82 results about "Robot operating system" patented technology

An autonomous traveling robot operation system that improves the ease with which an autonomous traveling robot is operated by using a voice input and a handwritten input is provided. An autonomous traveling robot operation system including: an autonomous traveling robot configured to shoot an environment near the autonomous traveling robot and operates an object to be operated; a handwritten input interface configured to display an image shot by the autonomous traveling robot and receive a handwritten input to the displayed image; and a voice input interface configured to receive a voice input to the object to be operated, in which the autonomous traveling robot operation system operates the autonomous traveling robot in such a way that the autonomous traveling robot operates the object to be operated in accordance with instructions of the handwritten input and the voice input is provided.

The invention provides a robot operating system and method based on hardware isolation and a dynamic task engine, belongs to the technical field of artificial intelligence, and aims to solve the problem that the real-time performance and the intelligence are bidirectionally opposite for a long time in an architecture level in the field of robots. The system comprises a heterogeneous multi-core SoC, a universal operating system deployed in a non-real-time domain, a kernel real-time operating system deployed in a real-time domain, an inter-core communication bus based on shared physical memory configuration and an integrated development tool chain based on a VSCode plug-in. The method comprises the steps that a robot operating system based on hardware isolation and a dynamic task engine is built; task generation, routing and deployment are carried out; and when the real-time domain executes the task, the high-frequency state data is reported to the non-real-time domain through the inter-core communication bus to form closed-loop cooperative control.

The invention relates to the technical field of robot operating systems, and provides a communication topic monitoring diagnosis method and system based on an ROS 2 system, and the method comprises the steps: configuring global parameters, topic parameters and diagnosis rules; creating an independent monitoring thread for each topic; in each monitoring thread, creating a monitor instance for the corresponding topic; dynamically loading a message type corresponding to the topic by each monitor instance, establishing QoS (Quality of Service) configuration and creating a subscriber; after the message arrives at the monitoring thread, the subscriber receives the corresponding message, triggers a preset callback function, and obtains an original statistical data stream; creating an independent analysis thread for each topic; in each analysis thread, performing real-time statistical calculation on the original statistical data to obtain a structured analysis result; and comparing the structured analysis result with the diagnosis rule in real time, and outputting a specific problem description and a diagnosis result. The problem that topics cannot be monitored and diagnosed automatically in batches is solved.

The invention provides a coroutine task scheduling optimization method based on OpenHarmony, belongs to the technical field of industrial robot operation, and aims to solve the problem that an industrial robot is insufficient in real-time performance, concurrency and flexibility in a complex task scene, and the method comprises the following steps: S1, coroutine data structure design; s2, optimizing coroutine memory management; s3, multi-architecture processor adaptation is carried out; s4, optimizing a coroutine task scheduling mechanism; s5, carrying out coroutine multi-core scheduling optimization; the invention designs and realizes an industrial robot operating system library of a lightweight coroutine in order to realize coroutine task scheduling optimization. According to the coroutine library, the lightweight coroutine library which is lower in memory occupation, higher in task real-time performance and higher in CPU utilization rate is designed and realized aiming at the condition that resources are limited in a robot scene, and meanwhile, the coroutine library is introduced into a domestic robot operating system for real-time scheduling adaptation for the first time.

The present invention discloses a robot operating system and operating method supporting multimodal interaction, relating to the field of intelligent robotics. The system comprises: a data receiving module, a target object recognition module, an analysis and decision module, and a response module. The data receiving module is configured to preprocess acquired multimodal heterogeneous data to obtain sensory data, wherein the multimodal heterogeneous data includes at least one of visual data, auditory data, tactile data, and semantic data. The target object recognition module is configured to create a corresponding user profile for the target object based on the sensory data. The analysis and decision module is configured to perform preference analysis based on the user profile and derive a response strategy based on a deep learning model. The response module is configured to issue an operation instruction based on the response strategy. The present invention achieves the ability to better understand and respond to user needs based on individual user characteristics.

The application provides a push stream control method and device and electronic equipment, and relates to the technical field of automatic driving. The method comprises the following steps: subscribing to a push stream switch topic published by a remote control platform based on a preconfigured robot operating system (ROS) node; obtaining push stream control information issued by the remote control platform from the push stream switch topic; the push stream control information comprises a push stream total switch and a target address; the push stream total switch is used to represent a push stream on state or a push stream off state; updating a current push stream parameter in the ROS node according to the push stream control information to generate a new push stream parameter; and controlling camera push stream to a target server according to the new push stream parameter; the target server is a device corresponding to the target address. The method can realize dynamic updating of the push stream parameter in the ROS node, thereby adapting to the dynamic scheduling requirements of multiple vehicles and multiple tasks in a vehicle-mounted scene.

