4405 results about "Robotic systems" patented technology

The invention provides an intelligent high-performance collaborative welding robot system, which belongs to the technical field of welding robots and comprises a multi-degree-of-freedom welding robot body, an intelligent control system, a high-performance welding power supply and auxiliary equipment. A welding process control module firstly obtains three-dimensional information of a workpiece based on visual inspection to construct a welding path; then selecting matched process parameters according to material characteristics and welding seam shapes; establishing a welding error matrix to monitor the welding process in real time; constructing a parameter error adjustment matrix for dynamic adjustment; analyzing parameter fluctuation by adopting a neural network to identify molten pool characteristics; the pre-trained neural network is used for evaluating the welding seam quality; and finally, a multi-robot collaborative welding strategy is integrated to achieve efficient operation, and the technical problem that in the prior art, welding process parameters in a welding robot are difficult to adjust accurately in real time so as to adapt to complex working condition changes is solved.

The teachings generally provide for a hand-held medical robotic system for use with a surgical tool, the system comprising an instrument comprising a hand-held portion, a tool support coupled to the hand-held portion, and an actuator assembly operatively interconnecting to move the tool support in a plurality of degrees of freedom to place the surgical tool and a localizer. The system additionally comprises a control system configured to determine a state of the surgical tool and determine a position and / or orientation of a reference coordinate system relative to a known coordinate system, activate a guided mode based on a first relationship criteria between the state of the surgical tool and the reference coordinate system, and deactivate the guided mode based on a second relationship criteria between the state of the surgical tool and the reference coordinate system, wherein the first relationship criteria and the second relationship criteria are different.

Disclosed in the present invention are a multi-modal shared teleoperation system and method for a three-arm space robot. The system at least comprises a master-side teleoperation system, a communication module and a slave-side robot system, wherein the master-side teleoperation system at least comprises two force feedback hand controllers, a microphone array and upper computer software, and the slave-side robot system comprises two operating arms each equipped with a gripper at the end, an observation arm having a binocular camera mounted at the end, a vision unit, a force sensor and lower computer software. The method comprises: an operator controlling two operating arms of an extravehicular robot to execute a task, and controlling an observation arm to acquire a better local field of view. In the method, a multi-modal teleoperation method comprising pose control, voice control and force control is fused with autonomous control of a robot by means of a shared control algorithm, and thus, human-robot collaborative control over the position, orientation and contact force of a robotic arm can be realized on the basis of the requirements of the operator, and the robot autonomously executes other relatively simple tasks, thereby reducing the operation burden of operators, and improving the control efficiency.

A multimodal shared telerobotic system and method for a three-arm space robot, the system at least includes a local-site system, a communication module, and a remote-site system, where the local-site system includes two force-feedback haptic devices for left and right hands, a microphone array, and upper computer software; the remote-site system includes two robotic arms provided with end-effectors, an observation arm with a stereo camera installed at an end thereof, two force sensors, a vision unit and lower computer software; an operator can control the two robotic arms of the robot outside a cabin for performing operations, and control the observation arm to obtain a better local view; and a multimodal telerobotic control method of pose control, voice control, and force control is integrated with the robot's autonomous control through a shared control algorithm.

The invention relates to the technical field of robot autonomous navigation and control, and discloses a robot system based on a sensing system, which comprises a multi-mode sensing module for outputting data to a dynamic environment modeling module; the dynamic environment modeling module is used for transmitting the model to the path planning module; the path planning module outputs the path sequence to the neural motion control module; the neural motion control module outputs the control signal to the dynamic execution module; the dynamic execution module is used for receiving the pulse control signal and driving each joint of the robot to execute the path in combination with inverse kinematics solution and a feedback control mechanism; and the collaborative optimization module is in two-way communication with the modeling module, the path planning module and the neural motion control module. According to the method, the contradiction between real-time performance and integrity of environment modeling in a complex scene is solved by fusing cross-modal information complementary characteristics of binocular vision, millimeter-wave radar and inertial data and combining mathematical representation of a hypergraph topology model on a dynamic obstacle interaction relationship.

A robotic surgical system. a surgeon console operatively coupled to a patient console and one or more surgical instruments. A surgeon computer is coupled to or integrated with the surgeon console, the surgeon computer further operatively connected to the one or more surgical instruments; A surgical robot is coupled to a robotic surgery control system and a feedback loop. The robotic surgery control system includes or is coupled to an artificial intelligence (AI) system. A feedback loop is further configured to receive performance-related data from the one or more sensors, the data analyzed by the robotic surgery control system or the AI system to dynamically adjust the robotic system's operation as needed. A data extraction module retrieves, from the robotic surgery control system or the AI system. one or more programmed steps executed by the surgeon for positioning at least one of the surgical instruments during the surgical procedure.

