related area meets the condition that the device is not blocked, determining that the intelligent robot meets the preset smooth driving condition;

[0056] When it is determined that the first driving-related area does not satisfy the equipment unblocked condition, it is determined that the intelligent robot does not satisfy the preset smooth driving condition.

[0057] The second aspect of the present invention discloses an intelligent robot, which includes a main body and a corresponding control device. The intelligent robot is used to access various information approval systems of a hospital. The control device includes:

[0058] The link and progress determination module is used to determine the current expected process link and progress of the target file according to the process query information for the target file input by the user, and determine the current actual process link and progress of the target file;

[0059] A judgment module, used to judge whether the intelligent robot meets the preset next link driving conditions according to the current expected process link and progress and the current actual process link and progress;

[0060] A path plan determination module is used to determine the driving path plan of the intelligent robot to transport the target file according to the first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link when the judgment module determines that the intelligent robot meets the driving conditions of the next link;

[0061] A file transport execution module, used to control the intelligent robot to perform corresponding file transport operations on the target file according to the driving path plan;

[0062] The process query information of the target file includes one or more of the number of the target file, the applicant, keywords, other information that can determine the target file as a query object, and other information that can determine the required query content about the target file to be queried;

[0063] Among them, the process links corresponding to the current expected process links and progress, and the current actual process links and progress all include one or more of the application approval link, the information submission link, the document stamping link and other document processing links.

[0064] As an optional implementation, in the second aspect of the present invention, the path plan determination module determines the driving path plan of the intelligent robot transporting the target file according to the determined first current position information of the target file, the second current position information of the intelligent robot, and the next link position information, specifically including:

[0065] Determine a basic driving path plan of the intelligent robot according to the determined first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link;

[0066] Determine relevant device information corresponding to the device placed in the hospital scene where the intelligent robot is located, and perform a corresponding first path optimization operation on the basic driving path plan according to the relevant device information to obtain a first optimized driving path plan;

[0067] Determine relevant personnel information corresponding to relevant personnel in the hospital scene, and perform a corresponding second path optimization operation on the first optimized driving path plan according to the relevant personnel information to obtain a second optimized driving path plan;

[0068] According to the second optimized driving path plan, a driving path plan for the intelligent robot to transport the target file is determined.

[0069] As an optional implementation, in the second aspect of the present invention, the path plan determination module performs a corresponding first path optimization operation on the basic driving path plan according to the relevant device information, and the manner in which the first optimized driving path plan is obtained specifically includes:

[0070] Determine, according to the basic driving path plan, a first driving area corresponding to the intelligent robot, and determine, according to the relevant equipment information, equipment placement information and equipment movement configuration information of regional equipment in the first driving area;

[0071] According to the device placement information and the device movement configuration information, determining whether the intelligent robot meets the preset smooth driving conditions;

[0072] When it is determined that the intelligent robot meets the smooth driving condition, the basic driving path plan is determined as the first optimized driving path plan;

[0073] When it is determined that the intelligent robot does not meet the smooth driving conditions, the target blocking equipment that blocks the smooth driving of the intelligent robot is determined according to the regional channel space information of the first driving area, the equipment placement information and the driving requirement space information of the intelligent robot; a blocking response plan for the target blocking equipment is generated according to the equipment movement configuration information and the equipment placement information; and according to the blocking response plan, a corresponding route update operation is performed on the basic driving path plan to obtain a first optimized driving path plan.

[0074] As an optional implementation, in the second aspect of the present invention, the path plan determination module performs a corresponding second path optimization operation on the first optimized driving path plan according to the relevant personnel information, and the manner in which the second optimized driving path plan is obtained specifically includes:

[0075] Determine, according to the first optimized driving path plan, a second driving area corresponding to the intelligent robot, and determine, according to the relevant personnel information, the real-time personnel location and distribution information of the regional personnel in the second driving area, and the personnel responsible event information;

[0076] According to the real-time personnel location and distribution information, the personnel in the area are divided into one or more personnel distribution groups, and the density of each of the personnel distribution groups is determined;

[0077] According to the event information of the personnel in charge, determine the responsibility of the personnel in each area and the nature of the event operation, and analyze the degree of need for maintaining the position of the personnel in each area according to the responsibility of the personnel in each area and the nature of the event operation;

[0078] Determine the required position change mode of each personnel in the area according to the personnel responsible event information;

[0079] Determine the predicted avoidance efficiency of each of the distributed groups of personnel with respect to the intelligent robot according to the density of each of the distributed groups of personnel, the degree of position maintenance requirements of the personnel in each of the distributed groups of personnel, and the position change requirements;

[0080] Determine the emergency priority of the personnel responsible event and the target file transportation event according to the personnel responsible event information, the determined file nature of the target file and the content of the communication event;

[0081] According to the density of each of the personnel distribution groups, the predicted avoidance efficiency, and the emergency priority situation, a corresponding second path optimization operation is performed on the first optimized driving path plan to obtain a second optimized driving path plan.

[0082] As an optional implementation, in the second aspect of the present invention, the path plan determination module performs a corresponding second path optimization operation on the first optimized driving path plan according to the density of each of the personnel distribution groups and the predicted avoidance efficiency and the emergency priority situation, and the manner in which the second optimized driving path plan is obtained specifically includes:

[0083] According to the density of each of the personnel distribution groups, the predicted avoidance efficiency, and the emergency priority, all of the personnel distribution groups are divided into a first personnel group that meets the preset robot active avoidance conditions and / or a second personnel group that meets the preset robot no-avoidance conditions;

[0084] When all the personnel distribution groups include the first personnel group, determining the target driving section area where the intelligent robot needs to change its route according to the first personnel group; generating a first optimal detour plan for the intelligent robot for the target driving section area according to the target driving section area and the real-time personnel position and distribution information; performing corresponding route update operations on the first optimized driving path plan according to the first optimal detour plan to obtain a second optimized driving path plan;

[0085] When all the population distribution groups do not include the first population group, the first optimized driving route plan is determined as the second optimized driving route plan.

[0086] As an optional implementation, in the second aspect of the present invention, the path plan determination module generates a blocking response plan for the target blocking device according to the device movement configuration information and the device placement information, specifically including:

[0087] Determining the device movement property and device movement requirement of the target blocking device according to the device movement configuration information;

[0088] According to the equipment movement properties and equipment movement execution requirements of the target blocking equipment, and the determined transportation travel priority characteristics corresponding to the intelligent robot and / or the target file, the target blocking equipment is divided into a first blocking equipment that meets a preset execution avoidance condition and / or a second blocking equipment that meets a preset non-execution avoidance condition;

[0089] When the target blocking device includes the second blocking device, generating a second optimal detour route for the intelligent robot for the second blocking device according to the current placement position of the second blocking device;

[0090] When the target blocking device includes the first blocking device, generating an optimal avoidance plan of the first blocking device for the intelligent robot according to the current placement position of the first blocking device and the first driving area;

[0091] A blocking response plan for the target blocking device is determined according to the second optimal detour route and / or the optimal avoidance plan.

[0092] As an optional implementation, in the second aspect of the present invention, the control device further includes:

[0093] The driving abnormality control module is used to collect the current position path information of the intelligent robot after the file transportation execution module controls the intelligent robot to perform the corresponding file transportation operation on the target file according to the driving path plan; determine the position path deviation of the intelligent robot according to the current position path information and the driving path plan, and determine the current environmental complexity of the hospital scene according to the relevant equipment information and relevant personnel information of the hospital scene where the intelligent robot is located; determine whether the intelligent robot meets the preset driving abnormality condition according to the position path deviation and the current environmental complexity; when it is determined that the intelligent robot meets the driving abnormality condition, generate a path deviation warning instruction corresponding to the intelligent robot, and / or perform a corresponding driving path update operation on the intelligent robot.

[0094] As an optional implementation, in the second aspect of the present invention, the driving abnormality control module determines whether the intelligent robot meets the preset driving abnormality condition according to the position path deviation and the current environmental complexity, specifically including:

[0095] Determine the rationality of the deviation of the intelligent robot according to the position path deviation, the relevant equipment information and the relevant personnel information;

[0096] According to the complexity of the current environment, determining a reasonableness threshold of the deviation of the intelligent robot for the hospital scene;

[0097] Determine whether the deviation rationality is greater than or equal to a preset deviation rationality threshold;

[0098] When it is determined that the deviation rationality is greater than or equal to the deviation rationality threshold, it is determined that the intelligent robot does not meet the preset abnormal driving condition;

[0099] When it is determined that the deviation rationality is less than the deviation rationality threshold, it is determined that the intelligent robot meets the preset abnormal driving condition.