The utility model discloses a lawn cleaning robot, include: robot main body, mechanical arm structure, lower layer clamp jaw, camera, dustbin, radar, omni -wheel, control unit, GNSS positioning module and IMU, the mechanical arm structure is controlled to a plurality of rudders, makes the mechanical arm structure realize to lift or put down action on the robot main body upper end, and realizes rotating action, is equipped with upper layer clamp jaw in the foremost end of this mechanical arm structure, and this upper layer clamp jaw is controlled to the first rudder, realizes clamping or release, the lower layer clamp jaw is controlled to the sixth rudder, realizes clamping or release, the camera is controlled to the fifth rudder, realizes rotation, has ROS robot operating system and existing identification algorithm YOLOV11 on the control unit deployment.

A modular symbolic operating system enabling robotic agents—humanoid, aerial, aquatic, or morphing—to operate with lawful cognition, ethical routing, and energy-agnostic behavior through real-time symbolic reasoning. The system integrates a symbolic instruction layer, behavioral arbitration graphs, and energy-type decoupling logic that allows mission-adaptive reconfiguration of robotic form, function, and purpose. This invention supports AGI-level interaction across domains including mobility, dexterity, manipulation, environmental engagement, and cooperative swarm missions—while maintaining symbolic integrity across dynamic configurations.

The invention provides a service calling method, electronic equipment, a medium and a program product. The method comprises the following steps: registering a target service to obtain service description information of the target service, issuing the service description information by a server, generating a service calling request by a client based on the service description information, and sending the service calling request to the server. The server side can convert the service calling request into the service calling message conforming to the message specification of the robot operating system based on the conversion rule, and sends the service calling message to the service node providing the target service, so that calling of the target service is achieved.

An embodiment of the present invention discloses a method and system for autonomous escape of an unmanned vehicle in a robot-operated system. The method includes: when the navigation center hub node of the robot operating system reports that the unmanned vehicle cannot reach the predetermined target point, based on the cost map, autonomously generating a temporary target point that the unmanned vehicle can reach; when the unmanned vehicle reaches the temporary target point and escapes the trapped situation, the original target point is sent to the navigation center hub node again for path planning; wherein, the situation in which the unmanned vehicle cannot reach the predetermined target point includes local trajectory control failure, route planning failure or repeated oscillation; wherein, the cost map is formed by assigning a cost value to each grid in the grid map. The system includes a temporary target point generating device and an original target point sending device. When the unmanned vehicle collides with an obstacle or planning fails, the present invention can effectively help the unmanned vehicle escape and eventually reach the predetermined target point.

The invention discloses a fault processing method and device, equipment and a medium, and relates to the technical field of detection, and the method comprises the steps: distributing a robot operation system node task for each computing device; acquiring a robot operating system node configuration file and a robot operating system node starting parameter; starting the robot operating system node of each computing device according to the robot operating system node configuration file and the robot operating system node starting parameter; in response to a process fault of the robot operating system node of any computing device, restarting the robot operating system node of the computing device through a daemon process program of the computing device; and in response to a fault of any computing device, starting a robot operating system node process on the faulted computing device on an adjacent computing device. According to the method, the high availability and the self-recovery capability of the ROS2 system are improved, and a more stable and reliable ROS2 computing platform is realized.

A kind of semi-physical test system and method of robot operating system application verification, including GPS transmitting module, state monitoring module, formation similarity calculation module, autonomous path planning module and effect evaluation module.Wherein, GPS transmitting module is used to generate and emit GPS signal in indoor environment simulation;State monitoring module is used to monitor the measured stress of each unmanned aerial vehicle;Formation similarity calculation module is used for each unmanned aerial vehicle to autonomously calculate the expected target position of itself in formation;Autonomous path planning module is used for each unmanned aerial vehicle to autonomously calculate the expected control acceleration of itself, and determine expected stress;Effect evaluation module is used to exclude the hardware failure of each unmanned aerial vehicle, and the function and performance of robot operating system are evaluated.The application can reduce the frequency of large-scale unmanned aerial vehicle to field test, reduce test cost.

