Artificial intelligence robot control system based on big data algorithm analysis

Abstract

The invention relates to the technical field of robot control, in particular to an artificial intelligence robot control system based on big data algorithm analysis. Comprising a processor unit, a controller unit, an actuator unit, an intelligent sensing module, a data acquisition and transfer module, a communication gateway module, a power management unit and a cloud service unit, wherein the processor unit is used for analyzing and processing big data and centrally managing and controlling the operation process of the robot; a master controller in the controller unit receives tasks firstly, then the master controller distributes the tasks downwards, and a slave controller is used for receiving task information and downloading instructions; the actuator unit is used for executing actions; and the cloud service unit is used for managing and storing the data. According to the design, a one-to-one mode can be adopted, one slave controller can also be called to control the control operation of part of or all actuators, the requirement for the controllers is effectively lowered, and the execution response speed of the robot is increased; data are stored and calculated through cloud service, the working pressure of a processor is relieved, the calculation speed is increased, execution instruction chaos is avoided, and the operation precision of the artificial intelligence robot is improved.

Description

Technical Field

[0001] The present invention relates to the field of robot control technology, and in particular to an artificial intelligence robot control system based on big data algorithm analysis. Background Art

[0002] The continuous development of artificial intelligence has greatly promoted the development of robots. With the rapid development of science and technology, people's lives and work are becoming more and more automated and intelligent. At the same time, with the continuous increase in labor costs, more and more robots have appeared in various fields such as industrial manufacturing, medical treatment, entertainment services, military, aerospace, etc., and more and more service positions will be replaced by service robots.

[0003] However, no matter how advanced the artificial intelligence technology is, the basis of the operation of artificial intelligence robots still cannot be separated from control. During the operation of many robots, more than one actuator is often used. If the actions of multiple actuators are controlled by a single processor / controller, the computing power of the processor is required to be high, and the accuracy of the controller is also required to be higher. There will still be problems such as deviation in execution action, slow execution response speed, and even confusion of instructions. At the same time, during the operation of artificial intelligence robots, a large amount of feedback information needs to be collected. The processor needs to determine the effect of the execution action based on the processing and analysis of a large amount of data and make timely adjustments and revisions. However, processing and analyzing massive amounts of data will also cause great work pressure on the processor. However, there is no control system for artificial intelligence robots in the prior art that can effectively solve the above problems. The following are the main problems faced: Coordinated control of multiple actuators: When a robot has multiple actuators, it is a major challenge to coordinate the actions of these actuators efficiently and accurately. A single processor processing multiple actuators may lead to excessive computational burden, which in turn affects the reaction speed and execution accuracy.

[0004] Data collection and processing: When robots perform tasks, they need to collect a large amount of feedback information in real time. How to effectively process this data to ensure timely adjustment and optimization of execution actions is a technical challenge.

[0005] Precision and speed of execution: In complex environments, the actuator may deviate due to environmental changes, resulting in less than expected execution results. Therefore, higher requirements are placed on the precision and response speed of the control system.

[0006] In view of this, we proposed an artificial intelligence robot control system based on big data algorithm analysis. Summary of the invention

[0007] One of the purposes of the present invention is to provide an artificial intelligence robot control system based on big data algorithm analysis to solve the problems raised in the above-mentioned background technology.

[0008] In order to solve the above technical problems, one of the purposes of the present invention is to provide an artificial intelligence robot control system based on big data algorithm analysis, including a processor unit, a controller unit, an actuator unit, an intelligent sensor module, a data acquisition and transfer module and a cloud service unit; the processor unit, the controller unit, the actuator unit, the intelligent sensor module, the data acquisition and transfer module and the cloud service unit are connected in sequence through network communication; wherein: The processor unit is used to analyze the massive big data obtained from the cloud service unit based on a verified and trusted computer device using a variety of big data algorithms, so as to centrally control the operation process of the artificial intelligence robot; the following key parts can be realized:

[0009] Data source: The processor unit is connected to the cloud service unit (6) through the network to obtain real-time big data from multiple dimensions such as different sensors, user behaviors, and market trends.

[0010] Data cleaning: Before analysis, the acquired data is preprocessed, including removing noise, filling missing values, standardizing data formats, etc., to ensure the quality and consistency of the data.

[0011] Algorithm selection: According to specific application requirements, select appropriate machine learning or deep learning algorithms, such as regression analysis, classification algorithm, cluster analysis, etc.

[0012] Model training: Use historical data to train the selected algorithm to build an accurate prediction model. Cross-validation is performed during the training process to ensure the generalization ability of the model.

[0013] Real-time data stream processing: The processor unit has real-time data processing capabilities and can analyze data the moment it arrives in order to quickly respond to changes in the external environment.

[0014] Decision support system: Based on the analysis results, it provides intelligent decision support to help managers centrally control the operation process of artificial intelligence robots. This includes optimizing resource allocation, adjusting work strategies, predicting equipment failures, etc.