[0100] As an optional implementation, in the second aspect of the present invention, the path plan determination module determines whether the intelligent robot meets the preset smooth driving conditions according to the device placement information and the device movement configuration information, specifically including:

[0101] According to the regional channel space information of the first driving area and the driving requirement space information of the intelligent robot, it is determined whether the first driving area meets the preset basic space feasibility conditions;

[0102] When it is determined that the first driving area meets the basic space feasibility condition, judging whether the first driving area meets a preset no-equipment-blocking condition according to the equipment placement information;

[0103] When it is determined that the first driving-related area meets the no-equipment-blocking condition, determining that the intelligent robot meets a preset smooth driving condition;

[0104] When it is determined that the first driving area does not meet the no-equipment-blocking condition, judging whether the first driving area meets a preset no-equipment-blocking condition according to the regional channel space information, the driving demand space information and the equipment placement information;

[0105] When it is determined that the first driving-related area meets the condition that the device is not blocked, determining that the intelligent robot meets the preset smooth driving condition;

[0106] When it is determined that the first driving-related area does not satisfy the equipment unblocked condition, it is determined that the intelligent robot does not satisfy the preset smooth driving condition.

[0107] The third aspect of the present invention discloses another intelligent robot, the intelligent robot comprises a body and a corresponding control device, the control device comprises:

[0108] A memory storing executable program code;

[0109] a processor coupled to the memory;

[0110] The processor calls the executable program code stored in the memory to execute the intelligent robot control method applied to the hospital scene disclosed in the first aspect of the present invention.

[0111] The fourth aspect of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute the intelligent robot control method for hospital scenarios disclosed in the first aspect of the present invention.

[0112] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0113] In an embodiment of the present invention, based on the process query information for the target file input by the user, the current expected process link and progress of the target file are determined, and the current actual process link and progress of the target file are collected; based on the current expected process link and progress and the current actual process link and progress, it is judged whether the intelligent robot meets the preset next link driving conditions; when it is judged that the intelligent robot meets the next link driving conditions, based on the determined first current position information of the target file, the second current position information of the intelligent robot, and the next link position information, a driving path plan for the intelligent robot to transport the target file is determined; based on the driving path plan, the intelligent robot is controlled to perform corresponding file transportation operations on the target file. It can be seen that the present invention can determine the driving path plan for the intelligent robot to transport the target file according to the determined relevant information when it is judged that the intelligent robot meets the driving conditions of the next link, and then control the intelligent robot to perform the corresponding file transportation operation on the target file, which is beneficial to improving the comprehensiveness, integrity and rationality of the intelligent robot control method applied to the hospital scene, and is beneficial to improving the rationality of the driving path plan determination method of the intelligent robot, and is beneficial to improving the diversity, pertinence and rationality of the determination parameters used to determine the driving path plan of the intelligent robot, and is beneficial to improving the accuracy and reliability of the determined driving path plan, so as to improve the control accuracy and reliability of the intelligent robot, and is beneficial to improving the control efficiency and convenience of the intelligent robot, further improving the accuracy and efficiency of the file transportation of the intelligent robot, reducing unnecessary file transportation being blocked, and improving the timeliness, accuracy and efficiency of the file transportation adjustment of the intelligent robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0114] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0115] Figure 1 It is a flow chart of an intelligent robot control method applied to a hospital scenario disclosed in an embodiment of the present invention;

[0116] Figure 2 It is a flow chart of another intelligent robot control method applied to a hospital scenario disclosed in an embodiment of the present invention;

[0117] Figure 3 It is a structural schematic diagram of a control device of an intelligent robot disclosed in an embodiment of the present invention;

[0118] Figure 4 It is a structural schematic diagram of another intelligent robot control device disclosed in an embodiment of the present invention;

[0119] Figure 5 It is a structural schematic diagram of another intelligent robot disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0120] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0121] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or end including a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units inherent to these processes, methods, products or ends.

[0122] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0123] The present invention discloses an intelligent robot control method and an intelligent robot applied to hospital scenes. When it is judged that the intelligent robot meets the driving conditions of the next link, the intelligent robot can determine the driving path plan for transporting the target file according to the determined relevant information, and then control the intelligent robot to perform the corresponding file transportation operation on the target file, which is conducive to improving the comprehensiveness, integrity and rationality of the intelligent robot control method applied to the hospital scene, and is conducive to improving the rationality of the intelligent robot's driving path plan determination method, and is conducive to improving the diversity, pertinence and rationality of the determination parameters used to determine the intelligent robot's driving path plan, and is conducive to improving the accuracy and reliability of the determined driving path plan, thereby helping to improve the control accuracy and reliability of the intelligent robot, and is conducive to improving the control efficiency and convenience of the intelligent robot, further improving the accuracy and efficiency of the intelligent robot's file transportation, reducing unnecessary file transportation being blocked, and improving the timeliness, accuracy and efficiency of the intelligent robot's file transportation adjustment. The following are detailed descriptions.

[0124] Embodiment 1

[0125] See also Figure 1 , Figure 1 : is a flow chart of an intelligent robot control method applied to a hospital scenario disclosed in an embodiment of the present invention. Figure 1 The described method can be applied to an intelligent robot in a hospital scenario, wherein the intelligent robot includes a main body and a corresponding control device, wherein the intelligent robot can be used to access various information approval systems of the hospital, wherein the control device may include a server, wherein the server includes a local server or a cloud server, and the embodiments of the present invention are not limited thereto. Figure 1 As shown, the intelligent robot control method applied to hospital scenarios includes the following operations:

[0126] 101. According to the process query information for the target file input by the user, determine the current expected process link and progress of the target file, and determine the current actual process link and progress of the target file.

[0127] Optionally, the process query information for the target file may include, but is not limited to, one or more of the target file number, applicant, keywords, other information that can determine the target file as a query object, other information that can determine the required query content about the target file, etc., and the embodiment of the present invention is not limited thereto.

[0128] Optionally, the process links and progress of the target file, for example: the process links of the target file can be application approval links, document submission links, document stamping links and other document processing links; when the process environment is the approval link, its progress can be pending approval progress, approval progress, approval completion progress and other forms of progress, etc., which are not limited in the embodiments of the present invention.

[0129] Optionally, the current expected process links and progress of the target file can be understood as the process links and progress that the target file should reach or is preset to reach at the current stage; and the actual process links and progress of the target file can be understood as the process links and progress that the target file actually reaches at the current stage, which is not limited in the embodiments of the present invention.

[0130] 102. Based on the current expected process links and progress, and the current actual process links and progress, determine whether the intelligent robot meets the preset driving conditions for the next link.

[0131] Further optionally, when it is determined that the intelligent robot does not meet the preset driving conditions for the next link, the above step 101 is executed again, or the corresponding process links and progress abnormality check response operations are executed on the target file, which is not limited by the embodiment of the present invention.

[0132] Further optionally, judging whether the intelligent robot meets the preset next link driving condition according to the current expected process link and progress and the current actual process link and progress may include:

[0133] Determine whether the current expected process link and progress match the current actual process link and progress; when the judgment result is yes, determine that the intelligent robot meets the preset next link driving conditions; when the judgment result is no, determine that the intelligent robot does not meet the preset next link driving conditions; or,

[0134] Based on the current expected process links and progress, the current actual process links and progress, determine whether the target file meets the preset conditions for completion of the current link; when the judgment result is yes, determine that the intelligent robot meets the preset driving conditions for the next link; when the judgment result is no, determine that the intelligent robot does not meet the preset driving conditions for the next link.

[0135] 103. When it is determined that the intelligent robot meets the driving conditions of the next link, a driving path plan for the intelligent robot to transport the target file is determined based on the first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link.

[0136] Optionally, the next link position information can be the target robot position where the intelligent robot transports the target file to the next process link, or the target file position where the target file enters the next process link; further, for example: the intelligent robot can directly transport the target file to address A, and the target file directly starts the next process link at address A; or the target file needs to reach address B to start the next process link, but the intelligent robot can only transport the target file to address C based on address B, and the target file goes to address B by other means based on address C to proceed to the next process link, and the embodiments of the present invention are not limited to this.

[0137] 104. According to the driving path plan, control the intelligent robot to perform corresponding file transportation operations on the target file.

[0138] Optionally, the above-mentioned control of the intelligent robot to perform corresponding file transportation operations on the target file can be used to realize the file transportation of application approval, submission of materials, document stamping, etc. between clinical department personnel and functional departments, thereby realizing integrated progress query, file transfer and processing, and reducing the running around of medical staff, which is not limited to the embodiments of the present invention.

[0139] It can be seen that the intelligent robot control method applied to the hospital scene described in the embodiment of the present invention can determine the driving path plan for the intelligent robot to transport the target file according to the determined relevant information when it is judged that the intelligent robot meets the driving conditions of the next link, and then control the intelligent robot to perform the corresponding file transportation operation on the target file, which is conducive to improving the comprehensiveness, integrity and rationality of the intelligent robot control method applied to the hospital scene, and is conducive to improving the rationality of the driving path plan determination method of the intelligent robot, and is conducive to improving the diversity, pertinence and rationality of the determination parameters used to determine the driving path plan of the intelligent robot, and is conducive to improving the accuracy and reliability of the determined driving path plan, thereby helping to improve the control accuracy and reliability of the intelligent robot, and is conducive to improving the control efficiency and convenience of the intelligent robot, further improving the accuracy and efficiency of the file transportation of the intelligent robot, reducing unnecessary file transportation blocking, and improving the timeliness, accuracy and efficiency of the file transportation adjustment of the intelligent robot.

