152 results about "Mobile manipulator" patented technology

The invention belongs to the technical field of mobile mechanical arm grabbing, and provides a mobile mechanical arm grabbing control method and system based on machine vision, and the method comprises the steps: collecting an image in the moving process of a mobile mechanical arm according to a preset grabbing path, recognizing a dynamic obstacle in the image through an RT-DETR algorithm, and generating a prediction track of the dynamic obstacle, collision detection is conducted on a preset grabbing path of the movable mechanical arm, an obstacle avoidance track switching instruction is generated by combining the current time point of the mechanical arm with the predicted collision time point of the dynamic obstacle, trajectory tracking is conducted on the obstacle avoidance track of the mechanical arm, a model reference self-adaptive control algorithm is adopted, a reference model is established, and obstacle avoidance is achieved. According to the method, mechanical arm vibration caused by obstacle avoidance track switching is effectively restrained, interference of vibration on grabbing stability is reduced, and the operation precision and reliability of the mechanical arm in a dynamic obstacle avoidance scene are remarkably improved.

The invention relates to a clamping control method of a movable mechanical arm. The clamping control method is used for solving the problem of collaborative optimization of stability and precision in clamping operation. According to the method, a motion coupling factor and a contact force gradient mode length are calculated in real time through a dynamic coordination module, base-world coordinate system conversion is combined to realize bidirectional constraint of chassis speed and mechanical arm torque, instability caused by sudden load change is inhibited, a time-varying sliding mode surface and an anti-buffeting control law are adopted for sliding mode control, and the stability of a mechanical arm is improved. Dynamic boundary layer thickness and adaptive gain are introduced, control parameters are further optimized through a double-delay depth deterministic strategy gradient, and a multi-target reward function is designed. According to the method, the robustness of the system is remarkably improved through closed-loop optimization, and the stability and precision of the movable mechanical arm in the clamping operation are improved.

The invention relates to the technical field of ink jet control, and discloses an intelligent ink jet control system and method, a robot and a storage medium. The method comprises the following steps: firstly, acquiring surface contour data and color information of an object to be jetted through a laser ranging device, and constructing an object surface feature vector; a target ink jet area is determined through area spray adaptability evaluation; then, semantic information of ink jet content is obtained, semantic element weights are calculated, and ink jet parameter constraints including an ink droplet size threshold value, an information level presentation rule and the like are generated in combination with a target area range; generating an intelligent ink-jet scheme according to the constraint, and controlling an ink-jet device to form a target pattern; and finally, a moving path of the moving mechanical arm is generated based on a cubic spline interpolation algorithm, and the target pattern acts on the target area. The method can adapt to complex surface forms and various materials, the ink jet process is accurately controlled, patterns are accurately presented and stably attached, and the ink jet effect and the information transmission effectiveness are improved.

The invention discloses a decoupling motion control method and system for a four-footed mobile operation robot considering the acting force of a mechanical arm, and belongs to the field of motion control of foot type mobile operation robots. An expected motion track input by a user can be tracked by performing planning through linear model prediction control MPC; on the basis of the tracked motion trail, mechanical arm joint control torque is calculated through a mechanical arm dynamic model and PD feedback; through nonlinear model predictive control NMPC planning, a quadruped robot whole-body motion trail of mechanical arm acting force obtained through calculation according to a mechanical arm dynamic model is considered, and an expected speed trail and an expected force trail input by a tracking user are obtained; and according to an expected speed trajectory and an expected force trajectory input by a tracking user, a whole body controller WBC based on hierarchical quadratic programming calculates a joint driving torque for tracking the expected trajectory according to task priorities. According to the method, the acting force / torque of the mechanical arm to the robot body is considered during motion control of the quadruped robot, and decoupling control over the mechanical arm and the quadruped robot in the quadruped mobile operation robot is achieved.