[0015] Trusted computing environment: Ensure that the computing devices used are strictly verified and adopt a combination of hardware and software security measures to protect the privacy and integrity of data.

[0016] Data encryption and access control: Encryption technology is used during data transmission and storage to ensure that only authorized users can access sensitive data.

[0017] Centralized control platform: Through the processor unit, a centralized management platform is established to monitor and adjust the operating status of multiple artificial intelligence robots in real time.

[0018] Feedback mechanism: Collect feedback information from the robot during task execution and analyze it to continuously optimize algorithms and operating procedures to improve the efficiency and accuracy of the robot's work.

[0019] The controller unit is used to receive task information from the processor unit and transmit task instructions to the executor unit, including a master controller and several slave controllers; it can be divided into two parts: Main Controller: Responsible for the overall task management and scheduling.

[0020] Receive task information from the processor unit, including task priority, type, and execution time.

[0021] Analyze, prioritize, and assign tasks into manageable subtasks.

[0022] Send the task instructions to the corresponding slave controller.

[0023] From the controller: Each slave controller is responsible for a specific type of task or is associated with a specific action execution mechanism.

[0024] Receive task instructions issued by the main controller, and further process and forward the instructions.

[0025] It is possible to implement local decision-making, be responsible for monitoring the status of the actuators it manages, and feed back the execution results to the main controller.

[0026] The actuator unit is used to execute corresponding actions according to the task instructions from the controller unit; the actuator unit includes a plurality of action execution mechanisms; the action execution mechanisms are connected to the corresponding slave controllers in communication, or all the action execution mechanisms are connected to each slave controller in communication at the same time, and its functions include: Action execution mechanism: Perform corresponding physical actions according to the task instructions received from the controller, such as movement, switching, adjustment, etc.

[0027] The actuator can be a motor, hydraulic cylinder, servo, etc., depending on the task to be achieved.

[0028] Each action execution mechanism establishes a communication connection with its corresponding slave controller to ensure that the instructions can be transmitted in time.

[0029] The intelligent sensing module is used to monitor the execution status of each actuator in real time during the operation of the actuator unit, collect corresponding status parameters and report them; this module is usually composed of multiple sensors and can collect various status parameters of the actuator, such as position, speed, temperature, pressure, etc.

[0030] Real-time monitoring: Sensors are used to continuously monitor the actuator’s operating status to ensure that any changes or abnormalities are captured in a timely manner.

[0031] Data acquisition: Periodically or on demand, status parameters are collected. These parameters can be digital signals (such as voltage, frequency) or analog signals (such as temperature, pressure).

[0032] Data reporting: Upload the collected data to the data set transfer module via wireless or wired network. This process may involve data preprocessing, such as filtering noise and data compression, to improve transmission efficiency.

[0033] The data acquisition and transfer module is used to collect data from the intelligent sensor module and transfer and upload it to the cloud; it is the key node for data flow in the entire system.

[0034] Data aggregation: Collect data from multiple smart sensor modules to ensure that the status information of all actuators can be recorded in a timely manner.

[0035] Data processing: Perform preliminary processing on the received data, such as format conversion, deduplication and error detection, to ensure data quality.

[0036] Data forwarding: Upload the processed data to the cloud service unit. Usually supports multiple communication protocols (such as HTTP, MQTT, etc.) to adapt to different network environments and requirements.

[0037] The cloud service unit is used to manage and store massive amounts of data through the powerful computing power and storage space of the cloud server, providing flexibility and scalability for the entire system.

[0038] Data storage: Use a distributed database or object storage service to store data from the data collection and transfer module securely and reliably in the cloud.

[0039] Data management: Provides data retrieval, classification, indexing and other functions to ensure that users can easily access and analyze stored data.

[0040] Data analysis: Through data analysis tools and machine learning algorithms, the collected data is deeply analyzed to extract valuable information. For example, the failure mode of the actuator can be identified and the operating parameters can be optimized.

[0041] Visual display: Provides a user-friendly interface and supports visual display of data, allowing users to intuitively understand the operating status and trends of the actuator.

[0042] As a further improvement of the present technical solution, the processor unit includes a big data algorithm, an analysis and processing module and a centralized control module; the big data algorithm, the analysis and processing module and the centralized control module are connected in sequence through network communication; wherein: The big data algorithm is used to load various big data structures and algorithms, and is used to process and analyze massive amounts of data in order to quickly and accurately extract the most valuable data required; this module is the core of the processor unit, and its main functions include: Data loading: supports the loading and management of various big data structures (such as structured data, semi-structured data and unstructured data), and can obtain data from various data sources (such as databases, cloud storage, sensor networks, etc.).

[0043] Algorithm support: It integrates a variety of big data processing algorithms, such as machine learning, deep learning, and data mining algorithms, and can select the most appropriate algorithm for data analysis according to different business needs.

