阅读说明：本技术 用于多功能、模块化、自动化装置类机器人任务调度方法 (Task scheduling method for multifunctional, modularized and automatic device robot ) 是由 陈建军 于 2021-08-11 设计创作，主要内容包括：本发明公开了用于多功能、模块化、自动化装置类机器人任务调度方法,该方法包括以下步骤：机器人终端判断机器人是否满足自主巡检要求,若满足机器人则依据自身技能执行自主巡检,若不满足则执行人工安排任务；机器人终端利用机器人巡检产生的告警数据引导实施人员前往指定告警目标地点进行维修；机器人通过语音通话及全景播放功能向云平台实时传输实施人员的语音通话及视频画面；云平台利用机器人对实施人员维修后的机柜进行辅助维修验证,判断问题是否已解决。有益效果：实现了机器人辅助维修、随工巡检、随工维修及远程VR的功能,更大程度的接近了无休息、高产量、高强度的智能巡检,有效地保障并提高了机器人的实用价值。(The invention discloses a task scheduling method for a multifunctional, modularized and automatic device robot, which comprises the following steps: the robot terminal judges whether the robot meets the autonomous inspection requirement, if so, the robot executes autonomous inspection according to self skills, and if not, the robot executes manual arrangement tasks; the robot terminal guides an implementer to go to a designated warning target location for maintenance by using warning data generated by robot inspection; the robot transmits the voice call and the video picture of an implementer to the cloud platform in real time through the voice call and panoramic playing functions; the cloud platform utilizes the robot to carry out auxiliary maintenance verification on the cabinet maintained by the implementing personnel, and judges whether the problem is solved. Has the advantages that: the functions of auxiliary maintenance, follow-up inspection, follow-up maintenance and remote VR of the robot are realized, intelligent inspection without rest, high yield and high strength is achieved to a greater extent, and the practical value of the robot is effectively guaranteed and improved.)

1. A task scheduling method for a multifunctional, modular and automated device-like robot is characterized by comprising the following steps:

s1, the robot terminal judges whether the robot meets the autonomous inspection requirement, if so, the robot executes autonomous inspection according to self skills, and if not, the robot executes manual scheduling tasks;

s2, the robot terminal guides an implementer to go to a designated warning target location for maintenance by using warning data generated by robot inspection;

s3, the robot transmits the voice call and the video picture of an implementer to the cloud platform in real time through the voice call and panoramic playing function;

s4, the cloud platform utilizes the robot to perform auxiliary maintenance verification on the cabinet maintained by the implementer, and judges whether the problem is solved.

2. The method according to claim 1, wherein the autonomous patrol in S1 requires that the current electric quantity of the robot is greater than 50% and the cloud platform does not issue tasks within 1 hour.

3. The method for task scheduling of a multi-functional, modular, automated equipment-like robot of claim 1 wherein said robot' S own skills at S1 include but are not limited to machine room environmental security inspection, cabinet intelligent identification alarm, machine room inventory assets, inventory free cabinets, generation of simulation maps and pdf data report.

4. The task scheduling method for a multi-functional, modular, automated device-like robot according to claim 3, wherein said S1 robot performing autonomous patrol according to its own skills comprises the following steps:

the robot terminal sequentially generates an inventory task, a patrol task and an environment detection task through a built-in task management module;

the robot terminal guides tasks by using a built-in guiding module, and controls the robot to sequentially go to each cabinet in the machine room for inspection;

after the target cabinet point location is reached, the robot calls a built-in data acquisition module to acquire current cabinet data;

the robot carries out algorithm analysis and identification on the collected data through a built-in processor, and transmits an analysis and identification result to the robot terminal by utilizing the communication module.

5. The method for task scheduling of a multi-functional, modular, automated device-like robot according to claim 4, wherein said data acquisition module comprises a temperature sensor, a humidity sensor, a noise sensor, a pm2.5 sensor, an environmental pollution sensor and a thermal imaging sensor.