The invention belongs to the technical field of robot control, and discloses a visual servo intelligent robust control method for a mobile mechanical arm for a complex operation task, which comprises the following steps of: 1, acquiring a working scene image, and calculating a space coordinate of a target feature point in real time through a projection transformation model; step 2, dynamically inhibiting visual measurement noise by adopting adaptive Kalman filtering, generating a feedforward compensation signal through an integral sliding mode observer, and decoupling chassis slippage disturbance; step 3, inputting the pose signal into a radial RBF neural network, designing an RBF gain scheduler, and adjusting an output proportion-integral gain in real time to suppress external time-varying disturbance; 4, adopting a hybrid visual servo mode switching mechanism, and generating a mobile platform control instruction through an integral sliding mode surface in a position servo mode; and 5, designing a three-order composite controller to drive the mechanical arm so as to realize accurate grabbing. According to the method, the grabbing deviation caused by kinematics uncertainty of the mobile platform and dynamic environment disturbance is eliminated.

The invention discloses a mobile manipulator man-machine collaborative operation motion control method based on quadratic programming, which comprises the following steps of: 1, constructing a kinematic equation of a mobile manipulator, and designing a quadratic programming solver to describe a mobile manipulator coordinated control problem in a man-machine collaborative operation scene; 2, a constraint function of a quadratic programming solver is designed, equality constraints are utilized to meet end speed tracking in a cooperative task, and inequality constraints are utilized to realize joint limit position avoidance; 3, designing a translation operability index, a collaborative operation formation optimization index, a relaxation cost dynamic control function and a joint speed cost dynamic control function which are suitable for a man-machine collaborative task, and integrating the indexes and the functions into a target function of a quadratic programming solver, and a mobile mechanical arm man-machine collaborative operation motion control frame based on quadratic programming is formed.

The utility model discloses a nitrogen bin for automatically storing wafers, which belongs to the field of storage equipment, is used for solving the problem of low efficiency of manual wafer storage and taking in the prior art, and comprises a bin body, a goods shelf, a conveying line and a material taking mechanism, the bin body is provided with a closed storage cavity, and the bin body is provided with a feed port and a discharge port which are communicated with the storage cavity; the goods shelf is arranged in the storage cavity and is used for placing wafers; the conveying line is arranged in the storage cavity and connected with the feeding port and the discharging port. The material taking mechanism comprises a moving module and a mechanical arm which are arranged in the storage cavity and connected with each other, the moving module is used for driving the mechanical arm to move between the goods shelf and the conveying line, and the mechanical arm is used for grabbing the conveying line or the wafers on the goods shelf and placing the wafers on the goods shelf or the conveying line. According to the wafer automatic storage nitrogen bin, the conveying line, the moving module and the manipulator cooperate to realize automatic storage and taking functions of wafers, so that the efficiency and the accuracy of wafer product storage and taking operation are improved.

A robot comprises a mobile base, a robotic arm operatively coupled to the mobile base, and at least one interface configured to enable selective coupling to at least one accessory. The at least one interface comprises an electrical interface configured to transmit power and / or data between the robot and the at least one accessory, and a mechanical interface configured to enable physical coupling between the robot and the at least one accessory.

The invention provides a robot mobile mechanical arm coordinated motion planning method and system which can be applied to the technical field of robot control and the like. The method comprises the steps that space-time joint trajectory planning is achieved based on a multi-type algorithm, a moving base incomplete constraint path and a moving mechanical arm tail end path are generated through a three-dimensional occupation map obtained through environment perception, an improved preset trajectory optimization algorithm is adopted to constrain speed / acceleration, and smoothness and obstacle avoidance capacity are improved; a vision-motion collaborative optimization scheme is provided, joint speed and holder control quantity are solved at the same time through quadratic programming, and perception information gain maximization and motion stability are considered on the premise that mechanical constraints and an environment distance field are met; meanwhile, a re-planning mechanism of dynamic risk perception is developed, and when the environment changes or enters a visual blind area, real-time adjustment of a local track is achieved by enhancing safety distance constraint and forcing visibility requirements.