An example robotic system includes a robotic arm configured to move in multiple degrees of freedom and a control system including one or more processing devices. The one or more processing devices are programmed to perform operations including: identifying an object in the environment accessible to the robotic arm based on sensor data indicative of the environment; determining that a component associated with the robotic arm is within a predefined distance of the object; and controlling the robotic arm to move the component toward or into alignment with the object in response to the component being within the predefined distance of the object.

Disclosed is a method and tidying robot system that performs it. A robot of a tidying robot system receives a starting location, a target cleaning area, and obstructions in its path navigating the target cleaning area. It determines a tidying strategy including vacuuming and obstruction handling. It executes the tidying strategy, vacuuming the target cleaning area and moving and / or avoiding obstructions, which are tidyable and / or movable objects. Where the obstruction may be picked up, the robot determines and executes a pickup strategy. Where the obstruction may be relocated but not picked up, it pushes the obstruction to a different location. Where the obstruction cannot be relocated / picked up, it alters its path to avoid the obstruction. The robot determines if the dirt collector is full, and if so, navigates to a base station configured to charge the robot and empty the dirt collector. Otherwise, it continues to execute the tidying strategy.

The invention relates to a robot distribution task priority scheduling method, which comprises the steps of inputting priority scoring parameters to a preset dynamic weight scoring model to obtain priority scores of distribution tasks, the priority scoring parameters comprising task emergency degree, distribution distance, goods weight and time efficiency requirements, the dynamic weight scoring model represents the influence degree of each priority scoring parameter on priority scoring; acquiring conveying capacity parameters of the plurality of robots, and allocating the robots to the delivery tasks according to the conveying capacity parameters and the priority scores of the delivery tasks; determining a planning path required by the robot to complete the corresponding distribution task; in the moving process of the multiple robots, the moving information of the multiple robots is obtained in real time, and whether path conflicts exist in the multiple robots or not is detected; and under the condition that the existence of the path conflict is detected, the planned path of the robot is optimized based on the conflict solving strategy so as to avoid collision of a plurality of robots. And efficient cooperative operation of a plurality of conveying robot systems is realized.

A system includes a camera, a robot, and a management system. The camera is configured to capture one or more images of a material handling environment. The material handling environment normally includes one or more items. The robot is at least in part configured to move along a travel path relative to the items, and the robot is configured to pick the items. The management system is configured to monitor the material handling environment through the images from the camera. The management system is configured to determine dynamically multiple picking solutions for the items in real-time while the robot moves along the travel path.

The invention discloses a method for dynamically establishing a knowledge graph based on multi-source heterogeneous data fusion, and belongs to the field of intelligent robot systems. Firstly, multi-source heterogeneous data fusion is carried out, a distributed Kalman filter network is constructed, filters are designed for different sensors, and data space-time alignment is realized; carrying out conflict detection and resolution by adopting an improved D-S evidence theory, and dynamically adjusting a fusion weight through a confidence evaluation model; secondly, constructing a dynamic knowledge graph, and establishing a three-layer graph structure comprising an environment entity, a space-time relationship and probabilistic reasoning; designing an event-triggered incremental updating algorithm, starting local reconstruction when the environmental change degree exceeds a threshold value, and introducing an LSTM memory network to enhance the time sequence reasoning capability; and finally, constructing a reinforcement learning model based on the dynamic knowledge graph, designing a multi-target reward function, and finally training until the model is converged. According to the method, the positioning error is reduced through EKF / UKF combined filtering, the multi-sensor data space alignment error is reduced through a conflict resolution mechanism, and the execution efficiency and the coping capacity of the omni-directional mobile robot in a complex dynamic environment can be improved.

A Level IV fuel-saving robot system for ACE HDTs of the present disclosure focuses on the minimization of actual fuel consumption (L / 100 km) for long-haul freight at first based on an electrical power split device (ePSD) and a mixed hybrid powertrain architecture. A basic model Level I fuel-saving robot realizes a longitudinal L1 automatic driving function through a predictive adaptive cruise (PACC) technology within an Operational Design Domain (ODD) for highways and reduces the actual fuel consumption of an ACE HDT by more than 20% compared with modern diesel HDTs, and the energy-saving and emission-reducing effect of the basic model Level I fuel-saving robot is decoupled from both the technical level of a vehicle engine and the driving level of a driver; an advanced Level IV fuel-saving robot has a L4 automatic driving function within the ODD for highways, operates in a “shadow mode” or “detached mode”, automatically generates a discrepancy report or detachment report, completes the “3R” batch validation for an L4 system on a billion mile scale quickly with high cost effectiveness on the premise of ensuring the traffic safety of existing road users and reduces the total validation expense by more than 65% compared with the modern HDT with internal combustion engine equipped with the L4 system, promoting the early commercialization of the Level IV fuel-saving robot.