[0140] In an optional embodiment, the above-mentioned determination of the driving path plan for the intelligent robot to transport the target file based on the determined first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link may include:

[0141] Determine a basic driving path plan of the intelligent robot according to the determined first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link;

[0142] Determine relevant device information corresponding to the devices placed in the hospital scene where the intelligent robot is located, and perform a corresponding first path optimization operation on the basic driving path plan according to the relevant device information to obtain a first optimized driving path plan;

[0143] Determine relevant personnel information corresponding to relevant personnel in the hospital scene, and perform a corresponding second path optimization operation on the first optimized driving path plan according to the relevant personnel information to obtain a second optimized driving path plan;

[0144] According to the second optimized driving path plan, a driving path plan for the intelligent robot to transport the target file is determined.

[0145] Further optionally, the above-mentioned determining the basic driving path plan of the intelligent robot according to the determined first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link may include:

[0146] Determine a first path plan according to the determined first current position information of the target file and the second current position information of the intelligent robot, and determine a second path plan according to the first current position information and the position information of the next link;

[0147] According to the first path plan and the second path plan, a basic driving path plan of the intelligent robot is determined.

[0148] Optionally, the relevant device information corresponding to the device may include, but is not limited to, one or more of device placement information, device mobile configuration information, and other device related information, and is not limited in the embodiment of the present invention.

[0149] Optionally, the relevant personnel information corresponding to the relevant personnel may include, but is not limited to, one or more of real-time personnel location and distribution information, personnel responsible event information, other personnel related information, etc., and is not limited in the embodiment of the present invention.

[0150] Optionally, the first path optimization operation may be understood as path optimization considerations from a device level, and the second path optimization operation may be understood as path optimization considerations from a personnel level, which is not limited in the embodiment of the present invention.

[0151] It can be seen that this optional embodiment can determine the basic driving path plan of the intelligent robot, and further perform corresponding path optimization operations on the intelligent robot from the equipment level and personnel level in the hospital scene to obtain the driving path plan of the intelligent robot, which is conducive to improving the comprehensiveness, integrity and rationality of the method of determining the driving path plan of the intelligent robot, and is conducive to improving the diversity, flexibility and pertinence of the considerations in determining the driving path plan of the intelligent robot, and thus is conducive to improving the accuracy and reliability of the determined driving path plan, thereby helping to improve the accuracy and efficiency of file transportation of the intelligent robot based on the determined driving path plan.

[0152] In another optional embodiment, performing the corresponding first path optimization operation on the basic driving path plan according to the relevant device information to obtain the first optimized driving path plan may include:

[0153] Determine the first driving area corresponding to the intelligent robot according to the basic driving path plan, and determine the equipment placement information and equipment movement configuration information of the regional equipment in the first driving area according to the relevant equipment information;

[0154] According to the equipment placement information and equipment movement configuration information, determine whether the intelligent robot meets the preset smooth driving conditions;

[0155] When it is determined that the intelligent robot meets the smooth driving conditions, the basic driving path plan is determined as the first optimized driving path plan;

[0156] When it is determined that the intelligent robot does not meet the conditions for smooth driving, the target blocking equipment that blocks the smooth driving of the intelligent robot is determined based on the regional channel space information, equipment placement information and driving demand space information of the first driving area; a blocking response plan for the target blocking equipment is generated based on the equipment movement configuration information and the equipment placement information; according to the blocking response plan, the basic driving path plan is subjected to corresponding route update operations to obtain the first optimized driving path plan.

[0157] Optionally, the device placement information of the regional device may include, but is not limited to, one or more of the placement position information, placement method information, placement information, location information and other placement information of the regional device, and is not limited in the embodiment of the present invention.

[0158] Optionally, the device movement configuration information of the regional device may be information reflecting whether the regional device can change its position, the method and conditions for changing the position, etc.; further, for example: if the regional device is a medical device, it generally cannot be easily moved and changed in position; for example, if the regional device is an ordinary device such as a trash can, it can be moved and changed in position, and the embodiments of the present invention are not limited to this.

[0159] Optionally, the regional channel space information of the first driving area may include, but is not limited to, one or more of the length, width and height information of the regional channel of the first driving area, the road surface and wall flatness information of the regional channel, the surrounding obstruction information of the regional channel, and other information that can reflect the regional channel space, and the embodiment of the present invention is not limited thereto.

[0160] Optionally, the spatial information required for the intelligent robot to drive may include, but is not limited to, one or more of the length, width, and height information required for the intelligent robot to drive smoothly, road and wall flatness information, and other information that can reflect its spatial requirements, etc., and the embodiments of the present invention are not limited thereto.

[0161] Optionally, the blocking response plan for the target blocking device can be understood as the optimal detour plan for the intelligent robot for the target blocking device, or a plan for controlling the target blocking device to avoid the intelligent robot so that the intelligent robot can pass smoothly, which is not limited in the embodiments of the present invention.

[0162] It can be seen that this optional embodiment can provide a method for determining the first optimized driving path plan from the equipment level, and match the corresponding method for determining the first optimized driving path plan for the intelligent robot that meets the smooth driving conditions and does not meet the smooth driving conditions, respectively. This is conducive to improving the diversity, flexibility, pertinence and rationality of the method for determining the first optimized driving path plan, and thus is conducive to improving the accuracy and reliability of the determined first optimized driving path plan. In addition, when the intelligent robot does not meet the smooth driving conditions, the corresponding blocking response plan is generated according to the equipment movement configuration information and the equipment placement information to determine the first optimized driving path plan, which is conducive to improving the accuracy and reliability of the intelligent robot's blocking response, and is conducive to improving the accuracy and efficiency of the intelligent robot's route update.

[0163] In yet another optional embodiment, the above-mentioned performing a corresponding second path optimization operation on the first optimized driving path plan according to the relevant personnel information to obtain the second optimized driving path plan may include:

[0164] According to the first optimized driving path plan, determine the second driving area corresponding to the intelligent robot, and determine the real-time personnel location and distribution information of the regional personnel in the second driving area and the personnel responsible event information according to the relevant personnel information;

[0165] Based on the real-time personnel location and distribution information, the regional personnel are divided into one or more personnel distribution groups, and the density of each personnel distribution group is determined;

[0166] According to the event information of personnel responsible, determine the responsibility of personnel in each area and the nature of event operation, and analyze the degree of position maintenance requirements of personnel in each area according to the responsibility of personnel in each area and the nature of event operation;

[0167] Determine the location change requirements for personnel in each area based on the personnel responsible for the event information;

[0168] According to the density of each group of personnel distribution, the degree of position maintenance requirements of personnel in each area, and the position change requirements, the predicted avoidance efficiency of each group of personnel distribution for the intelligent robot is determined;

[0169] According to the personnel responsible for the event information, the nature of the determined target file and the content of the conveyed event, determine the emergency priority of the personnel responsible for the event and the target file transportation event;

[0170] According to the density of each personnel distribution group and the predicted avoidance efficiency and emergency priority, a corresponding second path optimization operation is performed on the first optimized driving path plan to obtain a second optimized driving path plan.

[0171] Optionally, the personnel responsible for event information of the regional personnel may be understood as event information / action behavior information that the regional personnel are currently executing or continuously executing, which is not limited in the embodiment of the present invention.

[0172] Optionally, the responsibility situation of the regional personnel can be understood as the responsibility risk situation of the events for which the regional personnel are responsible; further, for example: for example, the regional personnel are medical staff, and the event information for which the personnel are responsible is medical treatment, then the responsibility situation of the regional personnel is used to indicate that the responsibility risk of the regional personnel is relatively high; for another example, if the regional personnel is a patient waiting to be called, then the responsibility situation of the regional personnel is used to indicate that the responsibility risk of the regional personnel is relatively low. The same applies to other situations, and the embodiments of the present invention are not limited thereto.

[0173] Optionally, the nature of the event operation of the regional personnel can be understood as the nature of the event for which the regional personnel is responsible, or the nature of the reason for the regional personnel to stay at that location; for example: the event information of the regional personnel being responsible for medical treatment and the event information of the regional personnel being responsible for cleaning have different event natures corresponding to the two. Furthermore, their requirements for not walking around at will are also different. The conditions for doctors to change positions and cleaning staff to change positions are obviously different. Other situations are similarly applicable and are not limited in the embodiments of the present invention.

[0174] Optionally, the degree of position maintenance requirement of regional personnel can be understood as whether the regional personnel can easily change their positions; for example: if the regional personnel is a doctor, the degree of position maintenance requirement is higher, and if the regional personnel is a patient waiting to be called or a caregiver, the degree of position maintenance requirement is relatively low; for example, a patient waiting to be called can move slightly to the side on their own initiative, while a patient undergoing examination cannot move at will, and other situations are similar, so examples will not be given here one by one.

[0175] Optionally, the required manner of position change of regional personnel can be understood as the operations required for regional personnel to perform position change; further, for example, if the regional personnel is a cleaning staff, then he or she can move directly, and if the regional personnel is a patient on a hospital bed, then it is more troublesome for him or her to move his or her position. The same is true for other situations, and examples will not be given here one by one.