The invention discloses a dynamic obstacle avoidance method for a mobile manipulator based on visual perception and null-space control, which comprises the following steps: dynamically adjusting the weight distribution of the movement of a mobile platform and the movement of the manipulator in a whole task based on real-time environment perception information and the real-time movement state of the mobile manipulator; the method comprises the following steps: detecting an obstacle in a working environment in real time through a visual perception module, and predicting a movement track of the obstacle in combination with a Transform network model based on a graph structure; according to the real-time position and the predicted track of the obstacle, motion parameters are dynamically adjusted, and a speed potential field function model associated with the shortest distance between the obstacle and the mobile mechanical arm is designed by adopting a speed potential field method; according to the method, the rejection speed of an end effector is introduced to compensate the interference of an obstacle on the end effector, and the rejection speed is combined with the expected speed of the end effector and the obstacle avoidance guiding speed obtained by solving through a speed potential field method, so that dynamic obstacle avoidance of the robot in the process of executing a set task is realized; and the task execution path is optimized while the obstacle is effectively avoided.

The present invention discloses a trajectory tracking method for a variable-load mobile manipulator based on reinforcement learning and model predictive control. First, a system model of the mobile manipulator established based on Lagrange's equation is obtained, and the dynamic equation is derived through the system kinetic energy, potential energy, and generalized force formulas. The model predictive control (MPC) module is based on this model, uses the discrete state equation to predict the future state, and obtains the control input by optimizing the cost function. The reinforcement learning (RL) module defines a specific state space, action space, and reward function, and trains the agent using the Q-learning algorithm. In the collaborative control stage, the weight coefficient is dynamically adjusted according to the system state, and the control inputs of MPC and RL are fused. The present invention effectively solves the problem of trajectory tracking of variable-load mobile manipulators, significantly improves the trajectory tracking accuracy, enhances the system adaptability and robustness, and has broad application prospects in the fields of industrial manufacturing, logistics warehousing, etc.

The invention discloses an automatic mounting mechanical arm for a tunnel pipeline. According to the core scheme, the automatic mounting mechanical arm comprises a walking track mechanism, a manipulator mechanism, a pipeline clamp mechanism and a pipeline butt joint compensation mechanism. The walking track mechanism is used for driving the mechanical arm mechanism to move in the tunneling direction and the section horizontal direction, the mechanical arm mechanism comprises at least one set of mechanical arms with a single-action / linkage control mode and is used for grabbing a to-be-installed pipeline and adjusting the space posture, and the pipeline clamp mechanism is arranged at the tail end of the mechanical arms. And the pipeline butt joint compensation mechanism is used for achieving flexible clamping and rigid locking of the pipeline, and the pipeline butt joint compensation mechanism is used for compensating the posture error of the butt joint position of the pipeline to achieve accurate alignment of the flange. Full-automatic grabbing, transferring, positioning and butt joint of pipelines in a tunnel can be achieved, the pipeline installation efficiency and butt joint precision are greatly improved, the manual operation intensity is reduced, and the robot is suitable for various pipeline installation working conditions of shield construction and high in universality.

The invention discloses an intelligent transfer and multi-station cooperative assembly system and method for sheet pipe truss machining. The intelligent transfer and multi-station cooperative assembly system comprises an electromagnetic rail, and an AGV trolley is movably connected to the electromagnetic rail; a truss transferring manipulator and a truss moving manipulator; the shot blasting machine is used for carrying out shot blasting treatment on the rod piece; the truss boxing robot is used for carrying out boxing treatment on the rod pieces subjected to shot blasting treatment; and the forklift robot is used for conveying the rod pieces on the AGV trolley at the material receiving station to the joist barrow, and the rod pieces are conveyed to the assembling station, the welding station, the polishing and shape adjusting station and the paint shed through the joist barrow. According to the invention, the closed-loop assembly line work of cutting-cleaning-transportation can be realized, rhythm faults caused by manual intervention are reduced, the overall productivity is improved, the forklift robot can accurately receive the rod pieces transported by the AGV and convey the rod pieces to a material receiving station, the traditional material transfer and stockpiling time is eliminated, and the production cycle is shortened.

A robot comprises a mobile base, a robotic arm operatively coupled to the mobile base, and at least one interface configured to enable selective coupling to at least one accessory. The at least one interface comprises an electrical interface configured to transmit power and / or data between the robot and the at least one accessory, and a mechanical interface configured to enable physical coupling between the robot and the at least one accessory.

