34 results about "Joint acceleration" patented technology

The present application relates to the technical field of robot control. Provided are a robot obstacle avoidance control method and a related device. In the present application, an RMP mapping tree is constructed on the basis of individual actual spatial positions of all obstacles currently present in an operating environment where a target robot is located, such that a root node task of the RMP mapping tree corresponds to a robot joint space, and corresponding leaf node tasks comprise a position motion task and a pose motion task of a robot tail end executing an expected operation, and comprise obstacle avoidance motion tasks of a plurality of robot key parts of the robot tail end respectively performing obstacle avoidance on the obstacles; and then, geometric dynamical systems involving speed information are respectively constructed for various motion tasks, and an expected joint acceleration is solved on the basis of an RMP push-forward operation and an RMP pull-back operation, so as to control the target robot to move, thereby enabling the robot to achieve expected operation execution effects while avoiding dynamic obstacles with high agility and real-time performance.

The invention relates to the technical field of foot type robot control, and provides a robot ground touching force estimation method and system based on a high-order finite time observer, and the method comprises the steps: building a foot type robot leg dynamic model; joint positions, speeds and joint acceleration driving items are selected as state variables, and a leg state space model of the legged robot is established; according to the established state space model, step-by-step iteration of an estimated value of a state variable is utilized, a power form of a nonlinear sign function and a set gain parameter matrix are combined, a high-order finite time observer is established in a recursive mode, and estimation of the ground touching force of the foot end of the foot type robot is obtained. A high-order finite time observer is established in combination with a nonlinear sign function and a designed parameter matrix, so that a ground touching force estimation error can be converged to a certain boundary within finite time, and the problems that a traditional extended state observer is low in ground touching force estimation precision and only can estimate slowly-changing ground touching force are effectively solved.

The embodiment of the invention discloses a control method of a double-arm robot, the double-arm robot and a storage medium. The method comprises the steps that the first pose deviation of the tail end of a first mechanical arm relative to a target object and the second pose deviation of the tail end of a second mechanical arm relative to the target object are determined, and a first cooperation parameter and a second cooperation parameter which are opposite in number are generated based on the first pose deviation and the second pose deviation, and the first cooperative parameter and the second cooperative parameter are input into the virtual positive dynamic model, a first joint acceleration and a second joint acceleration are obtained, and the first mechanical arm and the second mechanical arm are controlled based on the first joint acceleration and the second joint acceleration. The first cooperative parameter and the second cooperative parameter provided by the embodiment of the invention are equivalent to a virtual spring, and the virtual spring has an elastic characteristic and a force buffering capability, can be matched with the requirements of a double-arm cooperative task on compliant fault tolerance and robust interference resistance, and is beneficial to improving the double-arm cooperative capability, compliance and robustness of the double-arm robot.

The invention relates to the field of robots, in particular to a robot, a walking control method and device thereof and a program product. The method comprises the steps that the stability of the robot in different states is collected, and balance evaluation index items of the robot are determined according to the stability of the robot in different states; determining a target function of the robot according to the balance evaluation index in combination with a predetermined robot metabolism energy consumption rate item, a muscle activation level item, a joint acceleration item, a passive joint torque item and an arm driving excitation item; performing optimization simulation on the target function to determine an angle change curve of each joint of the simulation robot; and controlling the robot to walk according to the angle change curve. The objective function comprises the balance evaluation index item and the walking smoothness index item, so that the walking stability and smoothness of the robot can be effectively improved in the optimized walking control process, and the performance of the robot in practical application is improved.

The present invention proposes a multi-sensor fusion prosthetic hand gripping force feedback control method, including a multi-sensor fusion and feedback method, a gripping force prediction method and a PD-based CMAC manipulator gripping control method; the multi-sensor fusion and feedback method includes collecting surface electromyographic signals of muscles, collecting the temperature, contact force, sliding state of the object gripped by the prosthetic hand, collecting the joint acceleration and angular velocity corresponding to the gripping action, and collecting the actual gripping force of the prosthetic hand's gripping action; the gripping force prediction method predicts the gripping force of the current gripping action; the multi-sensor fusion and feedback method fuses the data to generate the prosthetic end perception information of the current gripping action; the present invention allows the user to adjust the actual gripping force and gripping action in time to achieve accurate and stable gripping of objects, while detecting the real-time temperature and contact force of the gripped object during the gripping process, and feeding back the tactile information to the user through the vibration and display module.

