1888 results about "Workspace" patented technology

A dual-arm cooperative potential field-based force-guided teleoperation system and control method. By means of real-time poses of tool center points of two robotic arms, whether the shortest distances dp-s,i between a target object and workspace boundaries of the two arms are lower than a threshold Ds is iteratively determined; if the shortest distances are both greater than the threshold, a dual-arm symmetric cooperation strategy is adopted, and if the shortest distances are lower than the threshold, a single-arm prioritized cooperation strategy is adopted, and the arm is used as a priority arm; cooperation factors δi of the two arms are respectively determined on the basis of the cooperation strategies; a dual-arm cooperative potential field is constructed on the basis of the cooperation factors, the distances between the target object and the tool center points of the two arms, and the position of an obstacle; and corresponding dynamic virtual constraint forces are generated on the basis of the dual-arm cooperative potential field, and two force feedback hand controllers are used to guide and assist an operator in controlling the two robotic arms to complete a dual-arm cooperative task.

The invention relates to the technical field of mechanical arm obstacle avoidance path planning, in particular to a multi-degree-of-freedom mechanical arm obstacle avoidance path planning method based on three-dimensional reconstruction, which comprises the following steps: step 1, three-dimensional environment perception and dynamic modeling; preferentially offsetting and expanding the near-obstacle nodes towards the concave area or the hole center to generate a candidate node set; and 4, three-dimensional grid collision verification and safe path correction are conducted, specifically, the working space of the mechanical arm is divided into three-dimensional voxel grids, and collision detection is achieved by judging whether path nodes fall into obstacle object elements or not. According to the method, the laser radar and the depth camera are adopted to synchronously collect data through hardware triggering, statistical filtering denoising and three-dimensional grid modeling are combined, geometrical characteristics of static obstacles and motion parameters of dynamic obstacles are restored, and the collision risk caused by environmental perception errors of the mechanical arm is effectively avoided.

Technology is described for determining a task plan that is usable by a robotic device in a workspace. The method can include converting instructions received for the robotic device into temporal logic (TL) statements and to a non-deterministic Buchi Automaton. A task probabilistic machine learning model can be generated with feasible task plans using the non-deterministic Buchi Automaton. A plurality of task plans can also be created or generated using the task probabilistic machine learning model. A sensor probabilistic machine learning model of the workspace can be constructed using information from sensors of the robotic device. The task plans from the task probabilistic machine learning model can be compared with the sensor probabilistic machine learning model to select the task plan with a high probability of correlation to the workspace.

The invention belongs to the field of intelligent equipment, and relates to a mechanical arm control method and system based on image point cloud cross-modal fusion and action block Transformer, and the method comprises the steps: constructing a scene point cloud according to a multi-view RGB image and a corresponding depth map; a virtual view of multi-view fusion image-point cloud information is generated around the working space of the mechanical arm through the scene point cloud; inputting the virtual view of the multi-view fusion image-point cloud information into a feature extraction network to obtain a feature map; obtaining each joint state and a historical action sequence in the mechanical arm, and projecting the joint states; inputting the feature map, the projected joint state and the historical action sequence into an encoder to obtain encoding features; the coding features are input into a decoder, and a mechanical arm action sequence is predicted based on an action partitioning strategy; the mechanical arm is controlled according to the mechanical arm action sequence; according to the method, the multi-modal sensing data of the point cloud image are integrated into uniform feature representation, and intelligent action planning of the mechanical arm is realized in combination with the action block Transform, so that the global understanding and decision-making capability of the robot on complex tasks is improved.

The invention relates to the technical field of data processing, and discloses a method and a system for dynamically generating declaration receipts based on custom configuration, the method comprises the following steps: constructing a component library, the component library comprises multiple types of data item components, and each data item component is packaged into an independent module; based on the graphical configuration process, adding the components in the component library to a working area, and setting field attributes; setting a dependency relationship between fields based on conditional logic, defining a legality rule of the fields based on a data verification rule, and automatically storing a historical version in a configuration process based on version control; and based on preset authority and distribution setting, determining a filling person range and a filling time limit of the declaration receipt, and notifying a filling person. According to the invention, the form creation efficiency is improved, the maintenance cost is reduced, and the expandability and applicability of the system are enhanced.

