22 results about "Robot software" patented technology

The invention relates to the technical field of safety protection, and discloses a system for realizing password resetting automation through an RPA technology, and the system comprises a demand analysis module which is used for analyzing and understanding an existing password resetting process, and determining the applicability and optimization point of application RPA; the flow design module is used for designing an automatic processing flow and rule and ensuring the safety and accuracy of the flow; the technology type selection module is used for selecting proper RPA robot software and engine and determining development and implementation schemes; the development environment building module is used for configuring a development environment and preparing software and hardware facilities required by development; through the developed RPA robot, preset automatic tasks can be continuously executed in an all-weather mode, the manual operation time is greatly shortened, and therefore the working efficiency is remarkably improved. By means of the automatic processing, a large amount of repeated and tedious work can be rapidly completed, and workers can concentrate on more valuable work.

A system and method of undoing capability intent actions of an artificial intelligence (AI) productivity tool chatbot software application comprising processing a received first user-query input and generating a query intent action, correlating a capability intent action with the user-query inputs by invoking an ML model algorithm to correlate the query intent value to a capability intent value for a capability to be executed by an AI productivity tool-enablable software application as a responsive capability intent action, initiating the capability intent action and identifying a negated intent that describes a reversing action that may be executed to reverse the capability intent action that is correlated to the first user query input, and generating a system state defining the state of the information handing system prior to the capability intent action being executed by the AI productivity tool-enablable software application.

The invention discloses a power transmission line track robot software and hardware system which comprises a hardware unit, a wireless communication module and a motor and battery distribution module, the hardware unit comprises a main control module, an image acquisition module, an image processor module, a wireless communication module and a motor and battery distribution module, and the output end of the image acquisition module is connected with the input end of the image processor module; the main control module is in data bidirectional connection with the image processor, and the main control module is connected with the motor and battery distribution module through a CAN bus and a driver; and the software unit comprises a FreeRTOS operating system, and the FreeRTOS operating system comprises an application layer, a board-level support package and a FreeRTOS layer. According to the invention, the arm part, the middle joint corner, the wrist part, the claw part and the hanging and buckling mechanical arm of the rail robot can be flexibly controlled, the complex motion mode is simplified, the task completion difficulty is reduced, through the cooperation of the software unit and the hardware unit, the automation degree is high, and the safety of an operator using the anti-falling guide rail when the operator goes up and down a tower is effectively ensured.

The invention provides a task processing method and a robot, the robot comprises a classifier, a task machine and a process state machine, the method comprises the following steps: the classifier determines whether a target task is a process task, if yes, task information corresponding to the target task is sent to the task machine, if not, a task type corresponding to the target task is determined, and the task type corresponding to the target task is sent to the task machine; and sending task information corresponding to the target task to a process state machine according to the task type. The task machine preprocesses the task information to enable the task information to meet task execution requirements corresponding to the process task, and then sends the task information to the process state machine; and after receiving the task information, the process state machine executes a task process corresponding to the target task. The target task is an intelligent agent task sent by a large language model corresponding to the robot, and the process task is a task comprising a plurality of different types of tasks. Therefore, the intelligent agent task can be better processed by the robot, the performance of the robot is improved, and the software development and maintenance cost of the robot is reduced.

The application discloses a robot skill primitive library automatic generation method and system based on a large language model, and relates to the fields of artificial intelligence and robot software engineering. The method comprises the following steps: adopting a double-level function extraction strategy to extract modular functions and process scripts in a robot code library from a robot task-level python file; based on the extracted robot function code, adopting a preset thinking chain prompt word to guide a large language model to generate global semantic description and to distinguish functions with the same name; based on the function metadata of the robot task level after the same name function is distinguished, adopting a preset thinking chain prompt word to guide the configured large language model to perform perception type code reconstruction with embedded field constraints; based on the reconstructed code, adopting a preset thinking chain prompt word to guide the configured large language model to perform adaptive iterative code evaluation and optimization closed loop to obtain a robot skill primitive library. The application can automatically and reliably generate a robot skill primitive library.