The invention relates to the field of mechanical engineering, and discloses an intelligent optimization method and system for a loading and unloading arm mechanism based on reinforcement learning, and the method comprises the steps: extracting environment data of an application scene, extracting physical parameters of a loading and unloading arm, analyzing a working process of the loading and unloading arm, and extracting operation data of the working process; analyzing joint torque and joint acceleration of the loading and unloading arm, calculating operation performance indexes of the loading and unloading arm, and analyzing working stability of the loading and unloading arm; analyzing an action sequence and an operation path of the loading and unloading arm, analyzing moment limitation and motion constraint of the loading and unloading arm, and determining an optimal operation path of the loading and unloading arm; constructing a sensor network of the loading and unloading arm, collecting working data of the loading and unloading arm in real time, analyzing risk factors in the working data, and calculating the risk probability of the loading and unloading arm; and a reinforcement learning optimization model of the loading and unloading arm is constructed, optimization parameters of the loading and unloading arm are analyzed, and intelligent optimization of the loading and unloading arm is executed. The operation efficiency and safety of the loading and unloading arm can be improved.

The invention discloses a motion track planning method, device and system of a mechanical arm and a storage medium, and relates to the technical field of mechanical control. The method comprises the following steps: acquiring an initial waypoint, a tail waypoint and a middle waypoint; calculating an absolute distance from each waypoint to the initial waypoint and a total absolute distance; setting a preset space velocity; calculating total spent time and time for arriving at each waypoint; and the angle vector of the shaft motor in the corresponding joint space and the constant speed section speed and the variable speed section acceleration of the shaft motor in each path section are calculated, the sampling time is preset, the joint acceleration vector real-time value, the velocity vector real-time value and the position vector real-time value of the mechanical arm at each time point are calculated, and the motion trail of the mechanical arm is planned. According to the embodiment of the invention, the accuracy and the working efficiency of the movement of the mechanical arm are improved, shaking and impact are reduced, and the stability and the safety of the movement are improved.

A robot control method and apparatus, and a device and a medium. The robot control method comprises: on the basis of an initial point and a target point of an end effector of a robot, determining a trajectory point set; acquiring joint control information corresponding to each joint of the robot when the end effector is located at each trajectory point in the trajectory point set, wherein the joint control information comprises at least one of a joint position, a joint speed and a joint acceleration; and for a first trajectory point and a second trajectory point that are adjacent to each other in the trajectory point set, and on the basis of first joint control information corresponding to each joint at the first trajectory point and second joint control information corresponding to each joint at the second trajectory point, controlling each joint to move, such that the end effector moves from the first trajectory point to the second trajectory point.

The embodiment of the invention discloses a robot motion control method, computer equipment and a computer storage medium. An optimization function about the contact force between the robot and the object and the joint acceleration of the robot and a floating base kinetic model of the robot are established, and the contact force constraint between the feet of the robot and the ground is established according to the friction constraint relation corresponding to the feet of the robot and the supporting constraint relation corresponding to the feet of the robot; an expected contact force constraint model about the contact force between the robot and the object and the joint acceleration of the robot is established according to the preset contact force, that is, the balance stability of the robot is reflected in friction constraint and inequality constraint for preventing toppling on the sole of the robot, and it is ensured that the robot can be kept balanced and stable all the time in heavy object operation; secondly, joint acceleration of the robot and contact force of the robot and an external object are solved in a unified mode, and contact force control and position adaptation of the robot in the operation process of the heavy object can be considered;

The application belongs to the technical field of robot dynamics parameter identification, and discloses a double sparse efficient identification method and system for robot dynamics parameters. The method comprises the following steps: S1, collecting joint positions, joint speeds, joint torques and joint accelerations of a robot to be processed at each time; S2, constructing an implicit dynamics equation of the joint torque by taking the joint torque as a target; S3, constructing a base function database, evaluating the importance of each base function in the base function database, thereby completing the first sparse of the base function; and performing sparsification on the coefficient matrix to make some elements in the coefficient matrix 0, thereby completing the second sparse of the base function, determining the base function and the coefficient matrix, and realizing the acquisition of an explicit dynamics equation of the joint torque. Through the application, the technical problems of complex theoretical modeling or low interpretability of a black box model in the prior art are solved.