A method of programming an industrial robot (100), with a robot manipulator (110) and robot controller (120), comprises: recording movements of the robot manipulator during a demonstration-based robot programming session, for thereby obtaining a robot trajectory; acquiring a video of the robot programming session; and generating, on the basis of the robot trajectory and the video, a robot program (C) executable by the robot controller, wherein the robot program includes at least one motion command which is expressed in a first reference frame (0 1). The method further comprises capturing operator input data indicating a first object (151) in an image in the video. The generated robot program includes a command to identify a position of an object resembling the first object in a work area (150) of a robot which executes the robot program; and the first reference frame is defined with respect to the identified position of the object resembling the first object.

The disclosure is directed to a fire suppression system that includes all control components in a single integrated panel. It further contemplates and may include a chamber configured to maintain an interior inert atmosphere and to enclose and establish a nonflammable workspace for a pyrophoric workpiece. A temperature sensor may also be included and mounted proximate the workspace, along with an oxygen concentration sensor configured to detect an interior oxygen concentration of the atmosphere. The system also includes a dispenser configured to discharge an antipyrophoric granular material onto the workpiece responsive to automatic detection proximate the workpiece of at least one of a predetermined temperature and oxygen concentration. In variations, the chamber is configured as a glove box having viewing windows and a plurality of sealed glove ports positioned to enable user manipulation of the workpiece about the workspace.

The invention discloses an automatic suction removal method, device and equipment for welding smoke and a medium, and relates to the technical field of machine learning. Linear interpolation and capacity expansion are conducted on a temperature matrix of a welding area; inputting the interpolated and expanded temperature matrix into a decision tree model, outputting predicted position information of the smoke source, and calculating spatial position coordinates; converting the point cloud data of the welding area into a grey-scale map, fusing the grey-scale map and the interpolated and expanded temperature matrix data to obtain a temperature space distribution matrix, inputting the temperature space distribution matrix into a first convolutional neural network, and outputting obstacle avoidance point cloud data; calculating parameters of the obstacle avoidance area, inputting the parameters, the spatial position coordinates and the initial joint rotation angle of the actuator into a second convolutional neural network, and outputting a target joint rotation angle; therefore, the welding smoke in the welding area can be automatically sucked by the actuator, the sucking efficiency is improved, the smoke concentration in the welding working area is reduced, the conflict condition of the smoke sucking disc working area is avoided, and the interference to the welding work and the sucking leakage rate are reduced.

To provide a development support system allowing users to freely create nodes and edges on a workspace, the development support system allowing selection of a large-scale language model for every prompt node, and enabling prompt provision (transmission) and acquisition of output results on a per-node basis.SOLUTION: A development support system 1 includes a workspace creation unit and a large-scale language model input / output unit, where a prompt node created on the workspace includes a large-scale language model selection field, a prompt reception field, and an output result display field for displaying an output to a prompt. Each prompt node also enables provision of prompts to the large-scale language model and acquisition of results, and the prompt node displays the output results.SELECTED DRAWING: Figure 1

The present disclosure relates generally to robotic systems, and more specifically to systems and methods for specifying a robot task configuration by means of annotating a visual workspace representation in coordination with a waypoint optimization process. This system enables a much broader use of robotic automation by saving time and reducing technical complexity. This system can be used to configure any visually enabled robotic task, such as tasks in warehouse management, manufacturing, delivery, inspection, logistics, etc.

Mechanisms are provided for dynamically generating workspaces and provisioning them with datasets. The mechanisms store datasets in a data vault for provisioning to dynamically generated workspaces associated with users. The dynamically generated workspaces are computer environments through which the users can perform operations on the one or more datasets. The mechanisms receive a request, from a user, for access to a specified dataset, and retrieve a data usage agreement (DUA) corresponding to a pairing of the user with the specified dataset. The DUA specifies a level of obfuscation to be applied to the specified dataset when provisioning a workspace associated with the user, with the specified dataset. The mechanisms dynamically generate, on-demand, the workspace associated with the user based on the retrieved DUA. The mechanisms also automatically provision, on-demand, the dynamically generated workspace with a version of the specified dataset corresponding to the level of obfuscation specified in the DUA.

A robotic arm obstacle avoiding path planning method is provided. The method includes the following steps: step 1: simplifying the robotic arm model and obstacles, determining robotic arm joint points, and adopting virtual joint interpolation to interpolate connecting rods between adjacent joints; employing spherical bounding boxes at each joint point to envelop and replace the robotic arm model, enabling complete substitution for distance calculation when the robotic arm assumes any posture; step 2: adopting an eye-to-hand configuration to position the depth camera, acquiring in real time the point cloud information of the robotic arm and obstacles in the workspace, and using a robot real-time filtering package to filter out the point cloud information of the robotic arm itself.