[0044] Data preprocessing: including data cleaning, normalization, feature selection and other steps to improve the accuracy and efficiency of subsequent analysis.

[0045] Real-time processing: Supports the processing of real-time data streams through stream processing frameworks (such as Apache Kafka, Apache Storm, etc.), ensuring that instant analysis can be performed at the moment the data is generated.

[0046] The analysis and processing module is used to call the corresponding analysis algorithm to perform statistics and analysis on the extracted optimal data so as to apply it to the control process of the artificial intelligence robot; after data extraction and cleaning, the module is responsible for in-depth analysis of the optimal data. The specific functions include: Statistical Analysis: Descriptive and inferential statistical analysis were performed on the extracted data using statistical methods to identify trends and patterns in the data.

[0047] Algorithm call: Call the corresponding analysis algorithm (such as regression analysis, cluster analysis, classification algorithm, etc.) according to different application scenarios to extract deeper insights.

[0048] Result visualization: Visualize the analysis results in the form of charts or dashboards to help operators quickly understand the meaning of the data and make decisions.

[0049] Feedback mechanism: By feeding back the analysis results to the big data algorithm module, data processing and algorithm selection are optimized to achieve closed-loop feedback.

[0050] The centralized control module is used to centrally manage and control the operation process of the artificial intelligence robot based on the analyzed and processed data. Functions include: Operation monitoring: Real-time monitoring of the robot status and operation data, including location information, task execution status, fault alarms, etc., to ensure the safety and reliability of the robot during operation.

[0051] Decision support: Based on the results of the analysis and processing module, it provides decision support functions to help operators formulate optimal operation strategies and adjust robot behavior.

[0052] Task scheduling: Dynamically adjust and optimize the robot's task execution order based on real-time data and preset algorithms to improve work efficiency and resource utilization.

[0053] Data storage and management: Responsible for storing and managing historical data and analysis results, supporting subsequent data mining and machine learning, and promoting continuous optimization of the system.

[0054] As a further improvement of the technical solution, the big data algorithms include but are not limited to: Bloom Filter, Hash, Bit-Map, Heap, double-layer bucket partitioning, database optimization method, inverted index, external sorting, Trie tree, distributed processing MapReduce, etc.; among which:

[0055] It is used to quickly check whether an element is in a set. It is a space-efficient data structure but may produce false positives (i.e. it may return "exist" but actually does not exist).

[0056] Network routing, caching systems, database systems, etc. are particularly suitable for element detection in large-scale data sets.

[0057] Used to quickly find elements, detect modifications to data objects, and analyze massive log data. Fast retrieval can be achieved by mapping input data to fixed-size values.

[0058] Database indexing, password storage, caching, data deduplication, etc.

[0059] Used to determine whether an element exists in a set, or to detect duplication. Each element corresponds to a bit, 1 means it exists, and 0 means it does not exist.

[0060] Data deduplication, permission management, quick search, etc.

[0061] A special complete binary tree structure is used to efficiently obtain the top n largest or smallest elements and the median in massive data.

[0062] Priority queues, scheduling algorithms, stream data processing, etc.

[0063] Used to find the kth largest, median, unique or repeated data in massive data. It effectively reduces the search space by bucketing.

[0064] Data analysis, statistical query, etc.

[0065] It includes strategies such as indexing, caching mechanism, data partitioning, table slicing, batch processing, replacing non-sequential access with sorting, and log analysis to improve database performance.

[0066] Large-scale application systems, online trading systems, etc.

[0067] As the basic structure of the search engine, it stores the location mapping of a word in a document or a group of documents, supporting efficient full-text search.

[0068] Search engines, information retrieval systems, etc.

[0069] Used to sort and remove duplicates from large data sets. Data is usually split into multiple small blocks, sorted in memory, and then merged.

[0070] Sorting large data sets, log processing, data warehousing, etc.

[0071] An efficient string storage and retrieval structure that supports string search, statistics, sorting, and prefix matching.

[0072] Autocompletion, spell checking, dictionary implementation, etc.

[0073] A distributed programming model for large-scale data processing that simplifies the parallel computing process through two stages: "map" and "reduce".

[0074] Big data analysis, log processing, data mining, etc.

[0075] As a further improvement of the present technical solution, several of the slave controllers are simultaneously connected to the master controller by signal; the master controller is used to receive task information from the processor unit, and schedule and manage the operation process of each slave controller according to application requirements; the slave controllers are used to control the corresponding action execution mechanisms or all the action execution mechanisms to execute corresponding action instructions according to the control instructions of the processor unit and / or the master controller.

[0076] As a further improvement of the present technical solution, the plurality of action execution mechanisms are used to respectively execute corresponding command actions according to the task instructions issued by the corresponding slave controller or the superior slave controller assigned by the system.