The application belongs to the technical field of robots, and particularly relates to a robot force control method and device, a computer readable storage medium and a robot. The method comprises: generating a Riemann motion strategy-based motion generation for an overall target task of a robot to obtain joint acceleration control quantity at a current control moment; determining joint torque control quantity at the current control moment according to the joint acceleration control quantity at the current control moment based on a preset control quantity mapping relationship; wherein the control quantity mapping relationship is a mapping relationship between the joint acceleration control quantity and the joint torque control quantity; and performing torque control on the robot according to the joint torque control quantity at the current control moment to execute the overall target task. In the application, the position control of the robot is converted into torque control through the preset control quantity mapping relationship, so that torque control of the robot can be realized under the algorithm framework of RMP.

A method to control a robot to perform at least one Cartesian or joint space task comprises using quadratic programming to determine joint forces, in particular joint torques, and / or joint accelerations of said robot based on at least one cost function which depends on said task.

The present invention relates to the technical field of mining hydraulic pipeline installation robots, and specifically discloses a mining hydraulic pipeline auxiliary installation robot fault monitoring system, including a monitoring parameter acquisition module, a hydraulic system state evaluation module, a robot joint performance evaluation module, a robot energy consumption change analysis module, a fault warning terminal, and a cloud database. By evaluating the hydraulic system efficiency of the robot during operation, and combining the joint torque, joint displacement, and joint acceleration in the robot joint parameters for comprehensive analysis and calculation, the robot's faults during operation are further monitored and analyzed. By monitoring and analyzing the fault points of the robot during operation from different directions, combined with the energy consumption parameters of the robot corresponding to each monitoring period during operation, the accuracy and reliability of the fault monitoring and evaluation results of the robot corresponding to each monitoring period during operation can be greatly improved.

The present invention relates to a method for suppressing sudden changes in the operating force of a reconfigurable manipulator. Based on the matrix perturbation theory, a space manipulator joint torque compensation is proposed to achieve the compensation torque equation and the dynamic equation containing the Jacobian matrix, thereby realizing the redistribution of the joint torque of a generalized redundant space manipulator fault. At the same time, the method of the present invention combines the advantages of the minimum norm method and the minimum torque method, and proposes a joint acceleration inverse solution method obtained by minimizing the joint torque as the optimization goal, so as to solve the instability of the joint values ​​and the joint singularity problems caused by the calculation of the minimum joint torque method.

The application provides an end tracking method for a foot-arm robot based on model predictive control and whole-body force control, and the method comprises the following steps: acquiring joint feedback data of a quadruped robot and a mechanical arm, and an end trajectory instruction of the mechanical arm at a current time; estimating a current pose and a current speed of a robot trunk part through a state estimator; obtaining a body position, a body speed, a body acceleration, a joint position, a joint speed, a joint acceleration and a foot end contact force trajectory of the quadruped robot in a time period as a first layer control architecture; establishing a whole-body dynamics model of the quadruped robot carrying the mechanical arm, adding balance related constraints, body and joint tracking constraints and foot end force tracking constraints as a second layer control architecture; and combining the first layer control architecture and the second layer control architecture to obtain joint torque of the quadruped robot carrying the mechanical arm. The application can realize tracking of an end trajectory while not violating the physical limit of the robot.