Systems and methods that allow robots to perform tasks for users are provided. A robot may comprise one or more robotic arms and / or a mobile base. The arms may be controlled by electric actuators and may have six or more degrees of freedom. The robot may have sensors which can be accessed remotely. Robots may have varying levels of autonomy, including, for example, full teleoperation (in which a human can have detailed control over the robot) or full autonomy (in which the robot can complete a task without any human intervention). Various entities can interact with individual robots or groups of robots over a network, locally, directly or in person, or any combination thereof. A management system can allow entities to control and / or monitor the robots.

Co-manipulation robotic systems are described herein that may be used for assisting with laparoscopic surgical procedures. The co-manipulation robotic systems allow a surgeon to use commercially-available surgical instruments while providing benefits associated with surgical robotics. Further, the co-manipulation robotic system may operate in multiple modes to enhance usability and safety, while allowing the surgeon to position the instrument directly with the instrument handle and further maintain the desired position of the instrument or a desired force applied by the instrument using the robot arm. For example, the robot arm may be moved automatically to maintain a constant tension force on an anatomical structure via the instrument in a constant tension mode.

The invention relates to the field of agricultural robots, and discloses an agricultural spraying robot system with visual navigation, and the system comprises a multi-mode sensing module, a dynamic environment modeling module, a time sequence prediction module, a multi-target path planning module, a spraying control module, and a hardware acceleration unit. The method comprises the steps that a dynamic semantic map is constructed through multi-modal perception, agricultural semantics and an attention mechanism are fused to predict an obstacle trajectory, a safe path is generated in combination with multi-objective optimization, the spraying amount is adjusted based on crop density, and real-time operation is ensured by means of hardware acceleration. According to the method, a dynamic semantic map is constructed through multi-modal perception, agricultural semantics is combined to enhance trajectory prediction, a safe path is generated by utilizing multi-objective optimization, the spraying amount is adaptively adjusted according to the crop density, and real-time control is realized by adopting heterogeneous hardware acceleration; the defects of a traditional agricultural robot in the aspects of navigation precision, obstacle avoidance safety, resource utilization and response speed are overcome, and the intelligent level of complex farmland operation is improved.

The invention discloses a multi-modal fusion real-time environment monitoring visual robot system, and relates to the technical field of real-time vision. The system comprises a multi-mode sensing module, and is equipped with various sensors such as a binocular stereo camera and a laser radar to collect environment data. The heterogeneous data preprocessing unit cleans and downsamples data such as images and point clouds; the space-time alignment fusion module realizes multi-source data space-time registration and synchronization; the environment semantic understanding engine constructs an environment semantic graph through a multi-branch network in combination with an attention mechanism; the abnormal event detection unit identifies abnormity based on a historical data model; the path planning and decision-making module integrates multiple targets to generate an optimal path; the autonomous movement execution module controls the robot to move and operate; and the cloud cooperative control center supports model updating and remote intervention. According to the invention, through cooperative work of all the modules, full-process intelligentization of environment monitoring data acquisition, processing, analysis and decision making is realized.

In various examples, a technique for generating a path between a current location and a target waypoint is disclosed that includes receiving a route plan that is associated with a plurality of waypoints representing locations in a physical environment. The technique also includes identifying a search space that includes the route plan, and identifying a target waypoint of the plurality of waypoints—the target waypoint being in a portion of the search space between a current location of a mobile robot and an end waypoint of the route plan. A path between the current location of the mobile robot and the target waypoint may then be generated.

A payload for an inspection robot. The payload includes a payload coupler pivotally coupled to the inspection robot to pivot in a plane substantially parallel to a direction of travel of the inspection robot along an inspection surface plane; and a sensor frame pivotally coupled to the payload coupler to pivot in the plane substantially parallel to the direction of travel. The payload further includes: a first sensor housing including a first phased array ultra-sonic (UT) sensor aligned with the direction of travel. The first sensor housing is pivotally coupled to the sensor frame to pivot in a plane substantially perpendicular to the direction of travel. The payload further includes a second sensor housing comprising a second phased array UT sensor aligned with the direction of travel. The second sensor housing is pivotally coupled to the sensor frame to pivot in the plane substantially perpendicular to the direction of travel.