6. The method for task scheduling of a multi-functional, modular, automated device-like robot according to claim 1, wherein the step of the robot terminal guiding the operator to go to the designated warning target site for maintenance using the warning data generated by the robot inspection in S2 comprises the following steps:

s201, an implementer checks alarm data generated by robot inspection by using an alarm module of a robot terminal and clicks an abnormal cabinet in the alarm data;

s202, the robot terminal calls a built-in guiding module to generate a navigation route and controls the robot to move to the front of a corresponding cabinet;

and S203, the implementer moves to the appointed alarm target site along with the robot, and maintains the abnormal cabinet in the alarm data.

7. The method as claimed in claim 1, wherein the robot in S3 has a microphone for voice communication, a VR panoramic camera for live video and a mini depth camera for real-time monitoring of the moving position of the human skeleton.

8. The method as claimed in claim 7, wherein when the implementer needs remote technical support in troubleshooting the problem, the expert can communicate with the implementer remotely in real time through the LAN, the microphone and the VR panoramic camera on the cloud platform to realize real-time remote technical support in S3.

9. The method for task scheduling of a multi-functional, modular, automated device-like robot according to claim 7, wherein the step of transmitting the video frame of the implementer to the cloud platform in real time by the panorama play function of the robot at S3 further comprises the steps of:

the robot divides the human body into 20 joint points which are connected according to a certain sequence and can describe the human body skeleton according to a human body skeleton algorithm by using a mini depth camera;

recognizing the X-axis coordinate, the Y-axis coordinate and the Z-axis coordinate of the human body by using the mini depth camera, calculating the distance of left and right movement according to the change of the XY-axis coordinate, and converting the depth distance according to the data of the Z-axis;

the robot chassis is controlled to move front and back, left and right through the navigation api, the robot is friendly and smooth to move along with the human body by matching with the moving acceleration, and the human body is locked.

10. The method for task scheduling of a multi-functional, modular, automated device-like robot according to claim 1, wherein the step of performing auxiliary maintenance verification on the cabinet maintained by the service personnel by the cloud platform using the robot in S4 to determine whether the problem is solved comprises the following steps:

s401, the cloud platform control robot acquires current cabinet data through a built-in data acquisition module and performs algorithm analysis and identification by using a built-in processor;

s402, the robot terminal obtains an analysis and identification result by using the communication module, if data are abnormal, an alarm is generated, the problem is displayed to be not solved, and if the data are normal, the problem is displayed to be solved.

Technical Field

The invention relates to the technical field of robot scheduling, in particular to a task scheduling method for a multifunctional, modularized and automatic device robot.

Background

With the development of information technology, in recent years, no matter a chip, a framework, a system or software is greatly improved, new technologies such as a blade system, a multi-core technology, virtualization application, a cooling technology, intelligent management software and the like are in a wide range, and great impact is brought to the application and management of a traditional data center; on the other hand, the business model of the enterprise is greatly changed, and a new generation of data center is urgently needed to be built to adapt to the change.

The management system can effectively meet the requirements of a new generation of data center by using the daily inspection management system of the equipment through remote monitoring by network management software, however, the current daily inspection management system of the equipment has the following defects when in operation: due to the fact that the robot is in a follow-up mode, actual scene diversity, flexibility and changeability are high, the robot cannot be comprehensive, flexible and practical, and various scene requirements cannot be met.

An effective solution to the problems in the related art has not been proposed yet.

Disclosure of Invention

Aiming at the problems in the related art, the invention provides a task scheduling method for a multifunctional, modularized and automatic device robot, so as to overcome the technical problems in the prior related art.

Therefore, the invention adopts the following specific technical scheme:

a task scheduling method for a multifunctional, modular and automated device-like robot, the method comprising the steps of:

s1, the robot terminal judges whether the robot meets the autonomous inspection requirement, if so, the robot executes autonomous inspection according to self skills, and if not, the robot executes manual scheduling tasks;

s2, the robot terminal guides an implementer to go to a designated warning target location for maintenance by using warning data generated by robot inspection;

s3, the robot transmits the voice call and the video picture of an implementer to the cloud platform in real time through the voice call and panoramic playing function;

s4, the cloud platform utilizes the robot to perform auxiliary maintenance verification on the cabinet maintained by the implementer, and judges whether the problem is solved.