The application belongs to the technical field of mechanical arms, and particularly relates to a mechanical arm control method and device, a computer readable storage medium and a mechanical arm. The method comprises the following steps: acquiring an actual state quantity and a planning state quantity of a mechanical arm; establishing an optimization objective function of the mechanical arm according to the actual state quantity and the planning state quantity; optimizing and solving the optimization objective function according to a preset control constraint condition to obtain motion control quantities such as end contact force, joint acceleration and joint torque of the mechanical arm; and controlling the mechanical arm to move according to the motion control quantities. Through the application, a unified control thought is provided for various motions of the mechanical arm, a complex control problem of the mechanical arm is set as a unified optimization control problem, and the control complexity is effectively reduced.

The application discloses a kind of composite material laying robot trajectory optimization methods, by combining NURBS fitting method and INGSA-Ⅱ multi-objective optimization algorithm are carried out joint parameter fitting of laying robot, realize time optimal, energy consumption minimum and impact minimum, after inverse solution of pressure vessel head joint angle optimization, joint related parameters are all smooth and continuous, pressure vessel head operating time is shorter, trajectory efficiency is high, the integral of joint acceleration and joint jerk with time is smaller, energy consumption and impact are lower;Realized in improving the work efficiency of robot while reducing the energy consumption of laying robot production core mold, reduce the impact in the movement process of laying robot, improve the smoothness of laying robot movement, prolong the service life of laying robot.

The application discloses a kind of joint acceleration driven redundancy manipulator uniform wear motion control method, it is related to manipulator motion planning technical field, it can also be used in financial field.Therein, the method includes: constructing the wear uniformity parameter of each joint of redundancy manipulator in the desired repetitive motion, wherein the smaller the value of the wear uniformity parameter, the more uniform the wear of each joint of the redundancy manipulator;According to the wear uniformity parameter representation, the motion control optimization scheme of the redundancy manipulator in the acceleration layer is established, wherein the motion control optimization scheme minimizes wear uniformity parameter as optimization goal;According to the motion control optimization scheme, the acceleration information of each joint of the redundancy manipulator is solved;The acceleration information of each joint is sent to controller, and the controller is used to drive the redundancy manipulator to track the desired motion trajectory according to the acceleration information of each joint to carry out uniform wear motion.

The present invention discloses a joint constraint trajectory planning method for a robot, comprising: determining a fifth parameter according to a joint torque constraint condition, and determining a sixth parameter according to a joint acceleration constraint condition; determining a path speed range of a preset path point according to a joint speed constraint condition, and determining a target constraint condition of a target function according to the path speed range, the fifth parameter, and the sixth parameter; optimizing the path speed of a target robot at a preset path point according to the target constraint condition and the target function, and determining a planned joint position corresponding to the target robot at the trajectory planning moment according to the optimal path speed. The present invention performs joint constraint trajectory planning on a target robot by adding joint torque constraints, joint acceleration constraints, and joint speed constraints, thereby avoiding problems of joint overload or low joint performance utilization in the target robot, and improving the accuracy of the robot's trajectory planning.

Embodiments of the present application disclose a robot control method, device, equipment and medium. The method comprises: determining a trajectory point set based on an initial point and a target point of an end effector of a robot; obtaining joint control information corresponding to each joint of the robot when the end effector is at each trajectory point in the trajectory point set; wherein the joint control information comprises at least one of joint position, joint speed and joint acceleration; for each adjacent first trajectory point and second trajectory point in the trajectory point set, controlling the movement of each joint according to the first joint control information corresponding to each joint at the first trajectory point and the second joint control information corresponding to each joint at the second trajectory point, so that the end effector moves from the first trajectory point to the second trajectory point. The technical solution can accurately control the movement of each joint of the robot, thereby improving the accuracy of robot control and ensuring the stability and safety of robot operation.

The invention relates to a robot control method and device, a robot system and a storage medium, and the method comprises the steps: according to the joint torque of a robot in a current control period, robot motion information and a predetermined acceleration constraint condition of the robot in a next control period, determining the joint torque of the robot in the next control period; the joint acceleration of the robot in the next control period is determined; the acceleration constraint condition is determined according to an operation space constraint of the robot and a joint space constraint of the robot, and the operation space constraint and the joint space constraint are determined according to a constraint space of the robot; according to the joint acceleration of the robot in the next control period, the joint torque of the robot in the next control period is determined; and controlling the robot according to the joint torque of the robot in the next control period. The technical problem that the movement accuracy of the surgical instrument at the tail end of the robot in the limited space cannot be guaranteed is solved.