A technique manages computing resources on a container orchestration platform. Such a technique involves establishing a pool of computing resources on the container orchestration platform. Such a technique further involves, after the pool of computing resources is established, receiving graphics processing unit (GPU) provisioning requests (GPRs) which identify workspaces. Such a technique further involves allocating computing resources from the pool to the workspaces identified by the GPRs based on a set of GPR prioritization policies.

A mobile track safety device (1.1), in particular a track worker warning system, for securing a work area (2) on a track section (3.1, 3.2) comprises a signal processing unit (19) for processing digital information, wherein the signal processing unit (19) has at least one interface (6) for receiving a position of at least one moving hazard object (8, 12), in particular a rail vehicle (12), from a tracking device (13.2, 17), and for receiving a position of at least one moving protection object (8, 16), in particular a track worker (16), from a tracking device (13.2, 17) and for issuing a safety command to secure the work area (2), wherein the signal processing unit (19) is configured to determine a hazard potential by comparing the positions of the at least one hazard object (8, 12) and the at least one protection object (8, 16) and to issue the safety command via the interface (6) depending on the determined hazard potential. A method for securing a work area (2) on a track section (3.1, 3.2), in particular by means of such a track safety device (1.1).

The application discloses a low-temperature cooling water cooling air-cooled island cleaning robot path planning method and system, and belongs to the technical field of robot control, comprising: based on the air-cooled island fin layout drawing, initializing the workspace grid, setting the reference parameter; driving the cleaning robot to collect multi-dimensional data, calculating the actual friction coefficient of the measured grid through the main friction coefficient and the torque auxiliary friction coefficient, for the unmeasured grid, linear extrapolation is carried out through the gradient to construct the real-time friction field; obtaining the ideal contact force vector, constructing the kinematics model to obtain the joint required torque, and calculating the joint angle adjustment amount, generating the control instruction and executing through the feedforward friction compensation and PID feedback control, constructing the wear amount estimation model, obtaining the current estimated wear amount, and calculating the core index, generating the rating report, continuously improving the operation efficiency, realizing the unity of the efficiency and equipment safety of the air-cooled island cleaning.

The invention provides a permission configuration method and device. The method comprises the following steps: acquiring a source code and relative path information of a target document edited in a current editing environment; wherein the relative path information is used for representing position information of the target document relative to a root directory of a working area of the current editing environment; analyzing the source code to obtain a document structure object of the target document; performing node traversal on the document structure object to identify a target node corresponding to the interaction component from each node of the document structure object; according to the permission attribute corresponding to the target node and the relative path information, generating an attribute value of the permission attribute in the source code; wherein the attribute value is used for performing permission configuration of the interaction component, so that the accuracy and consistency of permission configuration are improved, the workload of manual permission configuration of developers is reduced, and the development efficiency is improved.

The invention relates to a hanging box pose sensing method and system based on multi-sensor fusion, and belongs to the technical field of industrial automation and intelligent logistics. According to the method, a staged multi-mode sensing strategy is adopted, and high-precision positioning of the hanging box is achieved: in a non-working area, IMU and UWB tight coupling positioning is utilized, the IMU collects 6D pose data in real time, and coarse positioning is achieved in combination with absolute position information provided by UWB; and after entering a working area, starting a visual fine calibration system, acquiring pixel and depth information of the corner fitting of the hanging box by using a depth camera, extracting feature points based on an improved YOLOv5 algorithm, and obtaining a 6D pose with millimeter-level precision through pose calculation. And finally, dynamically fusing IMU, UWB and visual data by adopting an adaptive Kalman filtering algorithm, adaptively adjusting the weight according to environmental noise, and outputting stable and reliable pose information. The system comprises a multi-sensor module, a pose resolving module and a multi-mechanical-arm cooperation module, the positioning precision and the logistics system efficiency are remarkably improved, and the system is widely suitable for scenes such as mine material transportation.

Systems and methods provide endorsement of workspaces operating on Information Handling Systems (IHSs). A primary workspace definition is received by an IHS from a remote orchestrator. A primary workspace is instantiated on the IHS based upon the primary workspace definition, where the primary workspace provides access to a protected resource. The primary workspace definition received from the remote orchestrator identifies applications for operation within the primary workspace and also includes one or more endorsements for each of the applications. Instructions for operation of a applications are validated against an endorsement from the workspace definition. Applications are initiated for use within the workspace upon successful validation of the instructions.