[0176] Further optionally, the above-mentioned predicted avoidance efficiency of each personnel distribution group with respect to the intelligent robot is determined based on the density of each personnel distribution group, the degree of position maintenance requirement of the personnel in each area, and the position change requirement method. For example: when the density is used to indicate that the denser the personnel, the degree of position maintenance requirement is used to indicate that it is more difficult to move around and change positions, and the position change requirement method is used to indicate that the position change requirement operation is more complicated and troublesome, it can be determined that the predicted avoidance efficiency is lower. The same applies to other situations, and the embodiments of the present invention are not limited thereto.

[0177] Further optionally, the above-mentioned emergency priority situations corresponding to the personnel responsible event and the target file transportation event are determined based on the personnel responsible event information, the determined file nature of the target file and the communication event content. For example: when the personnel responsible event information is used to represent an event of standing in place waiting for a call, and the file nature of the target file and the communication event content are used to represent files related to operating an emergency operation, then it can be determined that the emergency priority of the target file transportation event is higher than that of the personnel responsible event. Other situations are similarly applicable and are not limited to the embodiments of the present invention.

[0178] It can be seen that this optional embodiment can provide a method for determining a second optimized driving path plan from the personnel level, and perform corresponding second path optimization operations according to the determined density of each personnel distribution group and the predicted avoidance efficiency and emergency priority situation to obtain a second optimized driving path plan, which is conducive to improving the comprehensiveness, integrity and rationality of the method for determining the second optimized driving path plan, and is conducive to improving the diversity, flexibility and pertinence of the determination parameters used to determine the second optimized driving path plan, and thus is conducive to improving the accuracy and reliability of the determined second optimized driving path plan, thereby helping to improve the accuracy and efficiency of intelligent robot file transportation based on the second optimized driving path plan.

[0179] In yet another optional embodiment, the above-mentioned performing a corresponding second path optimization operation on the first optimized driving path plan according to the density of each personnel distribution group and the predicted avoidance efficiency and emergency priority to obtain the second optimized driving path plan may include:

[0180] According to the density of each personnel distribution group, the predicted avoidance efficiency, and the emergency priority, all personnel distribution groups are divided into a first personnel group that meets the preset robot active avoidance conditions and / or a second personnel group that meets the preset robot no need to avoid conditions;

[0181] When all the personnel distribution groups include the first personnel group, a target driving section area where the intelligent robot needs to change its route is determined according to the first personnel group; a first optimal detour plan for the intelligent robot for the target driving section area is generated according to the target driving section area and the real-time personnel position and distribution information; according to the first optimal detour plan, a corresponding route update operation is performed on the first optimized driving path plan to obtain a second optimized driving path plan;

[0182] When all the personnel distribution groups do not include the first personnel group, the first optimized driving route plan is determined as the second optimized driving route plan.

[0183] Optionally, the above-mentioned first group of personnel that meets the preset robot active avoidance conditions and the second group of personnel that meets the preset robot no-avoidance conditions are illustrated by way of example: when the density of the personnel distribution group is used to indicate super density, the predicted avoidance efficiency of the personnel distribution group is used to indicate low avoidance efficiency, the emergency priority situation is used to indicate that the emergency priority of the events in which the personnel of the personnel distribution group are responsible is higher than the emergency priority of the target file transportation event, etc., then the personnel distribution group can be determined to be the first group of personnel that meets the preset robot active avoidance conditions; when the density of the personnel distribution group is used to indicate a very low density, the predicted avoidance efficiency of the personnel distribution group is used to indicate a high avoidance efficiency, the emergency priority situation is used to indicate that the emergency priority of the events in which the personnel of the personnel distribution group are responsible is lower than the emergency priority of the target file transportation event, etc., then the personnel distribution group can be determined to be the second group of personnel that meets the preset robot no-avoidance conditions, and other situations are similarly obtainable, and the embodiments of the present invention are not limited thereto.

[0184] Optionally, the second group of people who meet the preset conditions for the robot not to avoid may correspond to a situation where neither the regional personnel nor the intelligent robot need to avoid, or may be a situation where the regional personnel actively avoid the intelligent robot, which is not limited in the embodiments of the present invention.

[0185] Further optionally, when the second group of people meets the need to actively avoid the intelligent robot, a voice broadcast is generated to notify the people in the area to take active avoidance actions so that the intelligent robot can pass smoothly, which is not limited in the embodiment of the present invention.

[0186] Optionally, the target driving section area where the intelligent robot needs to change the route may correspond to the area where the first group of people is located (a targeted small area), or may correspond to a large area corresponding to the first group of people, which is not limited in the embodiment of the present invention.

[0187] Optionally, the first optimal detour solution may specifically be that the intelligent robot detours the target driving section area without creating a new obstruction and travels smoothly to the next link position, which is not limited in the embodiment of the present invention.

[0188] It can be seen that this optional embodiment can match the corresponding second optimized driving path plan determination method according to whether the personnel distribution group includes the first personnel group or does not include the first personnel group, which is conducive to improving the comprehensiveness, integrity and rationality of the second optimized driving path plan determination method, and is conducive to improving the diversity, flexibility and pertinence of the second optimized driving path plan determination method, and thus is conducive to improving the accuracy and reliability of the determined second optimized driving path plan. In addition, when the personnel distribution group includes the first personnel group, the first best detour plan of the intelligent robot is generated and then the second optimized driving path plan is determined, which is conducive to improving the detour accuracy, reliability, efficiency and timeliness of the intelligent robot, and thus is conducive to improving the accuracy and efficiency of file transportation of the intelligent robot.

[0189] In yet another optional embodiment, the above-mentioned generating a blocking response plan for the target blocking device according to the device movement configuration information and the device placement information may include:

[0190] Determine the device movement nature and device movement requirements of the target blocking device according to the device movement configuration information;

[0191] According to the equipment movement properties and equipment movement execution requirements of the target blocking equipment, the determined transportation travel priority characteristics corresponding to the intelligent robot and / or the target file, the target blocking equipment is divided into a first blocking equipment that meets the preset execution avoidance conditions and / or a second blocking equipment that meets the preset non-execution avoidance conditions;

[0192] When the target blocking device includes a second blocking device, generating a second optimal detour route for the intelligent robot for the second blocking device according to the current placement position of the second blocking device;

[0193] When the target blocking device includes a first blocking device, an optimal avoidance plan of the first blocking device for the intelligent robot is generated according to the current placement position of the first blocking device and the first driving involved area;

[0194] According to the second optimal detour route and / or the optimal avoidance plan, a blocking response plan for the target blocking device is determined.

[0195] Optionally, the device mobility property of the target blocking device may include, but is not limited to, movable property, immovable property, easily movable property, complex movable property, etc., which is not limited in the embodiment of the present invention.

[0196] Optionally, the above-mentioned first blocking device that meets the preset execution avoidance condition and the second blocking device that meets the preset non-execution avoidance condition are illustrated by way of example: for example, when the device movement property of the target blocking device is used to indicate that it can move, the device movement execution requirement is used to indicate that the movement requirement is less or the movement difficulty is lower, and the transport driving priority characteristic is used to indicate priority waiting for the device to avoid, then the target blocking device can be determined to be the first blocking device that meets the preset execution avoidance condition; for another example, when the device movement property of the target blocking device is used to indicate that it cannot move, the device movement execution requirement is used to indicate that the movement requirement is more or the movement difficulty is higher, and the transport driving priority characteristic is used to indicate priority detour, then the target blocking device can be determined to be the second blocking device that meets the preset non-execution avoidance condition, and other situations are similarly obtainable, and the embodiments of the present invention are not limited thereto.

[0197] Optionally, the second best detour route may be that the intelligent robot bypasses the first blocking device without creating a new blocking situation and passes smoothly to the next link position, which is not limited in the embodiment of the present invention.

[0198] Optionally, the best avoidance plan of the first blocking device for the intelligent robot may be an operating plan for controlling the first blocking device to not block the driving of the intelligent robot; further, according to the best avoidance plan, the first blocking device is controlled to perform corresponding avoidance operations, which is not limited in the embodiments of the present invention.

[0199] It can be seen that this optional embodiment can provide a method for determining the best avoidance plan for the target blocking device including the first blocking device, and can provide a method for determining the second best detour route for the intelligent robot for the target blocking device including the second blocking device, which is beneficial to improving the comprehensiveness, integrity and rationality of the method for determining the blocking response plan for the target blocking device, and further beneficial to improving the accuracy and reliability of the determined blocking response plan. In addition, the corresponding route adjustment objects and adjustment plan determination methods are matched according to different situations to provide the best blocking response plan, which is beneficial to improving the accuracy and efficiency of file transportation by the intelligent robot.

[0200] Embodiment 2

[0201] See also Figure 2 , Figure 2 is a flow chart of another intelligent robot control method applied to hospital scenarios disclosed in an embodiment of the present invention. Figure 2 The described method can be applied to an intelligent robot in a hospital scenario, wherein the intelligent robot includes a main body and a corresponding control device, wherein the intelligent robot can be used to access various information approval systems of the hospital, wherein the control device may include a server, wherein the server includes a local server or a cloud server, and the embodiments of the present invention are not limited thereto. Figure 2 As shown, the intelligent robot control method applied to hospital scenarios includes the following operations:

[0202] 201. According to the process query information for the target file input by the user, determine the current expected process link and progress of the target file, and determine the current actual process link and progress of the target file.