The invention discloses a building robot task planning and skill learning method and system, and relates to the technical field of intelligent construction and building robot control, and the method comprises the steps: receiving construction target description and construction environment information through a multi-modal task-skill collaborative generation model; and generating a structured semantic vector and reasoning a construction planning graph containing a plurality of subtasks. And collecting operation behavior parameters of the building robot in each subtask according to the construction planning graph, constructing an operation sample, and inputting the operation sample into the multi-modal task-skill collaborative generation model for skill learning and action instruction generation. And in the construction execution process, various sensing data are fused for real-time judgment, and if the task execution state is inconsistent with the planning state, the multi-mode task-skill collaborative generation model adjusts an instruction based on the latest state and outputs a reasoning chain. According to the method, the deployment efficiency and task adaptability of the robot system in actual construction are improved, and a foundation is laid for man-machine cooperation and unmanned construction in the field.

Co-manipulation robotic systems are described herein that may be used for assisting with laparoscopic surgical procedures. The co-manipulation robotic systems allow a surgeon to use commercially-available surgical tools while providing benefits associated with surgical robotics. Advantageously, the surgical tools may be seamlessly coupled to the robot arms using a disposable coupler while the reusable portions of the robot arm remain in a sterile drape. Further, the co-manipulation robotic system may operate in multiple modes to enhance usability and safety, while allowing the surgeon to position the instrument directly with the instrument handle and further maintain the desired position of the instrument using the robot arm.

The invention discloses a customer service robot system integrating knowledge base question and answer retrieval and work order processing, which comprises a natural language understanding and generating module, a knowledge retrieval module, a business system integration module, a dialogue management and decision module and a cue word management module, and relates to the technical field of artificial intelligence. Through cooperation of a large language model and a dialogue management module, the system realizes multiple rounds of deep understanding of a natural language, and can actively guide a user to clarify a demand, such as gradually inquiring an equipment model and fault details during repair, memorizing a dialogue context and avoiding information omission. Compared with traditional regular customer service, the method has the advantages that the accuracy of understanding complex problems is remarkably improved, open dialogue scenes such as technical consultation and fault diagnosis are supported, user interaction experience is closer to manual service seats, and the problems that multi-round dialogue understanding is limited, progress data cannot be obtained in real time, multiple knowledge bases are fused, and the automation degree of the business process is low are solved.

The invention provides an intelligent spraying composite robot system based on a large language model and a method thereof, and relates to the field of intelligent robots and automatic spraying, the intelligent spraying composite robot system comprises a chassis, a mechanical arm, a spraying gun, a camera, an instruction receiver and a controller; a mechanical arm and an instruction receiver are carried on the chassis; spray guns and cameras are mounted on the mechanical arms; the instruction receiver receives a natural language voice instruction, analyzes semantics through a large language model, and generates an action instruction; the controller comprises a motion control module, a three-dimensional point cloud data acquisition module, a feature point extraction module, a track planning module and a spraying operation module; the method improves the man-machine interaction, reduces the use threshold of the robot, is easy to operate, gives play to the spraying advantages of the composite robot, does not need to program in mainstream offline simulation software, can generate a spraying path with adjustable and controllable parameters only by collecting the point cloud template of the workpiece and selecting the feature points, and can be widely applied to furniture, furniture and the like. And spraying operation in the fields of automobiles, aerospace and the like.

The invention discloses a robot system for steel structure welding, relates to the field of steel structure machining equipment, and aims at solving the problem that a steel structure can be welded by collecting robot track data and a welding seam image in the welding process, constructing a track continuity evaluation model, identifying a path change trend and fusing an image structure and track change information. The position and confidence of a track interruption section are recognized, so that the high-precision recognition and automatic recovery capability after path interruption is improved; a smooth compensation track is generated by adopting third-order Bessel interpolation based on starting and ending points of an interruption section, curvature and posture consistency registration with an original track is completed, and continuity and stability of a welding path are ensured; multi-modal data such as current, voltage, temperature, acoustics and welding seam images are collected through multiple channels, welding abnormity is recognized, state feature vectors are formed, and the problems such as splashing abnormity and welding seam deviation can be found in real time; through multi-dimensional analysis and dynamic adjustment of the whole welding process, the stability, intelligence and adaptability of the welding system are remarkably improved.