Further, the autonomous inspection in the S1 requires that the current electric quantity of the robot is greater than 50%, and the cloud platform does not issue the task within 1 hour.

Further, the self skills of the robot in S1 include, but are not limited to, machine room environment security detection, intelligent cabinet identification alarm, machine room inventory assets, inventory idle cabinets, generation of simulation map, and pdf data report.

Further, the step of executing the autonomous inspection by the robot according to the skill of the robot in S1 specifically includes the following steps:

the robot terminal sequentially generates an inventory task, a patrol task and an environment detection task through a built-in task management module;

the robot terminal guides tasks by using a built-in guiding module, and controls the robot to sequentially go to each cabinet in the machine room for inspection;

after the target cabinet point location is reached, the robot calls a built-in data acquisition module to acquire current cabinet data;

the robot carries out algorithm analysis and identification on the collected data through a built-in processor, and transmits an analysis and identification result to the robot terminal by utilizing the communication module.

Further, the data acquisition module comprises a temperature sensor, a humidity sensor, a noise sensor, a pm2.5 sensor, an environmental pollution sensor and a thermal imaging sensor.

Further, the step of guiding an implementer to go to a designated warning target location for maintenance by the robot terminal using the warning data generated by the robot inspection in S2 specifically includes the steps of:

s201, an implementer checks alarm data generated by robot inspection by using an alarm module of a robot terminal and clicks an abnormal cabinet in the alarm data;

s202, the robot terminal calls a built-in guiding module to generate a navigation route and controls the robot to move to the front of a corresponding cabinet;

and S203, the implementer moves to the appointed alarm target site along with the robot, and maintains the abnormal cabinet in the alarm data.

Further, install the microphone that is used for voice conversation, be used for live VR panorama camera of video and be used for the mini degree of depth camera of real-time supervision human skeleton shift position on the robot among S3.

Further, in S3, when the implementer needs remote technical support in troubleshooting the difficult and complicated problems, the expert may communicate with the implementer remotely in real time through the local area network, the microphone, and the VR panoramic camera on the cloud platform, so as to implement real-time remote technical support.

Further, the step of transmitting the video picture of the implementer to the cloud platform in real time by the robot through the panorama playing function in S3 further includes the steps of:

the robot divides the human body into 20 joint points which are connected according to a certain sequence and can describe the human body skeleton according to a human body skeleton algorithm by using a mini depth camera;

recognizing the X-axis coordinate, the Y-axis coordinate and the Z-axis coordinate of the human body by using the mini depth camera, calculating the distance of left and right movement according to the change of the XY-axis coordinate, and converting the depth distance according to the data of the Z-axis;

the robot chassis is controlled to move front and back, left and right through the navigation api, the robot is friendly and smooth to move along with the human body by matching with the moving acceleration, and the human body is locked.

Further, the step S4 in which the cloud platform performs auxiliary maintenance verification on the cabinet maintained by the implementer using the robot, and the step S of determining whether the problem is solved specifically includes:

s401, the cloud platform control robot acquires current cabinet data through a built-in data acquisition module and performs algorithm analysis and identification by using a built-in processor;

s402, the robot terminal obtains an analysis and identification result by using the communication module, if data are abnormal, an alarm is generated, the problem is displayed to be not solved, and if the data are normal, the problem is displayed to be solved.

The invention has the beneficial effects that: the invention adopts a depth camera module and a VR360 panoramic camera, and is matched with navigation, so that the following function of the robot is realized. Meanwhile, the automatic polling function of the robot is added, so that the robot can intelligently arrange and execute the equipment cabinet checking, the equipment cabinet polling and the machine room environment safety polling according to idle time and idle tasks, when artificial tasks and plans are generated, the robot leaves pause automatic polling, the intelligent polling without rest, high yield and high strength is realized to a greater extent, and the practical value of the robot is effectively ensured and improved. The invention realizes the functions of robot auxiliary maintenance, follow-up inspection, follow-up maintenance and remote VR.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.