The invention relates to the technical field of robot software architecture and distributed systems, in particular to a data flow driven robot low-delay communication system and method. The system comprises a middleware scheduler, a sender computing node and a receiver computing node. And the middleware scheduler is used for loading a predefined data stream topology description file to declare all permitted communication paths, and performing admission verification on a data stream sending request according to the file. And the sender computing node is used for initiating a sending request and writing to-be-sent data into the shared memory area in a unified memory layout format after verification is passed. And the receiver computing node is used for registering a receiving intention and directly reading the written data in the shared memory area according to the indication of the middleware scheduler after the receiving intention passes the verification. According to the method, the defects of the existing open type robot middleware in the aspects of safety, real-time performance and resource utilization rate are systematically solved.

The invention relates to a humanoid robot OTA automatic upgrading method and system, and relates to the field of robot software maintenance, and the method comprises the steps: determining a target robot set based on robot state information; issuing batch upgrading tasks to the target robot set, and performing installation and upgrading by using a silent installation method; collecting the current battery electric quantity of the robot; if the current battery electric quantity is lower than the upgrading maintaining threshold value, determining a nearest target charging area according to the current robot position; an idle robot is determined based on the current robot position, the idle robot is controlled to carry the current robot to the target charging area for charging, and meanwhile the silent installation process is completed in the target charging area; and after the installation upgrade is completed, automatically running a self-checking program to verify the core function, and when an upgrade self-checking result accords with a preset self-checking requirement result, marking the upgraded version information as upgrade success and reporting the upgraded version information to the cloud management platform. The method has the effect of improving the upgrading efficiency of the robot.

The present application relates to a kind of humanoid robot OTA automatic upgrading method and system, it relates to the field of robot software maintenance, it includes: based on robot state information to determine target robot set;Batch upgrade task is issued to target robot set, and is installed and upgraded with silent installation method;Current battery capacity of robot is collected;If current battery capacity is lower than upgrade maintenance threshold, determine the nearest target charging area according to current robot position;Based on current robot position to determine idle robot, and control idle robot to carry current robot to target charging area and charge, while completing silent installation process in target charging area;After installation upgrade is completed, automatically run self-checking program to verify core function, when upgrade self-checking result meets the preset self-checking requirement result, mark the version information after upgrade as upgrade success and report to cloud management platform.The present application has the effect of improving the upgrading efficiency of robot.

1. The name of the design product: computer-based large model intelligent customer service robot software graphical user interface. 2. The use of the design product: for running programs. 3. The design points of the design product: the interface content of the graphical user interface in the screen. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: for the management and service of intelligent customer service robots. The front view is the initial interface of the software. Click the "Intelligent Q&A" button in the front view to enter the change state diagram 1. Click the "Add Robot" button in the change state diagram 1 to enter the change state diagram 2. Click the "Save" button in the change state diagram 2 to enter the change state diagram 3. Click the "Exit" button in the change state diagram 3 to enter the change state diagram 4.

A machine for machining and / or measuring gearing, having two or more numerically controlled machine axes for carrying out machining movements and / or measuring movements, having a machine controller, wherein the machine controller has a control software, wherein the control software is set up for executing machine functions, such as executing program sequences for controlling the numerically controlled machine axes, the output of service reports or the like. The machine controller has a user interface set up for interaction with a machine operator, wherein for at least one of the machine functions it is predetermined by the control software that the execution of this machine function requires at least one manual input by a machine operator at the user interface. A bot software is assigned to the control software in order to replace the at least one manual input and to execute the machine function independently of a machine operator.

The application discloses a method and device for configuring software of a sweeping robot, electronic equipment and a storage medium, and applies to the technical field of computers. The method for configuring the software of the sweeping robot comprises the following steps: obtaining modification data corresponding to client software of the sweeping robot, and obtaining a modified configuration file according to the modification data; selecting environment configuration data matched with environment parameters corresponding to the modification data in the configuration file according to the environment parameters; and analyzing target configuration data corresponding to the environment configuration data by the client software of the sweeping robot, so as to complete the configuration of the modification data. The application solves the technical problem of low development efficiency of the software of the sweeping robot.