The utility model provides a four-axis truss, and relates to the technical field of four-axis trusses. Positioning blocks are fixedly mounted at the upper ends of the two ends of the fixed cross beam respectively; and a first drag chain is mounted on the front side wall of the fixed cross beam. The position of the movable longitudinal beam is firstly adjusted left and right, then the position of the movable longitudinal beam is adjusted front and back, then the position of the adjusting beam is moved up and down, meanwhile, the position of a connecting shaft below the adjusting beam can also move along with the adjusting beam, the manipulator clamp can move front, back, left, right, up and down, and the position of the clamp can be accurately adjusted through movement in six directions (X / Y / Z axis translation). The four-axis truss is suitable for objects of different shapes and sizes, is particularly suitable for grabbing in complex arrangement or narrow space, and solves the problem that the position of a manipulator clamp on the four-axis truss needs to be automatically adjusted due to the fact that the four-axis truss mostly adopts a fixed guide rail layout and the placement positions of the objects are different, otherwise, the manipulator clamp cannot stably clamp the objects below.

A robot includes a guide, a mover, a hand, a deformation acquirer, a orientation adjuster, and a controller. The mover is installed to the guide and movable in a direction that the guide guides along. The hand is installed to the mover and holds a substrate. The deformation acquirer acquires information on a deformation of the guide. The orientation adjuster adjusts an orientation of the hand according to the deformation of the guide acquired by the deformation acquirer. The controller controls operation of the orientation adjuster. The controller adjusts the orientation of the hand performing a holding operation on the substrate to be transferred by using the orientation adjuster based on the information on the deformation of the guide.

The utility model relates to a pull buckle jig value board machine which comprises a working table, a conveying rail is arranged on the upper side of the working table, a feeding conveying belt is arranged, the feeding conveying belt is used for inputting no-load tools, a PCB material frame is arranged, and a PCB positioning disc is used for placing PCBs and positioning the PCBs. The feeding manipulator is used for moving the PCB from the material rack to the PCB positioning disc; the steel sheet platform is used for placing a steel sheet; the moving manipulator is used for moving the positioned PCBs to the no-load tool position of the feeding conveying belt; the method comprises the following steps: arranging a steel sheet platform, moving a steel sheet at the position of the steel sheet platform to a no-load tool position, arranging a PCB positioning disc, taking out a PCB from a PCB rack, firstly placing the PCB in the PCB positioning disc for positioning, and then moving the PCB to the no-load tool position through a moving manipulator, so that the positioning accuracy is high when the PCB is placed on the no-load tool without a visual detection structure, and the positioning accuracy is high. And meanwhile, a visual detection structure is not needed, and certain production efficiency can also be improved.

A system includes: one or more memories; and one or more processors configured to, acquire three-dimensional data of an environment at a first timing; extract a plurality of pieces of motion data from the one or more memories, the motion data including the target end-effector position and attitude and a swept volume that does not contact the environment; start the task based on first motion data, the first motion data being one of the extracted pieces of motion data; when determination is made that the mobile manipulator comes into contact with the environment, extract, as second motion data, motion data including a swept volume that does not contact the environment based on the three-dimensional data acquired in real time; and generate a transition trajectory for transitioning from a trajectory of the first motion data to a trajectory of the second motion data.

A robot system includes: a mobile manipulator that has a mechanism for moving on a floor and a mechanism for holding an object; a workbench robot that is fixed to a workbench and that has a mechanism for holding an object on the workbench; and a controller that controls an operation of each of the mobile manipulator and the workbench robot, in which the controller causes the workbench robot and the mobile manipulator to perform a passaging process of cells, the passaging process including conveyance and installation of a container containing the cells between the workbench and another experimental facility.

An energy harvesting system is disclosed including a plurality of beams connected to form a structural frame, and a plurality of solar concentrator panels mounted on the structural frame to provide a solar concentrator array for reflecting solar radiation onto a plurality of receiver tubes configured to transport a heat transfer fluid to be heated. The beams are configured to support a mobile manipulator for travel along the structural frame for performing at least one operation on the array. A mirror apparatus used in a solar concentrator panel is also disclosed and includes an elongate thin-walled closed structural beam, and a mirror extending along and mounted to a surface of the closed structural beam in a transversely deformed condition to cause the mirror to have a transverse curvature that is selected to focus the solar radiation onto a receiver tube.