The application relates to the technical field of driving assistance, and discloses a vehicle automatic emergency braking system and method based on a depth image, a vehicle automatic emergency braking system based on a depth image, which comprises a depth camera, a steering torque sensor, a vehicle-mounted controller and a robot operating system. The application further discloses an implementation method of the vehicle automatic emergency braking system based on the depth image, which comprises the following steps: S1, receiving a color image and a depth image and aligning the images; S2, generating a depth mask according to a vehicle state; S3, performing image processing on the depth image; and S4, determining a target distance according to the processed depth image. The application can realize nonlinear change of a depth threshold line and multi-scene adaptation, can compensate for defects of an ordinary camera imaging principle, can realize accurate target object detection, can have good robustness for target distance detection, and can further realize precise emergency braking.

The application discloses a design method of a multi-axle unmanned vehicle chassis based on a ROS general robot operating system, and comprises the following steps: step one, designing a multi-axle vehicle electric drive hardware platform, S1.1 hardware architecture design; S1.2 software platform design; step two, designing a multi-axle vehicle steering and torque distribution algorithm based on target speed control, S2.1 calculating multi-axle vehicle wheel steering angles by using an Ackerman steering angle principle; S2.2 designing a fuzzy torque control method according to different steering inside and outside speeds; and step three, designing a control algorithm module for controlling vehicle steering. The torque distribution algorithm based on target speed control can effectively distribute the multi-wheel torque of the system, guarantee the basic stability of the target speed, realize the fuzzy self-distribution strategy of the torque, has good practical value, can be used for realizing the algorithm basis of unmanned driving, and has the characteristics of good torque distribution effect of target speed control and strong practicability.

The invention provides a multi-sensor data fusion system. The multi-sensor data fusion system comprises a sensor interface module used for receiving and transmitting sensor messages; the time synchronization module is used for performing time synchronization processing on sensor messages from different sensors; the fusion processing module is used for fusing the sensor messages subjected to time synchronization processing; the fusion data publishing module is used for publishing the fused message; the multi-sensing data fusion system supports function implementation of all the modules based on a second-generation robot operating system ROS2. According to the multi-sensor data fusion system provided by the invention, the overall architecture is constructed based on the second-generation robot operating system ROS2, so that efficient collaboration and standardized communication of each functional module are realized, and the universality and deployment efficiency of the whole fusion system are improved.

The invention discloses a robot operating system communication method. The method comprises the following steps: installing a robot operating system and deploying a FastDDS; when the robot operating system publishes or subscribes a message, the hard real-time operating system obtains a QoS configuration parameter of the message and calculates a real-time priority index; establishing a priority mapping strategy of the robot operating system QoS and the hard real-time operating system in the hard real-time operating system; binding a corresponding priority for the message processing thread based on the real-time priority index; executing tasks based on priority scheduling and a dynamic priority adjustment mechanism; a load monitoring thread is deployed, the load monitoring thread counts system load data, task load data and network load data every preset time, and thread priority and resource allocation are adjusted in real time. According to the robot operating system communication method, the initial priority of the hard real-time operating system task is directly determined by QoS configuration, and QoS resource allocation can be dynamically counteracted according to the system load.

The application discloses a time-sensitive network data stream gating method for a robot operating system, which comprises the following steps: initializing a gating list; obtaining first occupation information of a first time slot corresponding to a first target sending queue in a first preset continuous gating period; when the first occupation information meets a preset adjustment condition, adjusting the first time slot into a second time slot; obtaining second occupation information of the second time slot in a second preset continuous gating period; when the second occupation information meets a preset recovery condition, restoring the time slot corresponding to the first target sending queue into the first time slot, otherwise, keeping the time slot as the second time slot. The method provided by the application can dynamically adjust the gating list according to the actual occupation of the time slot corresponding to the sending queue with the highest priority, thereby improving the adaptability of time slot configuration to service changes, guaranteeing the deterministic transmission of high-priority data streams, and improving the utilization rate of time resources.

A method for operating a mobile robot to dynamically offload computational tasks to a cloud system is described. Advantageously, the method allows the mobile robot to switch between local execution by the robot itself and remote execution by the cloud system at any time, depending on time, energy, or other requirements. This enables the mobile robot to be robust against varying network conditions while simultaneously leveraging the advantages of external computing resources whenever possible. In at least some embodiments, middleware, such as a robot operating system, is used for communication between the mobile robot and the cloud system.