[0203] 202. Based on the current expected process links and progress, and the current actual process links and progress, determine whether the intelligent robot meets the preset driving conditions for the next link.

[0204] 203. When it is determined that the intelligent robot meets the driving conditions of the next link, a driving path plan for the intelligent robot to transport the target file is determined based on the first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link; according to the driving path plan, the intelligent robot is controlled to perform corresponding file transportation operations on the target file.

[0205] 204. Collect the current location path information of the intelligent robot.

[0206] 205. Determine the position path deviation of the intelligent robot based on the current position path information and the driving path plan, and determine the current environmental complexity of the hospital scene based on the relevant equipment information and relevant personnel information of the hospital scene where the intelligent robot is located.

[0207] Optionally, the current environmental complexity of the hospital scene can be reflected by the number and distribution of personnel, the number and distribution of various types of medical equipment, etc.; further, for example: the more personnel, the denser the distribution of personnel, the more medical equipment, and the denser the placement of medical equipment, the more complex the current environment can be determined to indicate that the current environment is more complex, and other situations are similarly obtainable, and the embodiments of the present invention are not limited thereto.

[0208] 206. According to the position path deviation and the complexity of the current environment, determine whether the intelligent robot meets the preset abnormal driving conditions.

[0209] Further optionally, the method may also include the following operations:

[0210] When it is determined that the intelligent robot does not meet the abnormal driving conditions, the above steps 204-206 are executed again, which is not limited in the embodiment of the present invention.

[0211] 207. When it is determined that the intelligent robot meets the abnormal driving conditions, a path deviation warning instruction corresponding to the intelligent robot is generated, and / or a corresponding driving path update operation is performed on the intelligent robot.

[0212] In the embodiment of the present invention, for other descriptions of step 201 to step 207, please refer to other detailed descriptions of step 101 to step 104 in embodiment 1, and the embodiment of the present invention will not be repeated here.

[0213] It can be seen that the embodiment of the present invention can determine the driving path plan of the intelligent robot to transport the target file according to the determined relevant information when it is judged that the intelligent robot meets the driving conditions of the next link, and then control the intelligent robot to perform the corresponding file transportation operation on the target file, which is conducive to improving the comprehensiveness, integrity and rationality of the intelligent robot control method applied to hospital scenarios, and is conducive to improving the rationality of the method for determining the driving path plan of the intelligent robot, and is conducive to improving the diversity, pertinence and rationality of the determination parameters used to determine the driving path plan of the intelligent robot, and is conducive to improving the accuracy and reliability of the determined driving path plan, thereby helping to improve the control accuracy and reliability of the intelligent robot, and is conducive to improving the control efficiency and convenience of the intelligent robot, and further improving the document management of the intelligent robot. The accuracy and efficiency of document transportation can be improved, unnecessary document transportation can be reduced, and the timeliness, accuracy and efficiency of the intelligent robot's document transportation adjustment can be improved; and it can also judge whether the intelligent robot meets the driving abnormality conditions according to the position path deviation of the intelligent robot and the current environmental complexity of the hospital scene. If so, a path deviation warning instruction corresponding to the intelligent robot is generated and / or a corresponding driving path update operation is performed on the intelligent robot, and a driving abnormality response method for the intelligent robot is provided, which is conducive to improving the comprehensiveness and rationality of the driving abnormality response method, and then it is conducive to improving the accuracy and reliability of the intelligent robot's driving abnormality response, as well as improving the efficiency and timeliness of the intelligent robot's driving abnormality response, thereby helping to improve the accuracy, efficiency and timeliness of the intelligent robot's document transportation adjustment.

[0214] In an optional embodiment, judging whether the intelligent robot meets the preset driving abnormality condition according to the position path deviation and the current environmental complexity may include:

[0215] Determine the rationality of the intelligent robot's deviation based on the position path deviation, relevant equipment information and relevant personnel information;

[0216] According to the current complex environment, determine the reasonableness threshold of the intelligent robot's deviation for hospital scenarios;

[0217] Determine whether the deviation rationality is greater than or equal to a preset deviation rationality threshold;

[0218] When it is determined that the deviation rationality is greater than or equal to the deviation rationality threshold, it is determined that the intelligent robot does not meet the preset driving abnormality condition;

[0219] When it is determined that the deviation rationality is less than the deviation rationality threshold, it is determined that the intelligent robot meets the preset abnormal driving condition.

[0220] Optionally, for example: when the intelligent robot has a position path deviation, the position path deviation occurs because there are many people and equipment in the current hospital scene, and the intelligent robot only makes the optimal position route adjustment. Then it can be determined that the difference rationality is greater than or equal to the deviation rationality threshold, and further determined that the intelligent robot does not meet the preset abnormal driving conditions. Other situations can be obtained similarly, and the embodiments of the present invention are not limited.

[0221] Optionally, the complexity of the current environment is used to represent that the more personnel / medical equipment there are and the denser their distribution is, the larger the specific value of the deviation rationality threshold can be set. The same applies to other situations, and the embodiments of the present invention are not limited thereto.

[0222] It can be seen that this optional embodiment can provide a method for determining the reasonableness of deviation and a method for determining a deviation reasonableness threshold of the intelligent robot, and then determine the satisfaction of the driving abnormality conditions of the intelligent robot based on the comparison of the size of the deviation reasonableness and the deviation reasonableness threshold, which is conducive to improving the comprehensiveness and rationality of the method for determining the satisfaction of the driving abnormality conditions, and then is conducive to improving the accuracy and reliability of the determined driving abnormality conditions, thereby facilitating improving the accuracy, efficiency and timeliness of the response to driving abnormalities for the intelligent robot. In addition, the deviation reasonableness threshold can be determined according to the complexity of the current environment, which is conducive to improving the rationality of the method for determining the deviation reasonableness threshold, and then is conducive to improving the accuracy and pertinence of the determined deviation reasonableness threshold, improving the accuracy and reliability of the driving abnormality judgment for the intelligent robot, reducing unnecessary driving abnormality response operations and improving the execution accuracy of driving abnormality response operations.

[0223] In another optional embodiment, judging whether the intelligent robot meets the preset smooth driving conditions according to the device placement information and the device movement configuration information may include:

[0224] According to the regional channel spatial information of the first driving area and the driving demand spatial information of the intelligent robot, it is determined whether the first driving area meets the preset basic spatial feasibility conditions;

[0225] When it is determined that the area involved in the first driving meets the basic space feasibility condition, it is determined whether the area involved in the first driving meets the preset no-equipment-blocking condition according to the equipment placement information;

[0226] When it is determined that the first driving area meets the condition of no equipment blocking, determining that the intelligent robot meets the preset smooth driving condition;

[0227] When it is determined that the first driving area does not meet the equipment-free blocking condition, it is determined whether the first driving area meets the preset equipment-free blocking condition according to the regional channel space information, the driving demand space information and the equipment placement information;

[0228] When it is determined that the first driving area meets the equipment unblocked condition, determining that the intelligent robot meets the preset smooth driving condition;

[0229] When it is determined that the first driving-related area does not meet the equipment unblocked condition, it is determined that the intelligent robot does not meet the preset smooth driving condition.

[0230] Further optionally, the above judgment of whether the first driving area meets the preset basic space feasibility conditions is illustrated by an example: judging whether the first driving area can allow the intelligent robot to pass smoothly without obstruction by personnel and / or equipment (that is, the maximum free space and clear environment); if so, it is determined that the preset basic space feasibility conditions are met; if not, it is determined that the preset basic space feasibility conditions are not met, and the embodiments of the present invention are not limited thereto.

[0231] Further optionally, the above judgment of whether the first driving area satisfies the preset no-equipment blocking condition is illustrated by, for example: judging whether there is no equipment placed in the first driving area, if so, determining that the preset no-equipment blocking condition is met; if not, determining that the preset no-equipment blocking condition is not met, which is not limited in the embodiment of the present invention.

[0232] Further optionally, the above judgment of whether the first driving area satisfies the preset equipment non-blocking condition is illustrated by an example: judging whether a device is placed in the first driving area but the device does not block the driving of the intelligent robot. If so, it is determined that the preset equipment non-blocking condition is met; if not, it is determined that the preset equipment non-blocking condition is not met, and the embodiment of the present invention is not limited thereto.

[0233] It can be seen that this optional embodiment can determine whether the conditions for smooth driving of the intelligent robot are met from three levels: basic spatial feasible conditions, no equipment blocking conditions, and equipment unblocking conditions. This is beneficial to improving the comprehensiveness, integrity, rationality, and progressiveness of the method for determining whether the conditions for smooth driving of the intelligent robot are met, and thus is beneficial to improving the accuracy and reliability of the determined conditions for smooth driving, thereby helping to improve the accuracy and reliability of the subsequent execution of the first optimized driving path plan based on the conditions for smooth driving.

[0234] Embodiment 3

[0235] See also Figure 3 , Figure 3 : is a schematic diagram of the structure of an intelligent robot disclosed in an embodiment of the present invention. Figure 3 The described intelligent robot includes a main body and a corresponding control device, wherein the intelligent robot can be used to access various information approval systems of the hospital, wherein the control device may include a server, wherein the server includes a local server or a cloud server, which is not limited in the embodiment of the present invention. Figure 3 As shown, the control device may include:

[0236] The link and progress determination module 301 is used to determine the current expected process link and progress of the target file according to the process query information for the target file input by the user, and to determine the current actual process link and progress of the target file.