FIG. 1 is a flow chart of a method for task scheduling for a multi-functional, modular, automated device-like robot in accordance with an embodiment of the present invention;

FIG. 2 is a schematic diagram of an interface of a robot terminal used in a multi-functional, modular, automated device-like robot task scheduling method according to an embodiment of the present invention;

FIG. 3 is a schematic diagram of an alarm used in a multi-functional, modular, automated device-like robot task scheduling method according to an embodiment of the present invention;

fig. 4 is a schematic diagram of a human body joint point used in a multifunctional, modular, automated device-like robot task scheduling method according to an embodiment of the present invention.

Detailed Description

For further explanation of the various embodiments, the drawings which form a part of the disclosure and which are incorporated in and constitute a part of this specification, illustrate embodiments and, together with the description, serve to explain the principles of operation of the embodiments, and to enable others of ordinary skill in the art to understand the various embodiments and advantages of the invention, and, by reference to these figures, reference is made to the accompanying drawings, which are not to scale and wherein like reference numerals generally refer to like elements.

According to an embodiment of the present invention, a method for task scheduling for a multi-functional, modular, automated device-like robot is provided.

The present invention will now be further described with reference to the accompanying drawings and specific embodiments, wherein as shown in fig. 1-4, a task scheduling method for a multi-functional, modular, automated device-like robot according to an embodiment of the present invention comprises the following steps:

s1, the robot terminal judges whether the robot meets the autonomous inspection requirement, if so, the robot executes autonomous inspection according to self skills, and if not, the robot executes manual scheduling tasks;

and in the S1, the autonomous inspection requirement is that the current electric quantity of the robot is more than 50%, and the cloud platform does not issue tasks within 1 hour.

The skills of the robot in S1 include, but are not limited to, machine room environment security detection, intelligent cabinet identification alarm, machine room inventory assets, inventory idle cabinets, generation of simulation maps, and pdf data report.

The method for executing the autonomous inspection by the robot in the S1 comprises the following specific steps of:

the robot terminal sequentially generates an inventory task, a patrol task and an environment detection task through a built-in task management module;

the robot terminal guides tasks by using a built-in guiding module, and controls the robot to sequentially go to each cabinet in the machine room for inspection;

after the target cabinet point location is reached, the robot calls a built-in data acquisition module to acquire current cabinet data;

specifically, the data acquisition module comprises a temperature sensor, a humidity sensor, a noise sensor, a pm2.5 sensor, an environmental pollution sensor and a thermal imaging sensor.

The robot carries out algorithm analysis and identification on the collected data through a built-in processor, and transmits an analysis and identification result to the robot terminal by utilizing the communication module.

In addition, the robot terminal obtains the analysis and identification result, displays an alarm list through an alarm module and records the inspection result.

S2, the robot terminal guides an implementer to go to a designated warning target location for maintenance by using warning data generated by robot inspection;

the step of S2, in which the robot terminal guides an implementer to go to a designated warning target location for maintenance by using warning data generated by robot inspection, includes the following steps:

s201, an implementer checks alarm data generated by robot inspection by using an alarm module of a robot terminal and clicks an abnormal cabinet in the alarm data;

s202, the robot terminal calls a built-in guiding module to generate a navigation route and controls the robot to move to the front of a corresponding cabinet;

and S203, the implementer moves to the appointed alarm target site along with the robot, and maintains the abnormal cabinet in the alarm data.

S3, the robot transmits the voice call and the video picture of an implementer to the cloud platform in real time through the voice call and panoramic playing function;

wherein, install the microphone that is used for voice conversation, be used for live VR panoramic camera of video and be used for the mini degree of depth camera of real-time supervision human skeleton shift position on the robot among S3.

In the step S3, when the implementer needs remote technical support in troubleshooting, the expert may communicate with the implementer remotely in real time through the local area network, the microphone, and the VR panoramic camera on the cloud platform, so as to implement real-time remote technical support.