The application relates to the technical field of robot operating system, and provides a communication topic monitoring and diagnosing method and system based on a ROS 2 system, wherein the method comprises the following steps: configuring global parameters, topic parameters and diagnosis rules; creating an independent monitoring thread for each topic; in each monitoring thread, creating a monitor instance for the corresponding topic; each monitor instance dynamically loads the message type corresponding to the topic, establishes QoS configuration and creates a subscriber; when a message arrives at the monitoring thread, the subscriber accepts the corresponding message, triggers a preset callback function, and obtains an original statistical data stream; an independent analysis thread is created for each topic; in each analysis thread, original statistical data is subjected to real-time statistical calculation, and a structured analysis result is obtained; the structured analysis result is compared with the diagnosis rules in real time, and a specific problem description and a diagnosis result are output. The application solves the problem that topics cannot be monitored and diagnosed in batches and automatically.

The invention discloses a robot operating system based on KaiHong OS, a robot control method, computer equipment and a medium. The system comprises an operating system layer, a middle layer and an application layer, the operating system layer adopts a KaiHong OS and provides hardware abstraction, bottom layer driving, bottom layer task scheduling, compiling and equipment driving functions; the middle layer is used for carrying out secondary packaging on the operating system layer and providing standard interfaces which are uniform in format and modularized; and the application layer manages the whole robot operating system through the node manager, and splits and combines the functions of the robot operating system by taking nodes as units. According to the method, the KaiHong OS is used as the OS layer support of the robot operating system, the KaiHong OS is connected with the underlying hardware, the KaiHong OS is operated on the computer hardware, an application layer is kept unchanged, a developer can conveniently develop the robot on the KaiHong OS, and the development efficiency of the robot is improved.

1. Name of the product in this design: Graphical User Interface for Operating System of Data Center Inspection Robot for Electronic Equipment. 2. Application of this design: This design is intended for use in an electronic device. 3. The key design feature of this product is its graphical user interface. 4. The image or photograph that best illustrates the design's key features: the front view. 5. Purpose of the graphical user interface: This graphical user interface is used by users to view robot data information, control the robot in real time for inspection and assistance work in data center scenarios. 6. Human-Computer Interaction Method of Graphical User Interface: The main view is the main interface after the user enters the system; clicking the "Manual Inspection" function module in the main view leads to interface state diagram 1; clicking the "Inspection Task 1" option in interface state diagram 1 switches to interface state diagram 2; clicking the "Execute Now" button in interface state diagram 2 leads to interface state diagram 3; after the countdown in interface state diagram 3 ends, the robot proceeds to the first inspection point, and the interface state diagram jumps from 3 to 4; when the robot reaches the target point, the interface state diagram jumps from 4 to 5; after all inspection points have been inspected, the robot automatically returns, and the interface state diagram jumps from 5 to 6; when the robot returns to the starting point, the interface state diagram jumps from 6 to 7; clicking the "View" button in the "Rack Door Not Closed Alarm" list in interface state diagram 7 leads to interface state diagram 8.

The invention discloses an integrated non-intrusive, safe and user-friendly electroencephalography (EEG) system capable of classifying signals generated from both Event Related Potential (ERP) based steady-state visually evoked potential (SSVEP) and pure cognition, leveraging Riemannian Geometry-based signal classification algorithms for precise command generation. The system seamlessly combines SSVEP-based visual stimuli with cognition-based EEG signals to provide a comprehensive interface for brain-computer interaction (BCI) applications. Riemannian Geometry techniques are employed for robust signal classification and efficient command generation, enhancing the system's accuracy and reliability.

This invention relates to the field of program vulnerability detection, and discloses an optimized method, apparatus, and device for vulnerability detection in a robot operating system. The method includes: obtaining registration information through a registration tracker and obtaining execution information of the robot operating system through a runtime tracker; the registration information includes attributes related to callback functions and the type of the callback functions; constructing a callback trace based on the registration information and the execution information; analyzing the callback trace to verify whether a new system state has been generated; generating new test cases based on the new system state, and using the new test cases as test cases for the next round of iterations. This invention solves the problem of traditional fuzzy testing for robot operating system vulnerabilities being coarse and incomplete.

Provide a system. 【Solution means】 In an electronic communication management device, Means for analyzing the received electronic communication and performing category classification; Means for summarizing the content of the electronic communication; Means for setting priorities based on the electronic communication; Means for automatically generating a template sentence for the electronic communication; Means for notifying the user of unhandled electronic communications; Means for analyzing and classifying instructions within the factory; Means for summarizing the instructions and notifying the robot operation system; Means for determining the work order of instructions according to the priority; A system including the above.