[0237] The judgment module 302 is used to judge whether the intelligent robot meets the preset driving conditions for the next link based on the current expected process link and progress and the current actual process link and progress.

[0238] The path plan determination module 303 is used to determine the driving path plan of the intelligent robot to transport the target file based on the first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link when the judgment module 302 determines that the intelligent robot meets the driving conditions of the next link.

[0239] The file transport execution module 304 is used to control the intelligent robot to perform corresponding file transport operations on the target file according to the driving path plan;

[0240] The process query information of the target file includes one or more of the target file number, applicant, keyword, other information that can determine the target file as a query object, and other information that can determine the required query content about the target file to be queried;

[0241] Among them, the process links corresponding to the current expected process links and progress, and the current actual process links and progress all include one or more of the application approval link, information submission link, document stamping link and other document processing links.

[0242] It can be seen that the implementation Figure 3 The described intelligent robot can, when it is judged that the intelligent robot meets the driving conditions of the next link, determine the driving path plan for the intelligent robot to transport the target file based on the determined relevant information, and then control the intelligent robot to perform the corresponding file transportation operation on the target file, which is conducive to improving the comprehensiveness, integrity and rationality of the intelligent robot control method applied to hospital scenarios, as well as improving the rationality of the intelligent robot's driving path plan determination method, and is conducive to improving the diversity, pertinence and rationality of the determination parameters used to determine the intelligent robot's driving path plan, and is conducive to improving the accuracy and reliability of the determined driving path plan, thereby helping to improve the control accuracy and reliability of the intelligent robot, as well as improving the control efficiency and convenience of the intelligent robot, further improving the accuracy and efficiency of the intelligent robot's file transportation, reducing unnecessary file transportation obstructions, and improving the timeliness, accuracy and efficiency of the intelligent robot's file transportation adjustment.

[0243] In an optional embodiment, the path plan determination module 303 determines the driving path plan of the intelligent robot transporting the target file according to the determined first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link, specifically including:

[0244] Determine a basic driving path plan of the intelligent robot according to the determined first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link;

[0245] Determine relevant device information corresponding to the devices placed in the hospital scene where the intelligent robot is located, and perform a corresponding first path optimization operation on the basic driving path plan according to the relevant device information to obtain a first optimized driving path plan;

[0246] Determine relevant personnel information corresponding to relevant personnel in the hospital scene, and perform a corresponding second path optimization operation on the first optimized driving path plan according to the relevant personnel information to obtain a second optimized driving path plan;

[0247] According to the second optimized driving path plan, a driving path plan for the intelligent robot to transport the target file is determined.

[0248] It can be seen that the implementation Figure 4 The described intelligent robot can also determine the basic driving path plan of the intelligent robot, and further perform corresponding path optimization operations on the intelligent robot from the equipment level and personnel level in the hospital scene to obtain the driving path plan of the intelligent robot, which is conducive to improving the comprehensiveness, integrity and rationality of the method of determining the driving path plan of the intelligent robot, and is conducive to improving the diversity, flexibility and pertinence of the considerations in determining the driving path plan of the intelligent robot, and thus is conducive to improving the accuracy and reliability of the determined driving path plan, thereby helping to improve the accuracy and efficiency of the intelligent robot file transportation based on the determined driving path plan.

[0249] In another optional embodiment, the path plan determination module 303 performs a corresponding first path optimization operation on the basic driving path plan according to the relevant device information, and the manner of obtaining the first optimized driving path plan specifically includes:

[0250] Determine the first driving area corresponding to the intelligent robot according to the basic driving path plan, and determine the equipment placement information and equipment movement configuration information of the regional equipment in the first driving area according to the relevant equipment information;

[0251] According to the equipment placement information and equipment movement configuration information, determine whether the intelligent robot meets the preset smooth driving conditions;

[0252] When it is determined that the intelligent robot meets the smooth driving conditions, the basic driving path plan is determined as the first optimized driving path plan;

[0253] When it is determined that the intelligent robot does not meet the conditions for smooth driving, the target blocking equipment that blocks the smooth driving of the intelligent robot is determined based on the regional channel space information, equipment placement information and driving demand space information of the first driving area; a blocking response plan for the target blocking equipment is generated based on the equipment movement configuration information and the equipment placement information; according to the blocking response plan, the basic driving path plan is subjected to corresponding route update operations to obtain the first optimized driving path plan.

[0254] It can be seen that the implementation Figure 4The described intelligent robot can also provide a first optimized driving path plan determination method from the equipment level, and match the corresponding first optimized driving path plan determination method according to the intelligent robot meeting the smooth driving conditions and not meeting the smooth driving conditions, which is conducive to improving the diversity, flexibility, pertinence and rationality of the first optimized driving path plan determination method, and thus is conducive to improving the accuracy and reliability of the determined first optimized driving path plan. In addition, when the intelligent robot does not meet the smooth driving conditions, the corresponding blocking response plan is generated according to the equipment movement configuration information and the equipment placement information to determine the first optimized driving path plan, which is conducive to improving the accuracy and reliability of the intelligent robot's blocking response, and is conducive to improving the accuracy and efficiency of the intelligent robot's route update.

[0255] In another optional embodiment, the path plan determination module 303 performs a corresponding second path optimization operation on the first optimized driving path plan according to the relevant personnel information, and the manner of obtaining the second optimized driving path plan specifically includes:

[0256] According to the first optimized driving path plan, determine the second driving area corresponding to the intelligent robot, and determine the real-time personnel location and distribution information of the regional personnel in the second driving area and the personnel responsible event information according to the relevant personnel information;

[0257] Based on the real-time personnel location and distribution information, the regional personnel are divided into one or more personnel distribution groups, and the density of each personnel distribution group is determined;

[0258] According to the event information of personnel responsible, determine the responsibility of personnel in each area and the nature of event operation, and analyze the degree of position maintenance requirements of personnel in each area according to the responsibility of personnel in each area and the nature of event operation;

[0259] Determine the location change requirements for personnel in each area based on the personnel responsible for the event information;

[0260] According to the density of each group of personnel distribution, the degree of position maintenance requirements of personnel in each area, and the position change requirements, the predicted avoidance efficiency of each group of personnel distribution for the intelligent robot is determined;

[0261] According to the personnel responsible for the event information, the nature of the determined target file and the content of the conveyed event, determine the emergency priority of the personnel responsible for the event and the target file transportation event;

[0262] According to the density of each personnel distribution group and the predicted avoidance efficiency and emergency priority, a corresponding second path optimization operation is performed on the first optimized driving path plan to obtain a second optimized driving path plan.

[0263] It can be seen that the implementation Figure 4 The described intelligent robot can also provide a method for determining a second optimized driving path plan from a personnel level, and perform corresponding second path optimization operations according to the determined density of each personnel distribution group and the predicted avoidance efficiency and emergency priority to obtain a second optimized driving path plan. This is conducive to improving the comprehensiveness, integrity and rationality of the method for determining the second optimized driving path plan, as well as improving the diversity, flexibility and pertinence of the determination parameters used to determine the second optimized driving path plan, thereby helping to improve the accuracy and reliability of the determined second optimized driving path plan, and thus helping to improve the accuracy and efficiency of file transportation by the intelligent robot based on the second optimized driving path plan.

[0264] In another optional embodiment, the path plan determination module 303 performs a corresponding second path optimization operation on the first optimized driving path plan according to the density of each personnel distribution group and the predicted avoidance efficiency and emergency priority, and the method of obtaining the second optimized driving path plan specifically includes:

[0265] According to the density of each personnel distribution group, the predicted avoidance efficiency, and the emergency priority, all personnel distribution groups are divided into a first personnel group that meets the preset robot active avoidance conditions and / or a second personnel group that meets the preset robot no need to avoid conditions;

[0266] When all the personnel distribution groups include the first personnel group, a target driving section area where the intelligent robot needs to change its route is determined according to the first personnel group; a first optimal detour plan for the intelligent robot for the target driving section area is generated according to the target driving section area and the real-time personnel position and distribution information; according to the first optimal detour plan, a corresponding route update operation is performed on the first optimized driving path plan to obtain a second optimized driving path plan;

[0267] When all the personnel distribution groups do not include the first personnel group, the first optimized driving route plan is determined as the second optimized driving route plan.

[0268] It can be seen that the implementation Figure 4The described intelligent robot can also match the corresponding second optimized driving path plan determination method according to whether the personnel distribution group includes the first personnel group or does not include the first personnel group, which is conducive to improving the comprehensiveness, integrity and rationality of the second optimized driving path plan determination method, as well as improving the diversity, flexibility and pertinence of the second optimized driving path plan determination method, thereby helping to improve the accuracy and reliability of the determined second optimized driving path plan. In addition, when the personnel distribution group includes the first personnel group, the first best detour plan of the intelligent robot is generated and then the second optimized driving path plan is determined, which is conducive to improving the detour accuracy, reliability, efficiency and timeliness of the intelligent robot, thereby helping to improve the accuracy and efficiency of file transportation of the intelligent robot.