This invention discloses a method and apparatus for planning the end-effector path following configuration of a mobile robotic arm based on convex set graph optimization and penalty function constraints. The planning method includes the following steps: S1: After generating the reachability graph of the robotic arm, the reachability graph is projected onto the base plane of the robotic arm to generate the inverse reachability graph of the robotic arm; S2: Based on the inverse reachability graph and the end-effector target path of the robotic arm, the feasible configuration set of the mobile chassis corresponding to each end-effector target path point is solved; S3: Based on the feasible configuration set of the mobile chassis, the feasible configurations of the mobile chassis are initially planned to obtain the initial configuration sequence of the mobile chassis; S4: The initial configuration sequence of the mobile chassis is secondarily planned to obtain the optimal configuration sequence of the mobile chassis; S5: Based on the optimal configuration sequence of the mobile chassis, the end-effector target path, and the motion relationship between the mobile chassis and the end-effector of the robotic arm, the complete configuration sequence of the mobile robotic arm is calculated.

The utility model relates to automatic tapping equipment for a water tank, which comprises a machine table, a three-axis moving manipulator, a reciprocating conveyor belt, a drilling main shaft module and a polishing main shaft module, and is characterized by further comprising three groups of positioning and fixing modules and three groups of overturning modules, a positioning and fixing module, an overturning module, a positioning and fixing module and a positioning and fixing module are sequentially and transversely arranged on the machine table at equal intervals, three-axis moving manipulators are arranged on the side edges of the three positioning and fixing modules, and a drilling main shaft module, a drilling main shaft module and a grinding main shaft module are sequentially arranged on the corresponding three-axis moving manipulators. The reciprocating conveying belt is located in front of the three sets of positioning and fixing modules and the overturning module, four sets of feeding discs are arranged on the reciprocating conveying belt, the whole structure is simple, only one person is needed for placing the water tank and collecting the water tank after the water tank is completed, the labor cost is greatly reduced, and automatic machining of the water tank is achieved.

The present application relates to unmanned system multi-agent control technical field, especially related to a kind of wheeled mobile manipulator coordination control method, system and device.It includes the following steps: establishing wheeled mobile manipulator model, solving target accessibility area;Calculate the maneuverability index of wheeled mobile manipulator;Calculate the maximum linear velocity and angular velocity of wheeled mobile manipulator, obtain the velocity ellipsoid model of wheeled mobile manipulator;Design the joint state space of multi-agent, design the joint action space of multi-agent;Control algorithm flow is constructed;Set the task scene of wheeled mobile manipulator coordination control algorithm, set training hyperparameter, design task evaluation index;Training setting is carried out, the success rate of task is recorded at the end of training cycle, the effectiveness of flow.The present application solves the problem of solving kinematic equation or objective function optimization under the condition of complex model structure and high dimension.The present application achieves the technical effect of reducing complexity calculation.

The present application relates to visual robot automatic welding technical field, specifically a kind of laser visual guidance robot automatic welding hand-eye calibration method, including steps (1) design a three-dimensional calibration board with three calibration points, determine welding model;Step (2) according to the calibration point and the welding model, the calibration of the transformation matrix between the calibration board coordinate system and the robot base coordinate system is carried out;Step (3) moves the robot to collect the linear laser calibration line projected on the three-dimensional calibration board by linear laser sensor, obtains calibration feature points, completes hand-eye calibration.This method is simple in operation, and calibration precision is higher, is suitable for on-site rapid calibration, fully meets the precision requirement of automatic guidance welding.

The application belongs to the technical field of mobile manipulator scanning planning, and discloses a mobile manipulator online scanning planning method and system for unknown environment, which comprises the following steps: obtaining candidate chassis target poses according to a two-dimensional occupancy grid map and environment update results; evaluating the candidate chassis target poses to obtain effective targets; the candidate chassis performs trajectory tracking on the effective targets according to a planned path, and simultaneously monitors the path and the targets; if the path is blocked or the targets are invalid, the candidate chassis target poses are reacquired; when the chassis reaches a specified area, scanning positions are selected from candidate observation viewpoints, and it is determined whether the scanning positions are within the working range of the manipulator; if the scanning positions are within the working range of the manipulator, the scanning positions are scanned by the manipulator, so that the scanning coverage integrity, the spatial exploration efficiency and the task execution success rate in a complex environment are improved, and repeated scanning and redundant motion are reduced.