The invention relates to a data visualization method and device for a vehicle and the vehicle. The data visualization method for the vehicle comprises the following steps: acquiring a radar signal data frame in a first communication format, wherein the radar signal data frame comprises output data for a target environment corresponding to a millimeter wave radar device of the vehicle; generating a visual graphic data set of a target object in the target environment based on the radar signal data frame; and transmitting the visual graphic data set of the target object through a publish-subscribe mechanism among a plurality of ROS (Robot Operating System) nodes, so that the visual graphic data set is transmitted to at least one ROS node to serve as a data source for visually displaying the target object. According to the invention, the output data of the millimeter wave radar device of the vehicle is converted and transmitted into the visually displayed data source, so that the performance perception or verification of the radar device can be conveniently realized.

A robot operation system with improved accuracy of a learning model accuracy is provided. Provided is a robot operation system including a composite image generation unit to which CAD data of an object and a workpiece and a feature point of the workpiece are input configured to generate a plurality of composite images under random conditions from the CAD data of the object and the workpiece, an information processing apparatus configured to search for a route using a position of an end effector of a robot and a position of the feature point and move the end effector to the feature point along the searched route, and an imaging apparatus configured to photograph the object and the workpiece.

The invention belongs to the technical field of robot control and distributed autonomous systems, and particularly relates to an autonomous robot coverage control system based on multi-Jetson collaboration, which is realized based on an ROS2 robot operating system and a multi-Jetson embedded computing platform, and comprises the following steps: multi-sensor data acquisition; carrying out pose fusion and positioning; performing pose processing and neighbor recognition; neighbor detection and event judgment; performing data synchronization and cyclic scheduling; dynamically adjusting the sensing radius; carrying out actuarial calculation and weighted centroid calculation on the Voronoi region; control law calculation and saturation constraint; issuing a target point and executing a path; asynchronous and energy-saving control is realized; wherein the ten stages are independently executed on a local ROS2 node of each Jetson trolley, the whole system operates in an asynchronous distributed mode, and autonomous coverage control can be achieved without a central control node. According to the invention, the problems of complex synchronization, high energy consumption, communication dependence and the like in the existing multi-robot distributed coverage control can be solved.

The invention particularly relates to a method for optimizing an intelligent network with a body in a multi-dimensional state space. According to the method, a multi-dimensional state space S and a hierarchical action space A are constructed, a model based on deep reinforcement learning is used as a core scheduler, and autonomous learning and collaborative decision making of the method are realized; building a multi-dimensional space, building a hierarchical action space and a reinforcement learning collaborative optimization model are seamlessly integrated into a control system of the intelligent agent, and autonomous behavior decision-making of network awareness is achieved; the active optimization framework efficiently interacts with a robot operating system (ROS) service of the robot body, and converts an abstract optimization strategy into specific physical and communication instructions. According to the multi-dimensional state space-based intelligent network optimization method, the transformation of the intelligent agent from the traditional passive adaptation network to the active optimization network connection is realized, and the end-to-end task performance and the connection stability are remarkably improved.

The present embodiments propose a logistics robot operating system for order picking and inventory replenishment, a control method therefor and a computer program, the system controlling an inbound flow of transporting and loading a loading unit including transport items to a designated loading area through a loading robot, controlling, when inventory replenishment is required according to inventory monitoring in a storage area in which the transport items are disposed, an inventory replenishment flow of unloading the loading unit loaded in the loading area through a transport device and transporting the unloaded loading unit to the storage area through at least one task-performing robot, and managing, on the basis of user-specific transport information received through a warehouse management system, tasks of picking the transport items through the task-performing robot in the storage area and delivering the picked transport items to a packing position through the task-performing robot.

The invention relates to the technical field of agricultural machinery intelligent control, in particular to a hilly and mountain tractor intelligent autonomous operation method based on multi-sensor fusion, which comprises an intelligent autonomous operation system and is characterized in that a distributed control system with a robot operating system (ROS) as a software platform and a controller area network (CAN) bus as a neural network is constructed; the intelligent vehicle-mounted terminal, the multi-path electric control module and the positioning navigation unit are organically integrated, information centralized processing and instruction cooperative control are achieved, and the overall intelligent level and the system reliability of the tractor are remarkably improved. Moreover, based on a decision-making mechanism of multi-sensor fusion, the system does not depend on a single information source any more, and the system can maintain stable sensing ability through information complementation even in a common satellite signal shielding or attenuation environment in hills and mountains, so that the continuity of the autonomous operation system under complex and severe working conditions is guaranteed.