Provided in the embodiments of the present disclosure are a cutting device, a disassembly and recycling apparatus and a cutting method. The cutting device comprises a control module, a frame, a loading assembly, a positioning module and a cutting assembly, wherein the frame is provided with a working area; the loading assembly is movably arranged on the frame, and is configured to bear a battery module and drive the battery module to move into or move out of the working area; the positioning module is arranged on the frame, and comprises a first positioning assembly and a second positioning assembly; and the control module is configured to control the first positioning assembly to position the battery module in a first direction and control the second positioning assembly to position the battery module in a second direction, the first direction intersecting with the second direction, and the control module is configured to control the cutting assembly to cut a housing of the battery module.

The invention relates to the technical field of mechanical arm intelligent control, and discloses a mechanical arm grabbing control system and method based on visual perception, and the system comprises a visual perception module, a strategy planning module and a motion control module; the visual perception module is used for collecting image data of a working area and identifying color, shape and pose information of a target object through image processing as an identification result; the strategy planning module is used for modeling the working area into a two-dimensional grid map, and generating an optimal task sequence including a grabbing sequence, a placement coordinate and a placement posture for a target object according to an identification result and a current working area state; and the motion control module is used for planning the motion track of the mechanical arm according to the optimal task sequence and controlling the mechanical arm to execute grabbing, transferring and placing operations. According to the invention, high-precision and high-efficiency recognition, grabbing and accurate placement of multiple types of target objects in a complex environment can be realized.

The present disclosure relates to a system and method for monitoring air quality and providing recommendation for managing air quality. The system comprises one or more environment monitors, a user device and a server in communication with the environment monitor. The system enables the user to input a contextual information to specify a space and / or use of space in which the environment monitor is placed. The system is configured to provide recommendation based on the designated contextual information. The system offers flexibility in selecting sensors and provide specific, actionable advice tailored to individual environments. The system integrates seamlessly with other smart home devices for automated air quality management. Furthermore, the system allows users to select sensors based on the materials they work with, the processes they apply, and the pollutants of concern within their workspace.

The invention discloses a mechanical arm teleoperation control method and system based on incremental mapping, and the method comprises the steps: carrying out the noise reduction processing of the position and posture of a handle through adaptive low-pass filtering, and achieving the position and posture consistency mapping from a handle space to a mechanical arm working space after coordinate system axis rearrangement and similar transformation mapping; the system provides two kinds of control output of a pose tracking mode and a speed tracking mode, real-time inverse kinematics solution is carried out through a Jacobian matrix and a damping least square method in the speed mode, and resolution scaling and exponential moving average / spherical linear interpolation smooth filtering are carried out on a target pose in the pose mode. And then the handle motion instruction is mapped into a Cartesian instruction or a joint space instruction at the tail end of the mechanical arm, closed-loop execution is conducted through a real-time state feedback link, and the method can be used for scenes such as robot service, teaching, remote operation and data collection.

The invention discloses an intelligent control method for a cutter changing robot of a shield tunneling machine, belongs to the technical field of automatic control, and aims to solve the problems of low hob changing efficiency, inaccurate decision, large positioning error and the like of the shield tunneling machine under a complex stratum. Hob state parameters are collected through multiple sensors, a three-level decision threshold value is constructed, dynamic adjustment is conducted through fuzzy logic, and intelligent hierarchical control over abrasion pre-judgment, early warning and emergency response is achieved. A multi-dimensional weighting model is adopted to calculate the priority of the abraded hob, a cutterhead path is optimized in combination with a dual-objective function, and an efficient execution sequence is generated. In the positioning link, through reverse path planning, PID compensation inertial slippage and cooperation of multispectral imaging and feature matching technologies, hob mark points are accurately extracted, pose deviation is corrected, and it is ensured that the hob mark points enter a robot working space. A double-station conversion table is integrated, synchronous exchange of a new cutter and an old cutter is achieved through hydraulic and servo control, force-position hybrid control is adopted for an end effector, and the disassembly and assembly stability is improved by combining with a torque wrench for staged operation.

The present technology includes a system, protocol, and method by which artificial intelligence agents can interact. In particular, the present technology provides a common workspace, whereby agents have access to a common workspace and can view the state of a workspace. Agents can write to the workspace, making their commands available to all members of the workspace.