[0077] As a further improvement of the technical solution, the intelligent sensing module includes an image acquisition submodule, a state monitoring submodule, a touch sensing submodule and an action feedback submodule; the image acquisition submodule, the state monitoring submodule, the touch sensing submodule and the action feedback submodule are sequentially connected through network communication and run in parallel; wherein: The image acquisition submodule is used to collect graphic image data during the execution of the task action of the artificial intelligence robot through a sensor device with a camera function; these data may include key frames in the execution process, the status of the target object, environmental changes and other information.

[0078] accomplish: Hardware composition: includes high-resolution camera, light source (such as LED light) and image processing chip.

[0079] Data transmission: Image data is transmitted to the central processing unit in real time via a high-speed network interface (such as Wi-Fi or Ethernet) to facilitate subsequent analysis and decision-making.

[0080] The state monitoring submodule is used to collect state parameters of the artificial intelligence robot during operation through a variety of state monitoring sensors to monitor its working state; accomplish: Sensor network: includes a variety of status monitoring sensors to obtain the robot's motion status, load conditions and changes in the working environment in real time.

[0081] Data analysis: These parameters can help the system determine whether the robot is operating within a safe range and identify potential failures or abnormal situations.

[0082] The touch sensing submodule is used to obtain a signal of whether the actuator touches the object to be executed during the execution of the action through the touch sensing sensor; accomplish: Touch sensor: Uses capacitive or pressure sensors to detect touch events. When an object is touched, the sensor sends a signal to the processor.

[0083] Signal processing: Touch signals are not only used for real-time feedback, but can also be combined with image data to determine the accuracy of the action.

[0084] The action feedback submodule is used to feed back to the system processor a signal indicating whether the execution action of the actuator is accurate or not.

[0085] accomplish: Feedback mechanism: A motion sensor (such as an encoder) or a vision system is used to detect the deviation between the actuator’s final position and the desired target.

[0086] Data integration: Combine the data from the touch sensing submodule and the status monitoring submodule to generate a comprehensive execution report to facilitate system adjustment of subsequent actions or troubleshooting.

[0087] As a further improvement of the present technical solution, the cloud service unit includes a data management module and a cloud-based big database; the data management module is communicatively connected to the cloud-based big database; wherein: the data management module is used to obtain data related to the artificial intelligence robot from an external third-party platform and collected and uploaded through a data collection and transfer module, to process and manage massive amounts of data and store the processed data in the cloud-based big database.

[0088] As a further improvement of the technical solution, the data management module includes a verification and cleaning module, a data integration module and a storage backup module; the verification and cleaning module, the data integration module and the storage backup module are connected in sequence through network communication; wherein: The verification and cleaning module is used to verify the authenticity and timeliness of a large amount of data, and remove invalid and duplicate data through cleaning;

[0089] Authenticity verification: This module first performs authenticity checks on the input data to ensure that the data source is reliable. Various algorithms and techniques can be used, such as data source verification, signature verification, etc.

[0090] Timeliness verification: Check the timestamp of the data to ensure that the data is up to date and meets the real-time requirements.

[0091] Data cleaning: Improve data quality by removing invalid data (such as null values, malformed data) and duplicate data (using algorithms to detect similarities).

[0092] The data integration module is used to summarize and organize massive amounts of data and classify and summarize the data according to certain rules;

[0093] Data aggregation: This module aggregates massive data from different sources to form a unified data view.

[0094] Classification and induction: Classify and summarize data according to preset rules (such as data type, source, time period, etc.) to facilitate subsequent analysis.

[0095] The storage backup module is used to distribute and store massive amounts of data in a large cloud database and to regularly back up important data.

[0096] Distributed storage: The processed massive data is distributed and stored in a large cloud database to ensure the scalability and high availability of data.

[0097] Regular backup: Set up scheduled tasks to regularly back up important data to prevent data loss. Backup data can be stored in different areas to enhance security.

[0098] As a further improvement of the technical solution, it also includes a communication gateway module, which is used to integrate multiple communication technologies through a wireless sensor network gateway with multiple communication modes, so as to provide signal connection and data transmission channels between various levels of the system, and can automatically select and switch corresponding communication technologies according to the communication environment and signal strength; the communication gateway module includes a mobile communication sub-module, a wireless WiFi sub-module and a ZigBee sub-module; the mobile communication sub-module, the wireless WiFi sub-module and the ZigBee sub-module operate in parallel.

[0099] As a further improvement of the present technical solution, it also includes a power management unit, which is electrically connected to an external power supply system through a power line. The power management unit is respectively connected to the processor unit, the controller unit, the actuator unit, the intelligent sensor module, the data acquisition and transfer module and the communication gateway module through signal lines, so as to manage the energy supply of each unit / module in the distribution system.

[0100] Connection method: The power management unit is connected to the external power supply system through a power line to ensure the stable operation of the entire system. It is connected to various modules in the system (such as processor unit, controller unit, actuator unit, intelligent sensor module, data acquisition transfer module and communication gateway module) through signal lines to form a complete power management network.