Specifically, the cloud platform can check the scene on site through the VR panoramic camera. The technology is realized by adopting a local area network, and voice and rtmp streams are transmitted in real time through a socket, so that voice call and video picture transmission are realized.

The step of transmitting the video picture of the implementer to the cloud platform in real time by the robot through the panorama playing function in the step S3 further includes the steps of:

the robot divides the human body into 20 joint points which are connected according to a certain sequence and can describe the human body skeleton according to a human body skeleton algorithm by using a mini depth camera;

recognizing the X-axis coordinate, the Y-axis coordinate and the Z-axis coordinate of the human body by using the mini depth camera, calculating the distance of left and right movement according to the change of the XY-axis coordinate, and converting the depth distance according to the data of the Z-axis;

the robot chassis is controlled to move front and back, left and right through the navigation api, the robot is friendly and smooth to move along with a human body by matching with movement acceleration, and the human body is locked (the human body is locked through utraId, so that mistaken identification is prevented, and mistaken following is caused).

S4, the cloud platform utilizes the robot to perform auxiliary maintenance verification on the cabinet maintained by the implementer, and judges whether the problem is solved.

Wherein, the cloud platform utilizes the robot to carry out supplementary maintenance verification to the rack after implementing personnel' S maintenance in S4, and whether the judgement problem has been solved specifically includes the following steps:

s401, the cloud platform control robot acquires current cabinet data through a built-in data acquisition module and performs algorithm analysis and identification by using a built-in processor;

s402, the robot terminal obtains an analysis and identification result by using the communication module, if data are abnormal, an alarm is generated, the problem is displayed to be not solved, and if the data are normal, the problem is displayed to be solved.

For convenience of understanding the above technical solutions of the present invention, the following detailed description is made of application scenarios of the present invention in an actual process.

1) The robot can help guide the implementing personnel to reach the designated cabinet, and has a maintenance mark list and an alarm list, and for a large amount of data, the high position of the cabinet is more clearly indicated, the abnormal state is shown in the number of lamps, the water stain is detected on the floor, and the abnormal signal is shown. More directly perceived, more accurate.

2) The implementation personnel, field maintenance, some abnormity need field verification, whether the problem is solved or not, and whether the data is normal or not. The robot provides various sensors and efficient algorithms, identification and support are achieved, investigation is convenient, verification is convenient and rapid, and problems are solved.

3) The implementation personnel, some difficult problems of investigation need remote support, and the robot provides long-range pronunciation, live broadcast, VR function, makes things convenient for the long-range problem of solving of expert.

4) The robot follows the function, uses the degree of depth camera, and real time monitoring human skeleton shift position calls navigation api simultaneously and advances, backs, turns left, turns right. The following effect is achieved.

5) Autonomous inspection: and (5) building an intelligent management system for the robot. The robot checks assets in the machine room, checks idle cabinets, generates a simulation map, pdf data report forms and the like according to the skills (machine room environment safety detection, cabinet intelligent identification alarm, machine room checking assets, checking idle cabinets, and generates a manual operation, a manual task or a plan) of the robot, if the robot does not generate manual operation in the current period of time. The robot autonomously schedules the free time. And comprehensively checking the machine room and the machine cabinet, sequentially executing own skills and generating final report data. The spare time yield is greatly improved.

In summary, according to the technical scheme of the invention, the robot following function is realized by adopting the depth camera module and the VR360 panoramic camera and matching with navigation. Meanwhile, the automatic polling function of the robot is added, so that the robot can intelligently arrange and execute the equipment cabinet checking, the equipment cabinet polling and the machine room environment safety polling according to idle time and idle tasks, when artificial tasks and plans are generated, the robot leaves pause automatic polling, the intelligent polling without rest, high yield and high strength is realized to a greater extent, and the practical value of the robot is effectively ensured and improved. The invention realizes the functions of robot auxiliary maintenance, follow-up inspection, follow-up maintenance and remote VR.

The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.