This application discloses an automated method and system for generating a robot skill primitive library based on a large language model, relating to the fields of artificial intelligence and robotics software engineering. The method includes: extracting modular functions and procedural scripts from the robot's task-level Python files using a two-level function extraction strategy; based on the extracted robot function code, using preset thought chain prompts to guide the large language model in generating global semantic descriptions and disambiguating functions with the same name; based on the robot task-level function metadata after disambiguation, using preset thought chain prompts to guide the configured large language model in perceptual code reconstruction with embedded domain constraints; and based on the reconstructed code, using preset thought chain prompts to guide the configured large language model in adaptive iterative code evaluation and optimization loops to obtain the robot skill primitive library. This application can generate a robot skill primitive library fully automatically and with high reliability.

Provided is a robot software maintenance device for checking whether or not a software update for a robot control device connected via a network is appropriate, the software maintenance device comprising: a correction patch storage unit that stores a correction patch for updating software of the robot control device; a test case storage unit that stores a test case for determining success or failure of a software update; a configuration data acquisition unit that acquires, from the robot control device, configuration data for specifying a configuration of the robot control device; a virtual control device generation unit that generates, on the basis of the configuration data, a virtual control device that virtually imitates behavior of the robot control device; and an update determination unit that applies the correction patch to the virtual control device and determines success or failure of the software update according to the test case.

The invention discloses an all-in-one robot based on Beidou and a multi-mode sensing technology, and the all-in-one robot is provided with robot hardware and robot software. The robot hardware comprises an AGV trolley, an automatic total station, a satellite receiver, a multi-view camera, a force mode sensor, an acoustic mode sensor, an optical mode sensor, an electric mode sensor and an auxiliary device. The AGV trolley, the automatic total station, the satellite receiver, the multi-view camera, the force mode sensor, the acoustic mode sensor, the optical mode sensor and the electric mode sensor are detachable and are provided with multiple combination modes, and the robot software comprises a construction digital twin system. And the digital twinning system is combined to realize the functions of surveying and paying-off, station bypassing, routing inspection and acceptance inspection.

The application relates to the technical field of robot control, in particular to a self-adaptive robot driving system based on an RT-Thread, which comprises a power module, an integrated main control module, a motor driving module and a serial port transmission module; wherein the power module is used for providing power supply and monitoring the battery voltage in real time; the integrated main control module is used for carrying a real-time thread operating system and scheduling different function modules; the motor driving module is used for configuring the motor of a driving chassis and executing robot moving operation; and the serial port transmission module is used for reserving a serial port for communication connection and data transmission. The self-adaptive robot driver using the RT-Thread operating system is built by fusing the motor and sensor data accessed by the driving system, the special posture of the vehicle body can be detected in time and real-time control is carried out, and the convenience of robot software and hardware integration is greatly improved.

Machine (2) for machining and / or measuring gears, with two or more numerically controlled machine axes for performing machining and / or measuring movements, with a machine control (10), wherein the machine control (10) comprises control software (12), wherein the control software (12) is configured to execute a plurality of machine functions (F1, F2... FN), such as executing program sequences for controlling the numerically controlled machine axes, outputting service reports, or the like, wherein the machine control (10) comprises a user interface (14), wherein the user interface (14) is configured for interaction with a machine operator, wherein for at least one of the machine functions (F1, F2... FN) the control software (12) specifies that the execution of this machine function (F1, F2...FN) requires at least one manual input by a machine operator at the user interface (14), wherein the control software (12) is associated with a bot software (20) to replace the at least one manual input and to execute the machine function (F1, F2... FN) independently of a machine operator.