[0101] Energy management: This unit is responsible for monitoring the power requirements of each module and allocating the corresponding energy according to the real-time status to ensure that each module operates in the best working state. This dynamic allocation can improve the energy efficiency and response speed of the system.

[0102] The second object of the present invention is to provide a computing and operating device for a control system, which can be installed in the processor unit and / or the cloud service unit, and includes a processor, a memory, and a computer program stored in the memory and running on the processor, and the processor is used to implement the above-mentioned artificial intelligence robot control system based on big data algorithm analysis when executing the computer program.

[0103] Hardware architecture: The device includes a processor, memory, and cloud service interface. The processor is responsible for executing computer programs stored in the memory, which implement artificial intelligence control systems based on big data algorithm analysis.

[0104] Software system: The running program uses big data technology to analyze and process the data collected by the system to achieve intelligent control of the robot. This control can not only improve the robot's reaction speed, but also optimize the robot's behavior pattern through data analysis.

[0105] The third object of the present invention is to provide a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, it implements the above-mentioned artificial intelligence robot control system based on big data algorithm analysis.

[0106] Storing computer programs: Computer-readable storage media is used to store program codes that, when executed by the processor, will implement the functions of the above control system. It ensures the reliability and scalability of the software and facilitates future upgrades and maintenance.

[0107] Data storage: The storage medium can also be used to store historical data and models, allowing the system to continuously learn and optimize.

[0108] Compared with the prior art, the present invention has the following beneficial effects: 1. The artificial intelligence robot control system based on big data algorithm analysis can use a one-to-one approach to control the actuators (ensuring the response speed and accuracy of each actuator in a specific task) by setting up a multi-layer master-slave controller design, or call one of the slave controllers to control some or all of the actuators according to system requirements, effectively reducing the requirements for the controller and improving the robot's execution response speed; 2. The AI ​​robot control system based on big data algorithm analysis uses the powerful computing power and sufficient storage space of cloud services to collect a large amount of feedback information in a timely manner, store and calculate massive amounts of data. Using the powerful computing power of cloud services, the system can process a large amount of feedback information in real time and perform complex data storage and calculations. This process reduces the workload of the local processor and avoids instruction confusion caused by insufficient computing resources. It reduces the workload of the processor, increases the computing speed, avoids instruction confusion of the actuator, makes instruction execution more accurate, and improves the operating accuracy of the AI ​​robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0109] Figure 1 is a device block diagram of the overall system in the present invention; Figure 2 It is one of the device block diagrams of the local system in the present invention; Figure 3 This is the second device block diagram of the local system in the present invention; Figure 4 This is the second device block diagram of the local system in the present invention; Figure 5 It is a schematic block diagram of the structure of an exemplary electronic computer product device in the present invention.

[0110] The meaning of each number in the figure is: 1. Processor unit; 11. Big data algorithm; 12. Analysis and processing module; 13. Centralized control module; 2. Controller unit; 21. Master controller; 22. Slave controller; 3. Actuator unit; 31. Action execution mechanism; 4. Intelligent sensing module; 41. Image acquisition submodule; 42. State monitoring submodule; 43. Touch sensing submodule; 44. Action feedback submodule; 5. Data collection and transfer module; 6. Cloud service unit; 61. Data management module; 611. Verification and cleaning module; 612. Data integration module; 613. Storage and backup module; 62. Cloud big database; 7. Communication gateway module; 71. Mobile communication submodule; 72. Wireless WiFi submodule; 73. ZigBee submodule; 8. Power management unit. DETAILED DESCRIPTION

[0111] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Example

[0112] like Figure 1-Figure 5 As shown, this embodiment provides an artificial intelligence robot control system based on big data algorithm analysis, including a processor unit 1, a controller unit 2, an actuator unit 3, an intelligent sensor module 4, a data acquisition and transfer module 5 and a cloud service unit 6; the processor unit 1, the controller unit 2, the actuator unit 3, the intelligent sensor module 4, the data acquisition and transfer module 5 and the cloud service unit 6 are connected in sequence through network communication; wherein: The processor unit 1 is used to analyze the massive amount of big data obtained from the cloud service unit 6 based on a verified and trusted computer device, using a variety of big data algorithms, so as to centrally control the operation process of the artificial intelligence robot; The controller unit 2 is used to receive task information from the processor unit 1 and transmit task instructions to the executor unit 3, including a master controller 21 and a plurality of slave controllers 22; The actuator unit 3 is used to execute corresponding actions according to the task instructions from the controller unit 2; the actuator unit 3 includes a plurality of action execution mechanisms 31; the action execution mechanisms 31 are connected to the corresponding slave controllers 22 in communication, or all the action execution mechanisms 31 are connected to each slave controller 22 in communication at the same time; The intelligent sensor module 4 is used to monitor the execution status of each actuator in real time during the operation of the actuator unit 3, collect corresponding status parameters and report them; The data collection and transfer module 5 is used to collect data from the intelligent sensor module 4 and transfer and upload it to the cloud; The cloud service unit 6 is used to manage and store massive amounts of data through the powerful computing power and storage space of the cloud server.