Co-manipulation robotic systems are described herein that may be used for assisting with surgical procedures, including laparoscopic surgery. The co-manipulation robotic systems allow a surgeon to use commercially-available surgical tools while providing benefits associated with surgical robotics. Advantageously, the surgical tools may be seamlessly coupled to the robot arms using a disposable coupler while the reusable portions of the robot arm remain in a sterile drape. Further, the co-manipulation robotic system may operate in multiple modes to enhance usability and safety, while allowing the surgeon to position the instrument directly with the instrument handle and further maintain the desired position of the instrument using the robot arm.

A robotic system includes a robotic arm that interacts with an object during operation. It further includes a locking component that, during operation, locks a multi-position component in an operating position. Responsive to a triggering event, locking of the multi-position component in the operating position is released and the multi-position component moves away from its operating position, facilitating separation between the robotic arm and the object.

The invention provides an automatic deployment method for a robot system, and the method comprises the steps: collecting three-dimensional space data of a target environment through a multi-mode sensor array which comprises a laser radar, a binocular vision camera and an inertial measurement unit; fusing sensor data based on a space-time synchronization algorithm to generate an environment feature matrix; analyzing a user task instruction, extracting a task target and decomposing the task target into time, path priority and safety threshold parameters; constructing a multi-objective optimization model, and generating a candidate path set; adopting an improved Pareto leading edge screening algorithm to select an optimal path sequence; executing virtual verification and adjusting path deviation in the digital twin environment; and the physical execution mechanism is driven to implement deployment operation, and the local path re-planning module is triggered when the deviation is detected to exceed a threshold value. According to the invention, the accuracy, safety and efficiency of path planning can be improved, and the energy consumption and time cost are reduced.

The invention discloses a wheel-foot robot, a robot system, a motion control method and a motion control system, and the motion control system comprises a track publishing module which is used for converting the expected speed and position of a robot trunk into a state track; the predictive control module is used for constructing a model predictive control algorithm which takes the expected trajectory as input and takes the system state and the control input quantity as output, and optimizing the system state and the control input quantity in real time; the state estimation module is used for estimating the motion state of the robot by fusing the sensor data; and the whole body control module is used for constructing a multi-task control algorithm which takes the expected trajectory and the motion state as input and takes the joint torque, the joint speed and the joint position as output and has priorities or weights. According to the method, global prediction and optimization can be realized, the complexity of each optimization calculation can be effectively reduced, and the response speed and the real-time processing capability of a robot system are improved.

Co-manipulation robotic systems are described herein that may be used for assisting with surgical procedures, including laparoscopic surgery. The co-manipulation robotic systems allow a surgeon to use commercially-available surgical tools while providing benefits associated with surgical robotics. Advantageously, the surgical tools may be seamlessly coupled to the robot arms using a disposable coupler while the reusable portions of the robot arm remain in a sterile drape. Further, the co-manipulation robotic system may operate in multiple modes to enhance usability and safety, while allowing the surgeon to position the instrument directly with the instrument handle and further maintain the desired position of the instrument using the robot arm.

The invention discloses a shaping robot, a shaping system and a grain processing method thereof. An integrated moving and transferring device is used as a chassis for bearing all modules; the shaping industrial robot is used for driving a cutter on the mechanical arm to conduct shaping machining. The medicine scrap sucking and cleaning device is used for cleaning scraps generated by processing; the tool changing magazine is used for placing and managing tools and comprises a quick-changing tool rest, and a detection sensor used for detecting whether the tools exist or not is arranged on the quick-changing tool rest; the control system comprises a coordinate system management module, a tool path planning module, a robot kinematics module, a collision detection module, a motion simulation module and a robot program generation module. Automatic machining positioning, automatic machining path planning and automatic cutting tool switching and management can be achieved; the automation degree of grain cutting machining is effectively improved; in the shaping process, temperature and contact force detection sensors are used for detection, and early warning protection in the machining process is achieved.

The invention discloses an intelligent detection robot system for a valve hall assembly of a power converter station and a detection method. A robot body adopts an overhead six-axis series mechanical arm structure and is suspended in the center of the top of a valve hall; the intelligent path planning module performs optimization by combining a probability path diagram method with an improved A * bidirectional search algorithm, and ensures that the robot has efficient obstacle avoidance capability and an optimal moving track in a complex environment; the point cloud data detection and processing module adopts a multi-sensor fusion technology, combines an ICP algorithm to complete point cloud registration, and generates a three-dimensional model with labels. Compared with traditional manual detection, the system has the advantages that the detection efficiency and safety are improved, the labor cost is remarkably reduced, the development of intelligent maintenance means of electric power facilities is promoted, and technical guarantee is provided for stable operation of a converter station.