The invention provides a software algorithm testing method and device of a robot and a robot testing platform, and relates to the field of robot software testing. The software algorithm testing method for the robot comprises the steps that a to-be-tested software algorithm and task information are acquired, and initial configuration parameters corresponding to a target execution module of the robot are acquired based on the task information; based on the initial configuration parameter and the to-be-tested software algorithm, generating an action execution instruction, and based on the action execution instruction, controlling a target execution module to execute an action to obtain an execution result; and determining the algorithm performance of the to-be-tested software algorithm based on the execution result and the called preset execution result. According to the method, the influence of unpredictable factors in a real environment on action execution of the robot can be reduced.

The present application relates to a behavior tree modeling method, apparatus, and device that supports robot decision reuse. The method includes: constructing a decision library for robot software, selecting five mainstream decision modes from the decision library based on prior knowledge; the decision modes include prudent decision-making, reactive decision-making, hybrid decision-making, online probabilistic decision-making, and offline probabilistic decision-making; extracting three common behavior interaction modes from the decision modes based on the behavioral abstraction of perception behavior, effector behavior, and planning behavior, as well as the interactive relationship between behaviors; using the behavior interaction modes, selecting sequence control nodes and two action nodes in the behavior tree, and modeling with a sequence subtree structure as the basic model framework of the behavior interaction mode to obtain a behavior tree that supports robot decision reuse. This method can improve the reuse rate of robot decisions.

Systems and methods for adding process actions to the design of a robotic software process. A context-recognition module recognizes a current state of a process being designed, and passes information on that current state to a recommendation module. The recommendation module evaluates the current state and identifies at least one suitable process action to recommend in response to that current state. The recommendation module then recommends the at least one process action to the human designer. If the designer accepts the recommendation, a design module adds the process action to the process design. The recommendation module may also use information about previous actions in the process and in other processes when identifying suitable process actions. The context-recognition module and the recommendation module may each comprise at least one machine learning module, which may or may not be neural network based.

The invention relates to a machine tool (2) for machining and / or measuring teeth, comprising two or more numerical control spindles for carrying out machining and / or measuring movements, comprising a machine tool control system (10), which has control software (12), the invention relates to a machine tool control system (10) for a numerical control spindle (12), comprising control software (14) which is designed to carry out a plurality of machine tool functions (F1, F2... FN), such as to carry out program flows for controlling the numerical control spindle, to output service reports or the like, having a user interface (14) which is designed to interact with a machine tool operator, according to the invention, the control software provides that at least one manual input is required by a machine tool operator on the user interface to carry out the machine tool function, and the control software is provided with robot software in order to replace the at least one manual input and carry out the machine tool function independently of the machine tool operator.

The invention discloses a robot control, monitoring and simulation system which comprises an upper computer and an actuator, and the upper computer is connected with the actuator through ROS communication middleware. The ROS communication middleware is a distributed communication framework for robot software development, provides communication, coordination, resource management and other functions for different nodes in a robot system, and has the characteristics of cross-platform, open source, modularization and the like. According to the robot control, monitoring and simulation system, the robot control and task arrangement efficiency is improved, and the operation process of a user is simplified; due to the open source characteristic and the modular design, the initial investment and the long-term operation and maintenance cost are further reduced; a user can check the joints, the motion path and the state of the robot at any time, discover problems in time and adjust; the popularization and application range of the robot technology is expanded, and the operation convenience and flexibility are improved.

The application provides a task processing method and a robot, the robot comprising a classification machine, a task machine and a process state machine, the method comprising: the classification machine first determining whether a target task is a process task, if yes, sending task information corresponding to the target task to the task machine, if not, determining a task type corresponding to the target task, and sending the task information corresponding to the target task to the process state machine according to the task type. The task machine pre-processes the task information to make it meet the task execution requirements corresponding to the process task, and then sends it to the process state machine. After receiving the task information, the process state machine executes a task process corresponding to the target task. The target task is an agent task sent by a large language model corresponding to the robot, and the process task is a task comprising multiple different types of tasks. In this way, the robot can better process the agent task, improve the performance of the robot, and reduce the software development and maintenance cost of the robot.