The application discloses a kind of self-adaptive balancing device, method and storage medium of mobile mechanical arm, it is related to mechanical arm balance control technical field.Device includes: balancing device and control system;Balancing device is arranged on the mobile chassis of mobile mechanical arm, for adjusting the balance state of the mobile mechanical arm;Control system is used to calculate the center of gravity position of mobile mechanical arm in real time according to multi-axis mechanical arm mass data, balancing device mass data, mobile chassis mass data and mobile chassis inclination data, when judging that the center of gravity position of mobile mechanical arm deviates from preset operation range, timely control balancing device adjusts the center of gravity position of mobile mechanical arm, ensure that mobile mechanical arm is in balanced state.

Consistent connection strategies for coupling accessories to a robot can help achieve certain objectives, e.g., to tolerate and correct misalignment during coupling of the accessory. In some embodiments, the connection strategy may enable certain accessories to connect to certain sides of a robot. When connected, an accessory may be rigid in yaw, lateral motion, and fore / aft motion, while remaining unconstrained in roll and pitch as well as vertical motion. A sensor may enable detection of the accessory, and a mechanical fuse may release the accessory when a force threshold is exceeded. A mechanical coupler of an accessory may include two connectors, each of which includes a receiving area configured to receive a pin on the robot and a latch configured to retain the pin within the receiving area. The pins (and the receiving areas) may be differently sized, and may be differently arranged.

The present application provides a curtain wall mounting robot, a position control method, and a storage medium. The position control method comprises the following steps: achieving equivalence between a mobile base component and a manipulator component by adding virtual joints, and establishing an overall kinematic model; assigning priorities to different execution tasks in the overall kinematic model to form a first-priority task and a second-priority task, wherein the first-priority task has a higher priority than the second-priority task; upon completion of the first-priority task, scheduling the second-priority task on the basis of a null-space strategy; and performing motion control calculation by means of the overall kinematic model having undergone scheduling, and outputting control data to implement coordinated control between the mobile base component and the manipulator component. The present application solves the problems in the prior art of being unable to implement coordinated control between a manipulator component and a mobile base component and failing to sufficiently exploit the advantages of the redundancy characteristics of a mobile manipulator due to the use of hierarchical control.

The invention relates to a mobile mechanical arm hand-eye calibration method and device and computer equipment. The method comprises the steps that under the condition that a movable chassis of a movable mechanical arm moves to a preset target position, the mechanical arm tail end of the movable mechanical arm is controlled to move into the view field range of an external camera, and a calibration object is fixed to the mechanical arm tail end; acquiring first pose data of the tail end of the mechanical arm relative to the mobile mechanical arm base and second pose data of the calibration object in a camera coordinate system of the external camera, and performing hand-eye calibration on the mobile mechanical arm base and the external camera according to the first pose data, the second pose data and a preset pose transformation relation, the preset pose transformation relation represents the transformation relation between the coordinate system of the calibration object and the coordinate system of the tail end of the mechanical arm. By adopting the method, the hand-eye calibration precision can be improved.

The application provides a mobile manipulator grasping pose planning method and device, the method comprising: determining a target object grasping feasibility map; performing grid discretization processing on the feasibility map to obtain a plurality of grids; determining manipulator joint restriction constraint coefficients, obstacle safety restriction constraint coefficients and operation stability restriction constraint coefficients of all poses of each grid; calculating the hybrid operability of each pose of each grid; selecting the maximum value of the hybrid operability of each pose in the grid as the hybrid operability index of the grid, obtaining an evaluation index set of all grids, selecting the grid corresponding to the maximum value in the evaluation index set as the optimal mobile chassis position of the mobile manipulator, and the pose corresponding to the hybrid operability in the grid is the optimal grasping pose of the manipulator load of the mobile manipulator. The application realizes more flexible grasping operation of the manipulator through the hybrid operability and completes the obstacle avoidance function.