The present disclosure relates to the technical field of foot-type robot control, and provides a robot touch ground force estimation method and system based on a high-order finite time observer, which comprises: establishing a foot-type robot leg dynamics model; selecting joint position, velocity and joint acceleration driving term as state variables, and establishing a foot-type robot leg state space model; according to the established state space model, using step-by-step iteration of the estimated value of the state variable, combining the power form of the nonlinear sign function and the set gain parameter matrix, and establishing a high-order finite time observer through a recursive mode to obtain the estimation of the foot-type robot foot end touch ground force. The high-order finite time observer is established in combination with the nonlinear sign function and the designed parameter matrix, so that the touch ground force estimation error can converge within a certain boundary in a limited time, and the problems of low touch ground force estimation accuracy and slow change touch ground force estimation of the traditional extended state observer are effectively solved.

The present application provides a robot joint control method, device, and storage medium, relating to the technical field of robots. The method includes: obtaining the joint acceleration of a target joint at the current moment based on the preset limit parameters for the rotation of the target joint in the robot; obtaining the target joint position of the target joint at the next moment according to the expected joint position of the target joint at the current moment and the joint acceleration of the target joint; and performing motion control on the target joint in the robot according to the target joint position of the target joint at the next moment. By applying the embodiments of the present application, it is possible to take into account the preset limit parameters for the rotation of the target joint, constrain the change in the joint position of the robot through the preset limit parameters, and then, when controlling the target joint based on the obtained target joint position of the target joint at the next moment, achieve compliant control of the target joint.

The invention relates to the technical field of mining hydraulic pipeline installation robots, and particularly discloses a mining hydraulic pipeline auxiliary installation robot fault monitoring system which comprises a monitoring parameter acquisition module, a hydraulic system state evaluation module, a robot joint performance evaluation module, a robot energy consumption change analysis module, a fault early warning terminal and a cloud database. Fault evaluation is carried out on hydraulic system efficiency of the robot in the operation process, comprehensive analysis and calculation are carried out in combination with joint torque, joint displacement and joint acceleration in robot joint parameters, and faults of the robot in the operation process are further monitored and analyzed. By monitoring and analyzing the fault points of the robot in the running process from different directions and combining the energy consumption parameters of the robot in the running process corresponding to the monitoring periods, the accuracy and reliability of the fault monitoring and evaluation result of the robot in the corresponding monitoring periods in the running process can be improved to a great extent.

A robot force control method, and a computer-readable storage medium and a robot using the same are provided. The method includes: obtaining a joint acceleration control amount at a current control moment of the robot by performing a Riemannian Motion Policy (RMP)-based motion generation on an overall target task of the robot; determining, based on a preset control amount mapping relationship, a joint torque control amount at the current control moment according to the joint acceleration control amount at the current control moment, and executing the overall target task by performing a torque control on the robot according to the joint torque control amount at the current control moment. Through the above-mentioned method, the position control of robot is converted into the torque control of robot through a preset control amount mapping relationship, thereby realizing the torque control of robot under the algorithm framework of RMP.

The invention discloses a robot joint accelerated fatigue testing device and a testing method thereof, and relates to the technical field of robot testing for new energy automobile production, and the device comprises a force application assembly which comprises a first electric cylinder fixedly installed at the top of a cabinet and a wheel carrier fixedly connected to the bottom of the telescopic end of the first electric cylinder; the pressure roller is rotationally connected to the bottom of the wheel frame; the bearing assembly comprises a suspension shaft arranged in the middle of the cabinet, two groups of radial electromagnets arranged on the two sides of the suspension shaft and two axial electromagnets arranged at the two ends of the suspension shaft in the axis direction of the suspension shaft, each group comprises three radial electromagnets, and the radial electromagnets are arranged in an annular array with the axis of the suspension shaft as the center; the feeding assembly comprises a linear module fixedly installed below the machine cabinet, a U-shaped frame fixedly installed on the top of a sliding block of the linear module, and two sets of limiting wheels rotationally connected to the two sides of the top of the U-shaped frame. The problems that in the prior art, bearing fatigue testing cannot be conducted continuously, and efficiency is low are solved, and the physical blocking defect of supporting of a traditional support is avoided.