[0269] In another optional embodiment, the path solution determination module 303 generates a blocking solution for the target blocking device according to the device movement configuration information and the device placement information, specifically including:

[0270] Determine the device movement nature and device movement requirements of the target blocking device according to the device movement configuration information;

[0271] According to the equipment movement properties and equipment movement execution requirements of the target blocking equipment, the determined transportation travel priority characteristics corresponding to the intelligent robot and / or the target file, the target blocking equipment is divided into a first blocking equipment that meets the preset execution avoidance conditions and / or a second blocking equipment that meets the preset non-execution avoidance conditions;

[0272] When the target blocking device includes a second blocking device, generating a second optimal detour route for the intelligent robot for the second blocking device according to the current placement position of the second blocking device;

[0273] When the target blocking device includes a first blocking device, an optimal avoidance plan of the first blocking device for the intelligent robot is generated according to the current placement position of the first blocking device and the first driving involved area;

[0274] According to the second optimal detour route and / or the optimal avoidance plan, a blocking response plan for the target blocking device is determined.

[0275] It can be seen that the implementation Figure 4The described intelligent robot can also provide a corresponding method for determining the best avoidance plan for the target blocking device including the first blocking device, and provide a corresponding method for determining the second best detour route for the target blocking device including the second blocking device, which is conducive to improving the comprehensiveness, integrity and rationality of the method for determining the blocking response plan for the target blocking device, and thus is conducive to improving the accuracy and reliability of the determined blocking response plan. In addition, the corresponding route adjustment objects and adjustment plan determination methods are matched according to different situations to provide the best blocking response plan, which is conducive to improving the accuracy and efficiency of file transportation by the intelligent robot.

[0276] In yet another optional embodiment, Figure 4 As shown, the control device may also include:

[0277] The driving abnormality control module 305 is used to collect the current position path information of the intelligent robot after the file transportation execution module 304 controls the intelligent robot to perform the corresponding file transportation operation on the target file according to the driving path plan; determine the position path deviation of the intelligent robot according to the current position path information and the driving path plan, and determine the current environmental complexity of the hospital scene according to the relevant equipment information and relevant personnel information of the hospital scene where the intelligent robot is located; determine whether the intelligent robot meets the preset driving abnormality conditions according to the position path deviation and the current environmental complexity; when it is determined that the intelligent robot meets the driving abnormality conditions, generate a corresponding path deviation warning instruction for the intelligent robot, and / or perform a corresponding driving path update operation on the intelligent robot.

[0278] It can be seen that the implementation Figure 4 The described intelligent robot can also judge whether the intelligent robot meets the driving abnormality conditions based on the position path deviation of the intelligent robot and the current environmental complexity of the hospital scene. If so, it generates a corresponding path deviation warning instruction for the intelligent robot and / or performs corresponding driving path update operations on the intelligent robot, and provides a driving abnormality response method for the intelligent robot, which is conducive to improving the comprehensiveness and rationality of the driving abnormality response method, and then helps to improve the accuracy and reliability of the intelligent robot's driving abnormality response, as well as improve the efficiency and timeliness of the intelligent robot's driving abnormality response, thereby helping to improve the accuracy, efficiency and timeliness of the intelligent robot's file transportation adjustment.

[0279] In another optional embodiment, the driving abnormality control module 305 determines whether the intelligent robot meets the preset driving abnormality condition according to the position path deviation and the current environmental complexity, specifically including:

[0280] Determine the rationality of the intelligent robot's deviation based on the position path deviation, relevant equipment information and relevant personnel information;

[0281] According to the current complex environment, determine the reasonableness threshold of the intelligent robot's deviation for hospital scenarios;

[0282] Determine whether the deviation rationality is greater than or equal to a preset deviation rationality threshold;

[0283] When it is determined that the deviation rationality is greater than or equal to the deviation rationality threshold, it is determined that the intelligent robot does not meet the preset driving abnormality condition;

[0284] When it is determined that the deviation rationality is less than the deviation rationality threshold, it is determined that the intelligent robot meets the preset abnormal driving condition.

[0285] It can be seen that the implementation Figure 4 The described intelligent robot can also provide a method for determining the reasonableness of deviation of the intelligent robot and a method for determining the reasonableness of deviation threshold, and then determine the satisfaction of the driving abnormality conditions of the intelligent robot based on the comparison of the reasonableness of deviation and the reasonableness of deviation threshold, which is conducive to improving the comprehensiveness and rationality of the method for determining the satisfaction of driving abnormality conditions, and then is conducive to improving the accuracy and reliability of the determined driving abnormality conditions, thereby helping to improve the accuracy, efficiency and timeliness of the driving abnormality response for the intelligent robot. In addition, the reasonableness of deviation threshold can be determined according to the complexity of the current environment, which is conducive to improving the rationality of the method for determining the reasonableness of deviation threshold, and then is conducive to improving the accuracy and pertinence of the determined reasonableness of deviation threshold, improving the accuracy and reliability of the driving abnormality judgment for the intelligent robot, reducing unnecessary driving abnormality response operations and improving the execution accuracy of driving abnormality response operations.

[0286] In another optional embodiment, the path plan determination module 303 determines whether the intelligent robot meets the preset smooth driving conditions according to the device placement information and the device movement configuration information, specifically including:

[0287] According to the regional channel spatial information of the first driving area and the driving demand spatial information of the intelligent robot, it is determined whether the first driving area meets the preset basic spatial feasibility conditions;

[0288] When it is determined that the area involved in the first driving meets the basic space feasibility condition, it is determined whether the area involved in the first driving meets the preset no-equipment-blocking condition according to the equipment placement information;

[0289] When it is determined that the first driving area meets the condition of no equipment blocking, determining that the intelligent robot meets the preset smooth driving condition;

[0290] When it is determined that the first driving area does not meet the equipment-free blocking condition, it is determined whether the first driving area meets the preset equipment-free blocking condition according to the regional channel space information, the driving demand space information and the equipment placement information;

[0291] When it is determined that the first driving area meets the equipment unblocked condition, determining that the intelligent robot meets the preset smooth driving condition;

[0292] When it is determined that the first driving-related area does not meet the equipment unblocked condition, it is determined that the intelligent robot does not meet the preset smooth driving condition.

[0293] It can be seen that the implementation Figure 4 The described intelligent robot can also determine whether the conditions for smooth driving of the intelligent robot are met from three levels: basic spatial feasible conditions, no equipment blocking conditions, and equipment unblocking conditions. This is conducive to improving the comprehensiveness, integrity, rationality and progressiveness of the method for determining whether the conditions for smooth driving of the intelligent robot are met, and thus is conducive to improving the accuracy and reliability of the determined conditions for smooth driving, thereby helping to improve the accuracy and reliability of the subsequent execution of the first optimized driving path plan based on the conditions for smooth driving.

[0294] Embodiment 4

[0295] See also Figure 5 , Figure 5 is a schematic diagram of the structure of another intelligent robot disclosed in an embodiment of the present invention. Figure 5 The described intelligent robot includes a body and a corresponding control device, and the control device may include a server, wherein the server includes a local server or a cloud server, which is not limited in the embodiment of the present invention. Figure 5 As shown, the control device may include:

[0296] A memory 401 storing executable program codes;

[0297] a processor 402 coupled to the memory 401;

[0298] Furthermore, it may also include an input interface 403 and an output interface 404 coupled to the processor 402;

[0299] The processor 402 calls the executable program code stored in the memory 401 to execute the steps of the intelligent robot control method applied to the hospital scenario described in the first or second embodiment.

[0300] Embodiment 5

[0301] An embodiment of the present invention discloses a computer storage medium storing a computer program for electronic data exchange, wherein the computer program enables a computer to execute the steps of the intelligent robot control method applied to a hospital scenario described in Embodiment 1 or Embodiment 2.

[0302] Embodiment 6

[0303] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps of the intelligent robot control method applied to a hospital scenario described in Embodiment 1 or Embodiment 2.

[0304] The device embodiments described above are only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0305] Through the specific description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution can be essentially or partly contributed to the prior art in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, a magnetic disk storage, a magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0306] Finally, it should be noted that the intelligent robot control method and intelligent robot applied to hospital scenarios disclosed in the embodiments of the present invention are only preferred embodiments of the present invention, which are only used to illustrate the technical solution of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments can still be modified, or some of the technical features therein can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent robot control method applied to hospital scenarios, characterized in that: The intelligent robot is used to access various information approval systems of the hospital, and the method includes: Determine the current expected process link and progress of the target file according to the process query information for the target file input by the user, and determine the current actual process link and progress of the target file; According to the current expected process link and progress, and the current actual process link and progress, judging whether the intelligent robot meets the preset next link driving conditions; When it is determined that the intelligent robot meets the driving conditions of the next link, a driving path plan for the intelligent robot to transport the target file is determined according to the determined first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link; According to the driving path plan, controlling the intelligent robot to perform corresponding file transportation operations on the target file; The process query information of the target file includes one or more of the number of the target file, the applicant, keywords, other information that can determine the target file as a query object, and other information that can determine the required query content about the target file to be queried; Among them, the process links corresponding to the current expected process links and progress, and the current actual process links and progress all include one or more of the application approval link, the information submission link, the document stamping link and other document processing links.