Robot calibration is crucial in multi-robot cooperative systems where the inaccuracy of robots can add up and cause large errors in the final trajectory of handled parts or process tools. In this work, a two-step calibration approach is proposed based on artificial neural networks (ANNs) and definition of compensated pose for a master-slave cooperative robot system. Measuring the pose of master and slave robots at different locations in their shared workspace is required to create pairs of joint angles and output pose errors as training data. The generated data is used to train two ANN models for compensating the master-slave relative error and the master robot errors. The master-slave relative error is corrected by introducing a compensated pose for the slave robot with respect to the master robot. A neural network is then trained to predict the error parameters of the compensated pose for the joint angles of both robots as the input. The master robot is then corrected individually using another ANN model to address the absolute accuracy of the cooperative system.Measurements and simulations have been performed on a dual-robot cooperative system before and after geometric calibration. The process of cross validation is carried out to find the best network architecture for the optimal performance in correcting the robots'errors. It has been shown that even after pre-existing model-based calibration of each robot, both the absolute accuracy of the master robot and the relative tracking accuracy can be further improved by the proposed implementation of ANN calibration.

The invention provides an electromagnetic driving system. In one embodiment, the electromagnetic drive system comprises: a) one or more magnetic robots located within a workspace; b) three independent mechanical arms, wherein each independent mechanical arm comprises a movable electromagnetic coil; c) a positioning system for tracking the one or more magnetic robots; the three independent mechanical arms are controlled through multi-objective optimization to ensure a coil configuration space capable of providing a magnetic field for manipulating the one or more magnetic robots in the working space.

The invention provides an industrial operation area multi-view video collaborative analysis method and system based on artificial intelligence. The method comprises the following steps: firstly, acquiring multi-view video data; secondly, based on the working area and the equipment layout, deducing a semantic association relationship among the multi-view video data; according to the semantic association relationship, dynamically adjusting the analysis priority of the multi-view video data through an artificial intelligence model to determine an analysis priority sequence; and according to the determined analysis priority sequence, executing interactive co-processing of the multi-view video data, and finally generating a co-analysis result. According to the technical scheme provided by the invention, the physical layout and the workflow of the industrial site are converted into the semantic association relationship, and the dynamic scheduling analysis resources and the interactive collaborative analysis are performed according to the semantic association relationship, so that the spanning from simple monitoring of a plurality of isolated video streams to intelligent and coherent understanding of the whole operation flow is realized; and the intelligent level and decision support capability of monitoring analysis are improved.

An autonomous mobile robot includes a chassis, tractive elements coupled with the chassis, a primary mover, and an implement assembly. The primary mover is configured to drive the tractive elements to transport the autonomous mobile robot. The implement assembly is coupled with the chassis. The implement assembly includes a deck configured to define a work area configured to support a material, equipment, and tools for transport to a worksite. The implement assembly also includes a lift interface operably coupled with an implement actuator. The lift interface is configured to be driven by the implement actuator to removably couple with the material, equipment, or tool, and lift the material onto the deck for transport to the worksite.

The invention relates to a workpiece detection control method and device, and the method comprises the steps: a first conveying belt of a feeding mechanism transfers a material disc from the upper part of a first jacking platform to a feeding working region, a first moving module transfers a to-be-detected workpiece to a detection belt, and the first conveying belt transfers the material disc to a second jacking platform for stacking and placing; a first photographing mechanism, a second photographing mechanism and a linear scanning photographing mechanism of the detection part sequentially shoot images of the detected workpieces passing through respective working ranges and detect the images, qualified workpieces and unqualified workpieces are obtained, and the unqualified workpieces are classified and marked; unqualified workpieces are classified and temporarily stored in a first discharging mechanism by the discharging mechanism, and qualified workpieces are temporarily stored in a second discharging mechanism by the discharging mechanism; and repeating the steps until the test is finished. The workpiece detection equipment can take a picture of a top view, a side view and a top view line scanning picture of a detected product, qualified and unqualified products are obtained through processing of the processing mechanism, and the technical effect of automatic visual detection is achieved.

Systems and methods for workspace orchestration based on energy scores are described. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include: a processor; and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution by the processor, cause the IHS to: receive, at a local management agent from a workspace orchestration service, one or more files configured to enable the local management agent to instantiate a workspace, where the one or more files are selected or assembled based upon a workspace definition created, at least in part, based upon an energy score; and instantiate the workspace.