[0113] In this embodiment, the processor unit 1 includes a big data algorithm 11, an analysis and processing module 12 and a centralized control module 13; the big data algorithm 11, the analysis and processing module 12 and the centralized control module 13 are connected in sequence through network communication; wherein: The big data algorithm 11 is used to load various big data structures and algorithms, and is used to process and analyze massive amounts of data, so as to quickly and accurately extract the most valuable data required; The analysis and processing module 12 is used to call the corresponding analysis algorithm to perform statistics and analysis on the extracted optimal data so as to apply it to the control process of the artificial intelligence robot; The centralized control module 13 is used to centrally manage and control the operation process of the artificial intelligence robot based on the analyzed and processed data.

[0114] Specifically, the big data algorithms 11 include but are not limited to: Bloom Filter, Hash, Bit-Map, Heap, double-layer bucket partitioning, database optimization method, inverted index, external sorting, Trie tree, distributed processing MapReduce, etc.; among which: Bloom Filter can be used to retrieve whether an element is in a set; Hash can be used to find elements, detect modifications in data objects, and analyze massive log data; Bit-Map can be used to determine whether there are duplicates in a set or whether an element in a set exists; Heap can be used to obtain the top n largest or the top n smallest or the median in massive data; Double-layer bucket partitioning can be used to obtain the kth largest, median, non-repeating or repeated data in massive data; Database optimization methods are used to optimize databases, including indexing, caching mechanisms, data partitioning, table slicing, batch processing, replacing non-sequential access with sorting, log analysis, etc.; Inverted index, as the cornerstone of search engines, can be used to store the mapping of the storage location of a word in a document or a group of documents under full-text search; External sorting can be used for sorting and deduplication of big data; Trie tree can be applied to string search, statistics, sorting, prefix matching, etc.; Distributed processing MapReduce, as one of the core technologies of cloud computing, is a distributed programming model that simplifies parallel computing and can be applied to data processing processes with large data volumes.

[0115] In this embodiment, several slave controllers 22 are simultaneously connected to the main controller 21 by signal; the main controller 21 is used to receive task information from the processor unit 1, and schedule and manage the operating process of each slave controller 22 according to application requirements; the slave controllers 22 are used to control the corresponding action execution agencies 31 or all action execution agencies 31 to execute corresponding action instructions according to the control instructions of the processor unit 1 and / or the main controller 21.

[0116] In this embodiment, a plurality of action execution mechanisms 31 are used to respectively execute corresponding command actions according to the task instructions issued by the corresponding slave controller 22 or the superior slave controller 22 assigned by the system.

[0117] Furthermore, the intelligent sensing module 4 includes an image acquisition submodule 41, a state monitoring submodule 42, a touch sensing submodule 43 and an action feedback submodule 44; the image acquisition submodule 41, the state monitoring submodule 42, the touch sensing submodule 43 and the action feedback submodule 44 are sequentially connected through network communication and run in parallel; wherein: The image acquisition submodule 41 is used to collect graphic image data of the artificial intelligence robot during the task execution process through a sensor device with a camera function; The state monitoring submodule 42 is used to collect state parameters of the artificial intelligence robot during operation through a variety of state monitoring sensors to monitor its working state; The touch sensing submodule 43 is used to obtain a signal of whether the actuator touches the executed object during the execution of the action through the touch sensing sensor; The action feedback submodule 44 is used to feed back to the system processor a signal indicating whether the execution action of the actuator is accurate or not.

[0118] In this embodiment, the cloud service unit 6 includes a data management module 61 and a cloud-based big data database 62; the data management module 61 is communicatively connected with the cloud-based big data database 62; wherein: the data management module 61 is used to obtain data related to the artificial intelligence robot from an external third-party platform and collected and uploaded through the data collection and transfer module 5, to process and manage massive amounts of data and store the processed data in the cloud-based big data database 62.

[0119] Furthermore, the data management module 61 includes a verification and cleaning module 611, a data integration module 612 and a storage backup module 613; the verification and cleaning module 611, the data integration module 612 and the storage backup module 613 are sequentially connected through network communication; wherein: The verification and cleaning module 611 is used to verify the authenticity and timeliness of a large amount of data, and remove invalid and duplicate data through cleaning; The data integration module 612 is used to summarize and organize the massive amount of data and classify and summarize the data according to certain rules; The storage backup module 613 is used to distribute and store massive amounts of data in the cloud big database 62 and to regularly back up important data.