2. The intelligent robot control method applied to hospital scenarios according to claim 1 is characterized in that: The method of determining a driving path plan for the intelligent robot to transport the target file according to the determined first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link includes: Determine a basic driving path plan of the intelligent robot according to the determined first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link; Determine relevant device information corresponding to the device placed in the hospital scene where the intelligent robot is located, and perform a corresponding first path optimization operation on the basic driving path plan according to the relevant device information to obtain a first optimized driving path plan; Determine relevant personnel information corresponding to relevant personnel in the hospital scene, and perform a corresponding second path optimization operation on the first optimized driving path plan according to the relevant personnel information to obtain a second optimized driving path plan; According to the second optimized driving path plan, a driving path plan for the intelligent robot to transport the target file is determined.

3. The intelligent robot control method applied to hospital scenarios according to claim 2 is characterized in that: The step of performing a corresponding first path optimization operation on the basic driving path plan according to the relevant device information to obtain a first optimized driving path plan includes: Determine, according to the basic driving path plan, a first driving area corresponding to the intelligent robot, and determine, according to the relevant equipment information, equipment placement information and equipment movement configuration information of regional equipment in the first driving area; According to the device placement information and the device movement configuration information, determining whether the intelligent robot meets the preset smooth driving conditions; When it is determined that the intelligent robot meets the smooth driving condition, the basic driving path plan is determined as the first optimized driving path plan; When it is determined that the intelligent robot does not meet the smooth driving conditions, the target blocking equipment that blocks the smooth driving of the intelligent robot is determined according to the regional channel space information of the first driving area, the equipment placement information and the driving requirement space information of the intelligent robot; a blocking response plan for the target blocking equipment is generated according to the equipment movement configuration information and the equipment placement information; and according to the blocking response plan, a corresponding route update operation is performed on the basic driving path plan to obtain a first optimized driving path plan.

4. The intelligent robot control method applied to hospital scenarios according to claim 2 is characterized in that: The step of performing a corresponding second path optimization operation on the first optimized driving path plan according to the relevant personnel information to obtain a second optimized driving path plan includes: Determine, according to the first optimized driving path plan, a second driving area corresponding to the intelligent robot, and determine, according to the relevant personnel information, the real-time personnel location and distribution information of the regional personnel in the second driving area, and the personnel responsible event information; According to the real-time personnel location and distribution information, the personnel in the area are divided into one or more personnel distribution groups, and the density of each of the personnel distribution groups is determined; According to the event information of the personnel in charge, determine the responsibility of the personnel in each area and the nature of the event operation, and analyze the degree of need for maintaining the position of the personnel in each area according to the responsibility of the personnel in each area and the nature of the event operation; Determine the required position change mode of each personnel in the area according to the personnel responsible event information; Determine the predicted avoidance efficiency of each of the distributed groups of personnel with respect to the intelligent robot according to the density of each of the distributed groups of personnel, the degree of position maintenance requirements of the personnel in each of the distributed groups of personnel, and the position change requirements; Determine the emergency priority of the personnel responsible event and the target file transportation event according to the personnel responsible event information, the determined file nature of the target file and the content of the communication event; According to the density of each of the personnel distribution groups, the predicted avoidance efficiency, and the emergency priority, a corresponding second path optimization operation is performed on the first optimized driving path plan to obtain a second optimized driving path plan; And, according to the density of each of the personnel distribution groups, the predicted avoidance efficiency, and the emergency priority, performing a corresponding second path optimization operation on the first optimized driving path plan to obtain a second optimized driving path plan, including: According to the density of each of the personnel distribution groups, the predicted avoidance efficiency, and the emergency priority, all of the personnel distribution groups are divided into a first personnel group that meets the preset robot active avoidance conditions and / or a second personnel group that meets the preset robot no-avoidance conditions; When all the personnel distribution groups include the first personnel group, determining the target driving section area where the intelligent robot needs to change its route according to the first personnel group; generating a first optimal detour plan for the intelligent robot for the target driving section area according to the target driving section area and the real-time personnel position and distribution information; performing corresponding route update operations on the first optimized driving path plan according to the first optimal detour plan to obtain a second optimized driving path plan; When all the population distribution groups do not include the first population group, the first optimized driving route plan is determined as the second optimized driving route plan.

5. The intelligent robot control method applied to hospital scenarios according to claim 3 is characterized in that: The generating a blocking response plan for the target blocking device according to the device movement configuration information and the device placement information includes: Determining the device movement property and device movement requirement of the target blocking device according to the device movement configuration information; According to the equipment movement properties and equipment movement execution requirements of the target blocking equipment, and the determined transportation travel priority characteristics corresponding to the intelligent robot and / or the target file, the target blocking equipment is divided into a first blocking equipment that meets a preset execution avoidance condition and / or a second blocking equipment that meets a preset non-execution avoidance condition; When the target blocking device includes the second blocking device, generating a second optimal detour route for the intelligent robot for the second blocking device according to the current placement position of the second blocking device; When the target blocking device includes the first blocking device, generating an optimal avoidance plan of the first blocking device for the intelligent robot according to the current placement position of the first blocking device and the first driving area; A blocking response plan for the target blocking device is determined according to the second optimal detour route and / or the optimal avoidance plan.

6. The intelligent robot control method applied to hospital scenarios according to any one of claims 1 to 5, characterized in that: After controlling the intelligent robot to perform a corresponding file transport operation on the target file according to the driving path plan, the method further includes: Collecting current position path information of the intelligent robot; Determine the position path deviation of the intelligent robot according to the current position path information and the driving path plan, and determine the current environmental complexity of the hospital scene according to the determined relevant equipment information and relevant personnel information of the hospital scene where the intelligent robot is located; According to the position path deviation and the current environmental complexity, determining whether the intelligent robot meets the preset driving abnormality condition; When it is determined that the intelligent robot meets the abnormal driving condition, a path deviation warning instruction corresponding to the intelligent robot is generated, and / or a corresponding driving path update operation is performed on the intelligent robot; And, judging whether the intelligent robot meets the preset driving abnormality condition according to the position path deviation and the current environmental complexity, includes: Determine the rationality of the deviation of the intelligent robot according to the position path deviation, the relevant equipment information and the relevant personnel information; According to the complexity of the current environment, determining a reasonableness threshold of the deviation of the intelligent robot for the hospital scene; Determine whether the deviation rationality is greater than or equal to a preset deviation rationality threshold; When it is determined that the deviation rationality is greater than or equal to the deviation rationality threshold, it is determined that the intelligent robot does not meet the preset abnormal driving condition; When it is determined that the deviation rationality is less than the deviation rationality threshold, it is determined that the intelligent robot meets the preset abnormal driving condition.

7. The intelligent robot control method applied to hospital scenarios according to claim 3 or 5, characterized in that: The step of judging whether the intelligent robot meets preset smooth driving conditions according to the device placement information and the device movement configuration information includes: According to the regional channel space information of the first driving area and the driving requirement space information of the intelligent robot, it is determined whether the first driving area meets the preset basic space feasibility conditions; When it is determined that the first driving area meets the basic space feasibility condition, judging whether the first driving area meets a preset no-equipment-blocking condition according to the equipment placement information; When it is determined that the first driving-related area meets the no-equipment-blocking condition, determining that the intelligent robot meets a preset smooth driving condition; When it is determined that the first driving area does not meet the no-equipment-blocking condition, judging whether the first driving area meets a preset no-equipment-blocking condition according to the regional channel space information, the driving demand space information and the equipment placement information; When it is determined that the first driving-related area meets the condition that the device is not blocked, determining that the intelligent robot meets the preset smooth driving condition; When it is determined that the first driving-related area does not satisfy the equipment unblocked condition, it is determined that the intelligent robot does not satisfy the preset smooth driving condition.

8. An intelligent robot, characterized in that: The intelligent robot includes a main body and a corresponding control device. The intelligent robot is used to access various information approval systems of the hospital. The control device includes: The link and progress determination module is used to determine the current expected process link and progress of the target file according to the process query information for the target file input by the user, and determine the current actual process link and progress of the target file; A judgment module, used to judge whether the intelligent robot meets the preset next link driving conditions according to the current expected process link and progress and the current actual process link and progress; A path plan determination module is used to determine the driving path plan of the intelligent robot to transport the target file according to the first current position information of the target file, the second current position information of the intelligent robot, and the position information of the next link when the judgment module determines that the intelligent robot meets the driving conditions of the next link; A file transport execution module, used to control the intelligent robot to perform corresponding file transport operations on the target file according to the driving path plan; The process query information of the target file includes one or more of the number of the target file, the applicant, keywords, other information that can determine the target file as a query object, and other information that can determine the required query content about the target file to be queried; Among them, the process links corresponding to the current expected process links and progress, and the current actual process links and progress all include one or more of the application approval link, the information submission link, the document stamping link and other document processing links.

9. An intelligent robot, characterized in that: The intelligent robot comprises a body and a corresponding control device, wherein the control device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the intelligent robot control method applied to hospital scenarios as described in any one of claims 1-7.

10. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, which, when called, are used to execute the intelligent robot control method applied to hospital scenarios as described in any one of claims 1-7.

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