The embodiment of the invention discloses a robot control method and device, equipment and a medium. Comprising the steps of determining a track point set based on an initial point and a target point of an end effector of a robot; acquiring joint control information corresponding to each joint of the robot when an end effector is located at each track point in the track point set; wherein the joint control information comprises at least one of a joint position, a joint speed and a joint acceleration; for each adjacent first track point and second track point in the track point set, controlling each joint to move according to first joint control information corresponding to each joint at the first track point and second joint control information corresponding to each joint at the second track point, and the first track point and the second track point are arranged in parallel, so that the end effector moves from the first track point to the second track point. According to the technical scheme, all joints of the robot can be accurately controlled to move, so that the control accuracy of the robot is improved, and the running stability and safety of the robot are guaranteed.

The invention provides a multi-task hierarchical control method for a redundant mechanical arm, which comprises the following steps of: S1, constructing an error minimization problem taking a joint speed as an optimization variable according to a forward kinematics model of an ith subtask of the redundant mechanical arm and an error relationship between a position and a speed layer; s2, solving the minimization problem in the step S1 based on a gradient method, and establishing a single task control model of the ith subtask; s3, a null space projection matrix is introduced, a priority Jacobian matrix is constructed, all the single-task control models in the step S2 are integrated into a multi-task hierarchical control model, and joint acceleration is output; and S4, the redundant mechanical arm is controlled according to the joint acceleration output by the multi-task hierarchical control model in the step S3. According to the method, when the total sub-task dimension exceeds the degree of freedom of the mechanical arm, the low-priority tasks are decoupled from the high-priority tasks, and the multi-task execution capacity of the redundant mechanical arm is improved.

The present application belongs to the technical field of robots, and particularly relates to a robot torque control method and apparatus, a computer-readable storage medium and a robot. The method comprises: with respect to an overall target task of a robot, performing motion generation on the basis of Riemannian motion policies, so as to obtain a joint acceleration control amount at the current control moment; on the basis of a preset control amount mapping relationship and according to the joint acceleration control amount at the current control moment, determining a joint torque control amount at the current control moment, the control amount mapping relationship being a mapping relationship between joint acceleration control amounts and joint torque control amounts; and, according to the joint torque control amount at the current control moment, performing torque control on the robot, so as to execute the overall target task. The present application uses the preset control amount mapping relationship to convert position control of robots into torque control, so that torque control of robots can be achieved within the RMP algorithm framework.

The application relates to the field of mechanical engineering and discloses an intelligent optimization method and system for a loading and unloading arm mechanism based on reinforcement learning, which comprises the following steps: extracting environment data of an application scene, extracting physical parameters of the loading and unloading arm, analyzing a work flow of the loading and unloading arm, and extracting operation data of the work flow; analyzing joint torque and joint acceleration of the loading and unloading arm, calculating an operation performance index of the loading and unloading arm, and analyzing work stability of the loading and unloading arm; analyzing a motion sequence and an operation path of the loading and unloading arm, analyzing torque limitation and motion constraint of the loading and unloading arm, and determining an optimal operation path of the loading and unloading arm; constructing a sensor network of the loading and unloading arm, collecting work data of the loading and unloading arm in real time, analyzing risk factors in the work data, and calculating a risk probability of the loading and unloading arm; constructing a reinforcement learning optimization model of the loading and unloading arm, analyzing optimization parameters of the loading and unloading arm, and executing intelligent optimization of the loading and unloading arm. The application can improve operation efficiency and safety of the loading and unloading arm.