15 results about "Joint acceleration" patented technology

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.

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 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.

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 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.

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 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 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 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 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.

Embodiments of the present application disclose a control method of a dual-arm robot, the dual-arm robot and a storage medium. The method comprises: determining a first pose deviation of an end of a first mechanical arm relative to a target object and a second pose deviation of an end of a second mechanical arm relative to the target object; generating first and second collaborative parameters that are opposite numbers based on the first and second pose deviations; inputting the first and second collaborative parameters into a virtual positive dynamics model respectively to obtain first and second joint accelerations; and controlling the first and second mechanical arms based on the first and second joint accelerations respectively. The first and second collaborative parameters provided by the embodiments of the present application are equivalent to a virtual spring, the virtual spring has elastic characteristics and force buffering capacity, can match the requirements of soft fault tolerance and robust disturbance resistance of the dual-arm collaborative task, and is beneficial to improving the dual-arm collaborative capability, softness and robustness of the dual-arm robot.

The application relates to a robot control method and device, a robot system and a storage medium, wherein the method comprises the following steps: determining joint acceleration of a robot in a next control cycle according to joint torque of the robot in a current control cycle, robot motion information and a predetermined acceleration constraint condition of the robot in the next control cycle; the acceleration constraint condition is determined according to operation space constraint and joint space constraint of the robot, and the operation space constraint and the joint space constraint are determined according to constraint space of the robot; determining joint torque of the robot in the next control cycle according to the joint acceleration of the robot in the next control cycle; and controlling the robot according to the joint torque of the robot in the next control cycle. Through the application, the technical problem that the accuracy of end surgical instruments of the robot moving in a limited space cannot be ensured is solved.

This application provides a trajectory planning method, apparatus, robot, and computer-readable storage medium, relating to the field of robotics. The method includes: determining a transition path between a first motion segment and a second motion segment; wherein the first and second motion segments include any one of a linear motion segment, a circular motion segment, and a joint motion segment; and performing trajectory planning on the first motion segment, the second motion segment, and the transition path based on constraint information to obtain a target trajectory; wherein the constraint information includes at least one of joint velocity constraint information, joint acceleration constraint information, and joint torque constraint information of the robot joint. This application can calculate transition paths between various types of motion segments and plan the motion trajectories of multiple motion segments and transition paths based on constraint information during robot joint movement, thereby achieving smooth transitions between various types of motion segments and improving the effectiveness of smooth transitions.

The invention discloses a motion control method, equipment, medium and product for a wheel-legged mobile platform to pass through a limited space, and the method comprises the steps: determining an expected feed-forward control moment of a joint based on a single-leg dynamic model according to an expected joint position, joint speed and joint acceleration in the motion process of the wheel-legged mobile platform passing through the limited space; wheel feed-forward torque is determined according to the rolling resistance of the wheels and the positive pressure of the wheel-legged maneuvering platform on the wheels; wheel driving force is determined according to the wheel feed-forward torque, the wheel radius, the expected wheel rotating speed and the actual wheel rotating speed; determining a feedforward control torque of the joint based on the wheel driving force; according to the expected feed-forward control torque of the joint and the feed-forward control torque of the joint, the expected joint control torque is determined; and controlling the wheel-legged mobile platform to pass through the limited space based on the expected joint control moment and the wheel driving force. The accuracy and stability of the wheel-legged mobile platform passing through the limited space can be effectively improved.