[0120] In this embodiment, a communication gateway module 7 is also included. The communication gateway module 7 is used to integrate multiple communication technologies through a wireless sensor network gateway with multiple communication modes, so as to provide a channel for signal connection and data transmission between various levels of the system, and can automatically select and switch the corresponding communication technology according to the communication environment and signal strength; the communication gateway module 7 includes a mobile communication sub-module 71, a wireless WiFi sub-module 72 and a ZigBee sub-module 73; the mobile communication sub-module 71, the wireless WiFi sub-module 72 and the ZigBee sub-module 73 run in parallel.

[0121] In this embodiment, a power management unit 8 is also included. The power management unit 8 is electrically connected to the external power supply system through a power line. The power management unit 8 is signal-connected to the processor unit 1, the controller unit 2, the actuator unit 3, the intelligent sensor module 4, the data acquisition and transfer module 5 and the communication gateway module 7 through signal lines, respectively, for managing the energy supply of each unit / module in the distribution system.

[0122] like Figure 5 As shown, this embodiment also provides a computing operation device for a control system, which can be installed in the processor unit 1 and / or the cloud service unit 6, and includes a processor, a memory, and a computer program stored in the memory and running on the processor.

[0123] The processor includes one or more processing cores. The processor is connected to the memory through a bus. The memory is used to store program instructions. When the processor executes the program instructions in the memory, the above-mentioned artificial intelligence robot control system based on big data algorithm analysis is realized.

[0124] Optionally, the memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0125] In addition, the present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned artificial intelligence robot control system based on big data algorithm analysis.

[0126] Optionally, the present invention also provides a computer program product comprising instructions, which, when executed on a computer, enables the computer to execute the above-mentioned artificial intelligence robot control system based on big data algorithm analysis.

[0127] A person of ordinary skill in the art can understand that the process of implementing all or part of the steps of the above-mentioned embodiments can be completed by hardware or by instructing related hardware through a program. The program can be stored in a computer-readable storage medium. The above-mentioned storage medium can be a read-only memory, a disk or an optical disk, etc.

[0128] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An artificial intelligence robot control system based on big data algorithm analysis, characterized by: The system comprises a processor unit (1), a controller unit (2), an actuator unit (3), an intelligent sensor module (4), a data acquisition and transfer module (5), a cloud service unit (6), a communication gateway module (7) and a power management unit (8); the processor unit (1), the controller unit (2), the actuator unit (3), the intelligent sensor module (4), the data acquisition and transfer module (5) and the cloud service unit (6) are sequentially connected via network communication; wherein: The processor unit (1) is used to analyze and process the massive amount of big data obtained from the cloud service unit (6) based on a verified and trusted computer device, using a variety of big data algorithms, so as to centrally control the operation process of the artificial intelligence robot; The controller unit (2) is used to receive task information from the processor unit (1) and transmit task instructions to the actuator unit (3), and includes a main controller (21) and a plurality of slave controllers (22); The actuator unit (3) is used to execute corresponding actions according to the task instructions from the controller unit (2); the actuator unit (3) comprises a plurality of action execution mechanisms (31); the action execution mechanisms (31) are communicatively connected to their corresponding slave controllers (22), or all the action execution mechanisms (31) are communicatively connected to each slave controller (22) at the same time; The intelligent sensor module (4) is used to monitor the execution status of each actuator in real time during the operation of the actuator unit (3), collect corresponding status parameters and report them; The data collection and transfer module (5) is used to collect data from the intelligent sensor module (4) and transfer and upload it to the cloud; The cloud service unit (6) is used to manage and store massive amounts of data through the powerful computing power and storage space of the cloud server.

2. The artificial intelligence robot control system based on big data algorithm analysis according to claim 1 is characterized in that: The processor unit (1) comprises a big data algorithm (11), an analysis and processing module (12) and a centralized control module (13); the big data algorithm (11), the analysis and processing module (12) and the centralized control module (13) are sequentially connected via network communication; wherein: The big data algorithm (11) is used to load various big data structures and algorithms, and is used to process and analyze massive amounts of data, so as to quickly and accurately extract the most valuable data required; The analysis and processing module (12) is used to call the corresponding analysis algorithm to perform statistics and analysis on the extracted optimal data so as to apply it to the control process of the artificial intelligence robot; The centralized control module (13) is used to centrally manage and control the operation process of the artificial intelligence robot based on the analyzed and processed data.

3. The artificial intelligence robot control system based on big data algorithm analysis according to claim 2 is characterized in that: The big data algorithm (11) includes but is not limited to: Bloom Filter, Hash, Bit-Map, Heap, double-layer bucket partitioning, database optimization method, inverted index, external sorting, Trie tree, distributed processing MapReduce, etc.; among which: Bloom Filter can be used to retrieve whether an element is in a set; Hash can be used to find elements, detect modifications in data objects, and analyze massive log data; Bit-Map can be used to determine whether there are duplicates in a set or whether an element in a set exists; Heap can be used to obtain the top n largest or the top n smallest or the median in massive data; Double-layer bucket partitioning can be used to obtain the kth largest, median, non-repeating or repeated data in massive data; Database optimization methods are used to optimize databases, including indexing, caching mechanisms, data partitioning, table slicing, batch processing, replacing non-sequential access with sorting, log analysis, etc.; Inverted index, as the cornerstone of search engines, can be used to store the mapping of the storage location of a word in a document or a group of documents under full-text search; External sorting can be used for sorting and deduplication of big data; Trie tree can be applied to string search, statistics, sorting, prefix matching, etc.; Distributed processing MapReduce, as one of the core technologies of cloud computing, is a distributed programming model that simplifies parallel computing and can be applied to data processing processes with large data volumes.

4. The artificial intelligence robot control system based on big data algorithm analysis according to claim 1 is characterized in that: A plurality of slave controllers (22) are simultaneously connected to the master controller (21) by signal; the master controller (21) is used to receive task information from the processor unit (1) and to schedule and manage the operation process of each slave controller (22) according to application requirements; The slave controller (22) is used to control the corresponding action execution mechanism (31) or all the action execution mechanisms (31) to execute the corresponding action instructions according to the control instructions of the processor unit (1) and / or the master controller (21).

5. The artificial intelligence robot control system based on big data algorithm analysis according to claim 4 is characterized in that: The plurality of action execution mechanisms (31) are used to respectively execute corresponding command actions according to task instructions issued by the corresponding slave controller (22) or the superior slave controller (22) assigned by the system.

6. The artificial intelligence robot control system based on big data algorithm analysis according to claim 1 is characterized in that: The intelligent sensing module (4) comprises an image acquisition submodule (41), a state monitoring submodule (42), a touch sensing submodule (43) and an action feedback submodule (44); the image acquisition submodule (41), the state monitoring submodule (42), the touch sensing submodule (43) and the action feedback submodule (44) are sequentially connected via network communication and operate in parallel; wherein: The image acquisition submodule (41) is used to collect graphic image data during the process of the artificial intelligence robot performing a task action through a sensor device with a camera function; The state monitoring submodule (42) is used to collect state parameters of the artificial intelligence robot during operation through a variety of state monitoring sensors to monitor its working state; The touch sensing submodule (43) is used to obtain a signal of whether the actuator touches the executed object during the execution of the action through a touch sensing sensor; The action feedback submodule (44) is used to feed back to the system processor a signal indicating whether the execution action of the actuator is accurate or not.

7. The artificial intelligence robot control system based on big data algorithm analysis according to claim 1 is characterized in that: The cloud service unit (6) comprises a data management module (61) and a cloud-based big database (62); the data management module (61) is in communication connection with the cloud-based big database (62); wherein: the data management module (61) is used to obtain data related to the artificial intelligence robot from an external third-party platform and collected and uploaded by the data collection and transfer module (5), to process and manage massive amounts of data and to store the processed data in the cloud-based big database (62).

8. The artificial intelligence robot control system based on big data algorithm analysis according to claim 7 is characterized in that: The data management module (61) comprises a verification and cleaning module (611), a data integration module (612) and a storage backup module (613); the verification and cleaning module (611), the data integration module (612) and the storage backup module (613) are sequentially connected via network communication; wherein: The verification and cleaning module (611) is used to verify the authenticity and timeliness of a large amount of data, and remove invalid and duplicate data through cleaning; The data integration module (612) is used to summarize and organize the massive amount of data, and classify and summarize the data according to certain rules; The storage backup module (613) is used to distribute and store massive amounts of data in a cloud-based large database (62), and to regularly back up important data.

9. The artificial intelligence robot control system based on big data algorithm analysis according to claim 1 is characterized in that: The system further comprises a communication gateway module (7), wherein the communication gateway module (7) is used to integrate a plurality of communication technologies through a wireless sensor network gateway having a plurality of communication modes, so as to provide a channel for signal connection and data transmission between various levels of the system, and can automatically select and switch a corresponding communication technology according to the communication environment and signal strength. The communication gateway module (7) comprises a mobile communication submodule (71), a wireless WiFi submodule (72) and a ZigBee submodule (73); the mobile communication submodule (71), the wireless WiFi submodule (72) and the ZigBee submodule (73) operate in parallel.

10. The artificial intelligence robot control system based on big data algorithm analysis according to claim 9 is characterized in that: The system further comprises a power management unit (8), wherein the power management unit (8) is electrically connected to an external power supply system via a power line, and the power management unit (8) is signal-connected to the processor unit (1), the controller unit (2), the actuator unit (3), the intelligent sensor module (4), the data acquisition and transfer module (5) and the communication gateway module (7) via signal lines, respectively, for managing the energy supply of each unit / module in the distribution system.

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